The Effects of Slow Frame Rates on Human Performance 

by Jennifer E. Thropp and Jessie Y.C. Chen 

ARL-TR-3813 June 2006 

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ARL-TR-3813 June 2006 

The Effects of Slow Frame Rates on Human Performance 

Jennifer E. Thropp 

University of Central Florida 

Jessie Y.C. Chen 

Human Research and Engineering Directorate, ARL 

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14. ABSTRACT 

We conducted a comprehensive examination of the effects of different frame rates on human performance and reviewed 

more than 50 studies and summarized them in the areas of psychomotor performance, perceptual performance, behavioral 

effects, and subjective perception. Overall, there seems to be strong support for a threshold of around 15 Hz for many tasks, 

including those that are psychomotor and perceptual in nature. Less impressive yet acceptable performance may be 

accomplished at around 10 Hz for many tasks. Subjective reactions to video quality seem to support rates of 5 Hz, although 

videos presented at 15 Hz and above are generally more widely preferred. 

15. SUBJECT TERMS

 degraded video; frame rate; human performance 

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 Jessie Y.C. Chen 

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iii 

Contents 

List of Figures iv

1. Introduction 1

1.1 Background .....................................................................................................................1 

1.1.1 The Mechanisms of FR .......................................................................................2 

1.1.2 Related Sources of Temporal Distortion .............................................................2 

1.1.3 Update Rate and Refresh Rate.............................................................................3 

1.1.4 Variable Versus Constant FR..............................................................................4 

1.2 Adverse Effects of FR on Task Performance..................................................................4 

1.2.1 Task Dependency ................................................................................................5 

1.2.2 Viewing Condition Dependency .........................................................................6 

1.2.3 Display Luminance and the Number of GLs.......................................................7 

1.2.4 Auditory Cues in Addition to Visual Cues..........................................................7 

1.2.5 End User Characteristics .....................................................................................7 

2. Psychomotor Performance 8

2.1 Placement Performance...................................................................................................8 

2.1.1 Placement Task Conclusion ................................................................................9 

2.2 Tracking Performance .....................................................................................................9 

2.2.1 Tracking Task Conclusion.................................................................................11 

3. Perceptual Performance 13

3.1 Target Recognition Performance...................................................................................13 

3.1.1 Constant FR Effects of Target Recognition ......................................................13 

3.1.2 Variable FR Effects of Target Recognition.......................................................15 

3.1.3 Target Recognition Performance Conclusion ...................................................15 

3.2 Perception and Psychophsics.........................................................................................16 

3.2.1 Perception and Psychophsics Conclusion .........................................................17 

4. Behavioral Effects 19

5. Subjective Assessment 19

6. Conclusions 22
iv 

7. References 25

Appendix A. Summary of FR Effects on Psychomotor Performance 31

Appendix B. Summary of FR Effects on Perceptual Performance 33

Appendix C. Summary of FR Effects on Subjective Assessment 35

Glossary of Acronyms 37

Distribution List 38 

List of Figures 

Figure 1. Summary of FR effects on psychomotor performance................................................. 12 

Figure 2. Summary of FR effects on perceptual performance.................................................... 18 

Figure 3. Summary of FR effects on subjective assessment........................................................ 21 

Figure 4. Summary of effects of slow FR (figures 1 through 3).................................................. 22 
1 

1. Introduction 

1.1 Background 

In recent years, there have been growing applications of robotic technologies in fields such as 

space exploration, search and rescue, national defense, entertainment, police special weapons 

and tactics operations, health care, and personal assistance (Chen, Haas, Pillalamarri, & 

Jacobson, 2006). In the military domain, the U.S. Army’s Future Combat System (FCS) 

program, for the first time in the U.S. military history, envisions a future battlefield incorporating 

a wide array of unmanned assets including aerial and ground vehicles as well as unmanned 

sensor platforms (Unit of Action Maneuver Battle Lab, 2003). These unmanned systems will 

extend the ranges and capabilities of their human operators’ perception and action and will have 

a major impact on future combat operations (Oron-Gilad, Chen, & Hancock, 2005). In order to 

effectively employ the unmanned assets, it is essential that the robotic operator maintain an 

effective perception of the remote environment through the communication channel between the 

human operator and the robot. However, factors such as distance, obstacles, bandwidth, and 

electronic jamming may pose challenges for maintaining sufficient signal strength (French, 

Ghirardelli, & Swoboda, 2003). As a result, the quality of video feeds that a robotic operator 

relies on for remote perception may be degraded and the operator’s performance may be 

compromised (Van Erp & Padmos, 2003). 

Common forms of video degradation caused by low bandwidth include reduced frame rate (FR) 

(frames per second), reduced resolution of the display (pixels per frame), and a lower gray scale 

(number of levels of brightness or bits per frame) (Rastogi, 1996). The product of FR, 

resolution, and gray scale is bandwidth (bits per second), and it is important to determine how to 

balance these three variables with a given bandwidth so that operator performance can be 

optimized (Sheridan, 1992). Generally, for applications in virtual environments (VEs), many 

researchers recommend 10 Hz (i.e., 10 frames per second or 10 fps) to be the minimum FR to 

avoid performance degradation (Watson, Walker, Ribarsky, & Spaulding, 1998). However, 

depending on the nature of the tasks, the same degrees of slowing of FRs may have different 

effects on human performance. To provide a comprehensive examination of the effects of 

different FRs on human performance, this report reviewed more than 50 studies and summarized 

them in the areas of psychomotor performance, perceptual performance, behavioral effects, and 

subjective perception. First, some background information about the mechanisms of FR and 

other related sources of temporal distortions are presented. This discussion is followed by a brief 

review of the major moderating factors that can impact the adverse effects of slow FR on human 

performance. 
2 

1.1.1 The Mechanisms of FR 

FR is the tempo at which the new frames of the graphical scene are computed, rendered, and 

displayed. Frame time (the length of time required to compute, render, and display the image), 

which is the inverse of FR, is the primary source of delay in desktop personal computers; in VEs, 

input devices such as three-dimensional (3-D) trackers are additional sources of delay (Watson, 

Walker, Woytiuk, & Ribarsky, 2003). FR is limited by several computational factors, including 

frame time, which is then determined by the current computational demands and the actual 

image displayed (i.e., complexity or level of detail [LOD]). Possible sources of low FR in VEs 

include the computation required to process tracker data (e.g., input from peripheral devices such 

as mice or eye trackers), computation speed of the effects of user movement (e.g., use of headmounted displays [HMDs]), the graphical rendering time, and communication overhead in 

distributed systems. If any of these factors overwhelms the system or bandwidth limitations, the 

FR may be reduced. FR, however, is not an entity that exists in isolation; it is also associated 

with other computational demands. 

1.1.2 Related Sources of Temporal Distortion 

Bryson (1993) differentiates FR from lag, two major sources of temporal distortion in real-time 

computing systems. Lag is the temporal discrepancy between the data stream from the tracker 

(e.g., input device such as a mouse) and the actual resulting graphic (Bryson, 1993). Therefore, 

lag is the time delay between the user’s action and its displayed result (Watson, Spaulding, 

Walker, & Ribarsky, 1997). In terms of teleoperation, delay is considered to be the temporal 

difference between communication between the local and remote sites (i.e., how long it takes for 

the user’s command or input to see a result in the system’s action) (Tharp, Liu, French, Lai, & 

Stark, 1992). Lag is also referred to as delay, latency, and system responsiveness (SR). 

Lag is created by the following factors: delays in tracker signal, delays in communication 

between tracker and computer, delays from computations involved in processing tracker data, 

and delays from graphical rendering. SR resolution, however, can be complicated. SR is the 

combination of system latency (SL) and the time between the completion of the user’s last action 

and the next source of input into the display. Furthermore, Watson et al. (1997) explain that 

frame time, SL, and SR vary randomly. SL is the frame time plus time needed for the system to 

collect input samples from the real world, such as tracker performance. The variation in latency 

is greater than the variation in frame time, and the variation in SR is the greatest, as it builds 

upon the variation in both frame time and SL. Thus, it is important to consider the means and 

the standard deviations of these display speeds. 

Watson et al. (2003) maintain that there are several factors that cause delay in an interactive 

graphics system, some of which affect only frame time, while others impact only latency, and 

still others impact both frame time and latency. However, all these potential sources impact SR. 

Thus, FR and lag are closely related and are often manipulated at the same time (e.g., see Ware 
3 

& Balakrishnan, 1994). Bryson (1993) has stated that it is difficult to isolate the effects of lag 

and FR from other types of VE distortions. Watson et al. (1997) also state that lag is closely 

associated with FR and that they should both be considered by designers. However, there is not 

much research to guide these designers. 

Latency and FR occur together but must be carefully manipulated in experiments in order for 

effects to be properly detected. Ellis, Adelstein, Baumeler, Jense, and Jacoby (1999) found that 

latency was a more reliable and stronger influence than FR on tracking performance in a VE. In 

a tracing task, latency was also more influential, having a multiplicative effect on response time 

(Arthur, Booth, & Ware, 1993). This may be because latency can be experimentally varied over 

a greater range than FR. For instance, in a study by Ellis et al. (1999), experimental latency 

ranged from 80 to 480 ms, yielding a proportion of 1:6, whereas the FR range of 6 to 20 fps 

yields a proportion of 1:3.7. 

1.1.3 Update Rate and Refresh Rate 

Update rate in teleoperation or in VE applications refers to the frequency at which the image of 

the remote site is captured and then displayed to the remote operator (e.g., via HMD or other 

displays), and it depends on the bandwidth limitation (Liu, Tharp, French, Lai, & Stark, 1993). 

Update rate, therefore, is the upper limit and determinant of display rate. For instance, if the FR 

of the HMD peaks at 100 Hz, and the update rate was 30 Hz, images could only be displayed at a 

maximum rate of 30 Hz. Usually, in the VE applications, FRs are higher than the update rates, 

so the image would appear smooth. In some VE literature, however, update rate and FR are 

sometimes used interchangeably (Kolasinski, 1995). 

Refresh rate, on the other hand, refers to the number of images presented to the eye every second 

(usually between 60 and 10 Hz) (Richard, Birebent, Coiffet, Burden, Gomex, & Langrana, 

1996). Basically, refresh rate is a hardware-determined constant, while update rate can vary 

widely based on scene complexity and other factors such as available computing power for 

generating the images (Kolasinski, 1995; Pausch, Crea, & Conway, 1992). The following 

example by Richard et al. helps to clarify the distinction between refresh rate and FR: a display 

system with a refresh rate of 60 Hz and an FR of 4 Hz will present 15 consecutive identical 

images before there are any changes in the scene. 

Watson et al. (1998) state that high LOD in a frame’s image and adequate SR facilitate user 

performance, yet make strong computational demands that often end in an LOD/SR trade-off. 

Update rate is directly proportional to bandwidth and is impacted by factors such as computation 

and rendering speeds of the graphics system. Thus, update rate could be increased if scenes were 

generated with simpler components such as lines and bioptic images as opposed to polygons and 

stereo images (Liu et al., 1993). Cai (2004) describes the merit of context-aware displays, in 

which the human user’s perceptual state (e.g., user’s scanning behavior with context 

anticipation) and the actual display content are monitored in order to provide the optimum LOD 
4 

for that specific image. This is an important consideration since human visual search can be 

guided by content and purpose (Yarbus, 1967), and excessive LOD can be minimized when not 

needed in order to allocate bandwidth to other demands, such as higher FR. In terms of temporal 

resolution, Cai (2004) found that when video was presented at less than 4 Hz, bandwidth usage 

was clearly lower than continuous streaming at approximately 17 Hz. 

1.1.4 Variable Versus Constant FR 

Many bandwidth studies have empirically manipulated constant FRs. Yet the amplitude and 

deviation of FRs can vary in a computing system, ultimately yielding a variable FR which may 

be reported as a range or mean. This variability can occur in presentations with significant 

change in the detail between scenes in the frames. Normally, in VEs, an adaptive detail 

management system adjusts the object polygon count from frame to frame, depending on the 

LOD needed, and consequently, this determines the frame update rate in order to present an 

approximately constant polygon count in each scene. However, when the LOD changes 

dramatically between frames, an adaptive detail management system may initially calculate the 

timing of the next frame erroneously. 

Fluctuations in the actual frame times occur even when a specific FR is sought in a controlled 

environment. In other words, a particular FR can actually be a range of FRs, which yields a 

mean FR along with standard deviations in frame time. For instance, Watson et al. (1997) used 

the experimental stimuli presented for a 100-ms frame time and introduced a standard deviation 

in frame time of 20 ms, which in turn generated a range of frame times of 72 to 129 ms (the 

inverse of which corresponds to a range of FRs of 13.9 to 7.8 Hz). The implementation of frame 

time standard deviations can replicate the reality that numerous mechanisms result in a variable 

rather than constant FR in video transmission. Procedures for calculating variable FR values are 

presented in detail in Watson et al. (1997). 

1.2 Adverse Effects of FR on Task Performance 

Extremely low update rates can be problematic. As the FR becomes lower, the time (lag) 

between frames becomes longer, and the scene may appear jittery. Objects may consequently 

appear to move in saccades, and the human visual system has to conduct spatiotemporal 

interpolation to “fill” these visual gaps (Richard et al., 1996). Arthur et al. (1993) state that 

frame update rate and the lag in receiving and processing tracker data are among the two factors 

that are often associated with human performance in virtual worlds. Head-coupled tracking 

involves tracking head movements so that when the user moves his or her head, the perspective 

generated on the display will mimic real-life changes in perspective from head movements. 

Arthur et al. state that FR is directly related to a specific type of head-coupled display system lag 

in which there is a delay between eye position reception and display update. This is the time to 

compute and render a scene from the user’s perspective, since current tracker measurements are 

needed; two are needed if the display is stereoscopic. 
5 

Tharp et al. (1992) and Liu et al. (1993) state that 3-D tracking and “pick-and-place” tasks are 

two skills that are often required for tele-manipulation. Reddy (1997) explains that poor FR and 

large delay can degrade human-system interaction, often in terms of impaired depth perception 

on the visual display. Thus, the use of low FRs can have adverse effects on tele-manipulation, 

especially as far as depth perception is concerned. However, there are several moderating factors 

that might impact the adverse effects of low FRs. In this section, we briefly review five of those 

moderators: task dependency, viewing condition dependency, display luminance and the number 

of gray scale levels (GL), auditory cues in addition to visual cues, and end user characteristics. 

1.2.1 Task Dependency 

Johnson and Caird (1996), who investigated the impact of FR on sign language gesture 

recognition, remind readers that the required FR for performance of a task can depend on the 

nature of the task itself. If animation must be conveyed, then considering that the human visual 

systems takes 50 msec to process a frame, 20 Hz may be required (Card, Moran, & Newell, 

1983). However, conveying a basic understanding of a sequence may require fewer frames. 

It has been reported that 10 Hz is the minimum threshold for performance in immersive VEs (see

Bryson, 1993; MacKenzie & Ware, 1993; Watson et al., 1997, 1998). However, higher rates of 

10 to 15 Hz are required for acceptable performance (McKenna & Zeltzer, 1992). For 

architectural walk-through tasks, various minimum FRs have been recommended, including 6 Hz 

(Airey, Rohlf, & Brooks, 1990), 7 Hz (Pausch, 1991), and 10 Hz (Bryson, 1993; Card, 

Robertson, & MacKinlay, 1991; McKenna & Zeltzer, 1992). 

Watson et al. (2003) differentiate between open and closed loop tasks, each of which is affected 

by FR. In a closed loop task, such as tracking, continuous feedback is provided. Thus, the 

result of the previous action feeds into the next action. Continuous feedback is therefore 

required for the operator to execute the next move. Automobile driving is considered to be a 

closed loop tracking task because the driver is required to maintain position of the vehicle within 

the specified lanes and to follow a prescribed pathway. In a tracking task, delay increases the 

time that passes until feedback is received by the user, and as a result, performance can degrade. 

Difficult tracking tasks are further impaired by delays. 

Open loop tasks, on the other hand, have little or no feedback available to the operator. For 

example, placement task performance depends on predictive planning and is not guided by 

adjustments of feedback as are closed loop tracking tasks. However, placement tasks end in a 

closed loop phase where finer adjustments are made to place the object in its final position, 

which is a small target space. 
6 

1.2.2 Viewing Condition Dependency 

Parkhurst and Niebur (2001) demonstrate the human observer’s different needs of visual detail 

for different viewing conditions. In a velocity-based LOD graphics rendering technique, objects 

remain stationary but appear as a blur in the observer’s visual field if he or she turns his or her 

head. Therefore, the blurred object does not need to have a high LOD. Thus, LOD is reduced 

as the object moves across the visual field but then increases again as the observer slows and 

stops his or her viewpoint rotation. In this rendering method, LOD is linearly related to 

rotational velocity of the observer. This method also keeps the system’s computational load 

roughly constant. 

In distance-based LOD manipulation (i.e., real-time viewpoint-dependent simplification), objects 

that are farther away from the viewer do not need to be rendered at high complexity. This 

reduction in detail then allows more resources to be allocated to the generation of higher FRs, as 

per the LOD-FR trade-off. There are other times when the human visual system does not 

naturally process high LOD, such as when objects are in the periphery of the visual field (Virsu 

& Rovamo, 1979) and when rapidly moving objects appear as blurred (Murphy, 1978; Burr & 

Ross, 1982). 

Both pixel size and FR can influence the accuracy of perception of motion in depth. Even 

though the object may be moving at a constant velocity, this velocity appears to accelerate or 

decelerate, depending on whether it is located near or far from the viewer. According to Pfautz 

(2002), the motion of small objects near the line of sight and far from the viewer is likely to be 

limited by pixel size. However, the motion of large objects far from the line of sight and near the 

viewer is likely to be limited by FR. If FR and pixel size are correct, then the viewer can detect 

perspective depth. 

There may also be differential effects for stereoscopic and monoscopic displays (see Arthur et 

al., 1993; Lion, 1993). In monoscopic displays, the image is presented to only one eye; in some 

settings, this can be done to avoid retinal image disparity. In stereoscopic displays, both eyes 

receive an image, but the image displayed to each eye is slightly different because of the position 

of the eyes relative to each other. Lion (1993) found that stereo performance was significantly 

better than mono performance in a manual tracking task. This was confirmed by Richard et al. 

(1996), who demonstrated that tracking task completion time was lower overall for the stereo 

condition. 

There may also be effects for the use of head-coupled imagery on visual performance (see Lion, 

1993). In restricted head coupling, participants rest their chins against a chin rest to control for 

the effects of parallax. This is another viewing condition variable which may be a moderator in 

the relationship between FR and human performance if both are manipulated simultaneously. 
7 

1.2.3 Display Luminance and the Number of GLs 

The number of GLs is a characteristic of the video monitor and is usually measured in bits. 

Whiting, Honig, Carterette, and Eigler (1991) demonstrated a linear relationship between GL and 

video display luminance: in the range of 80 to 180 gl, there is a slope of 0.209 (candela 

[cd]/m2)/GL. Whiting et al. were able to generate a mean luminance of 6.2 cd/m2 (1.8 ft-lumen), 

which corresponds to a GL of 128. GL can also serve as a source of image noise; Whiting et al. 

manipulated pixel noise standard deviations of 5, 10, 14, and 20 GL for static images and 20 GL 

for dynamic noise. Also, image contrast can be defined as the GL increment of the target. Thus, 

GL could be a characteristic of visual display quality that could impact target detection 

performance independently as well as interactively with FR (also see Vitkovitch & Barber, 

1994). 

1.2.4 Auditory Cues in Addition to Visual Cues 

It is also necessary to consider the influence of auditory components of visual presentations. In 

some settings, audition is thought to play a larger role in temporal perception than vision (e.g., 

see Welch, Duttonhurt, & Warren, 1986). For instance, musical tempo can influence the human 

perception of time in passing and display FR (Mastoropoulou & Chalmers, 2004; 

Mastoropoulou, Debattista, Chalmers, & Troscianco, 2005). Speech reading ability, which is 

rooted in target recognition, is significantly more accurate in audio-visual conditions than in an 

audio-only mode (Vitkovitch & Barber, 1994; Frowein et al., 1991). This effect may be a 

moderator that should be distinguished from possible FR manipulation effects. 

Audiovisual skew or asynchrony between the video and the audio aspects of the image sequence 

can also affect recognition. It can be caused by low FRs that present obsolete visual information 

that does not match the continuous real-time delivery of sound. While this mismatch can 

typically impair performance, it can be helpful in some instances of low FR. For example, an 

asynchrony in which audio lags the visual component of the presentation can actually aid 

performance beyond that which can be normally perceived at 30 Hz (Knoche, deMeer, & Kirsh, 

2005). The direction of audio-visual skew can be a moderator worth considering. Therefore, it 

is important to examine the full range of effects generated by an interaction among audition, 

vision, and FR. 

1.2.5 End User Characteristics 

Although many aspects of the system and experimental methods can influence the relationship 

between FR and performance, it is important to consider the individual differences in the humans 

who use these systems. One possible moderator is the level of experience the operator has with 

computers and virtual reality (VR). Those who have been exposed to these systems are more 

familiar with the different viewing and psychomotor effects that can result from temporal 

distortions which would otherwise not be present in the everyday, real-world human-machine 

experience. Many of today’s computing and simulation environments are capable of rendering 
8 

graphics at 30 Hz and higher. Operators of these advanced systems may therefore be 

unaccustomed to the effects of low FR and lag. For instance, Liu et al. (1993) suggest a 

minimum update rate of 2 Hz for experienced users and 10 Hz for inexperienced users of a 

teleoperation tracking task. Adaptation to poor temporal fidelity has also been demonstrated. 

Increasing the operators’ exposure to low temporal fidelity can aid performance, and training is 

one way to accomplish adaptation (see Johnson & Caird, 1996). 

2. Psychomotor Performance 

2.1 Placement Performance 

According to Fitts’ Law, the time required to acquire a target is a function of (a) the physical 

distance to the target and (b) the physical size of the target (Fitts, 1954). The interaction between 

low FR on Fitts’ Law was assessed by Bryson (1993, Experiment 2). This placement task 

involved moving a cursor from an initial position to a final position in a computer system. The 

performance means showed that increased lag and low FR have similarly detrimental effects on 

placement performance. More specifically, lags and FRs greater than 250 ms (< 4 Hz) 

dramatically increased the difficulty level of the task. Furthermore, the effect of great lag and 

low FR was less pronounced in the participant who was experienced with VEs with poor SR. In 

addition, Massimino and Sheridan (1994) suggested that frame rate as low as 5 Hz might be 

viable for placement tasks if force feedback were available. 

In Liu et al. (1993), operators performed pick-and-place tasks while wearing HMDs. They found 

that operators who were experienced with HMDs were able to perform the placement tasks at 

update rates as low as 10 Hz but had significantly more errors below 2 Hz. Those who were 

inexperienced demonstrated impairments once the update rate dropped below 30 Hz, which 

suggests that experience level can moderate the relationship between FR and performance. Liu 

et al. also observed that task completion time was longer at update rates below 10 Hz. 

Meehan, Insko, Whitton, and Brooks (2002) assessed placement performance in VEs; however, 

they also measured the physiological reactions imposed by various FRs. Lower FRs can impair 

performance and feelings of presence. For instance, the 10-Hz condition caused many participants 

to lose a sense of balance, causing anomalous dependent measure scores which consequently 

required readjustment. The change in heart rate was significantly higher in the 10-Hz than in the 

15-Hz condition, indicating increased stress at the lower FR. Reported behavioral presence 

significantly increased as FR increased from 15 to 20 Hz and from 20 to 30 Hz. 

Watson et al. (1997) examined placement performance in the context of variable FRs, using the 

sinusoidal method to calculate standard deviations in frame time. Average placement and grab 

times significantly improved when mean FR increased from 10 Hz to 20 Hz. In a later study, 

Watson et al. (1998) again assessed the effects of FR means and standard deviations on grasping 
9 

and placement tasks. This time, standard deviations were calculated with the frame-latency 

manipulation method and were absolute values of FRs (e.g., 4 Hz). Grasp time and the number 

of grasp attempts were significantly greater at the 9-Hz mean FR and when the standard 

deviation of system responsiveness (SDSR) was 4 Hz. Overall, grasping performance was 

impaired the most when mean FRs were low and SDs were high. Based on these results, Watson 

et al. (1998) speculated that improving the mean FR above 17 Hz may not necessarily increase 

grasping performance; to test this, a second study was conducted with a set of higher FRs. FR 

SDs were based on percentages of FRs (e.g., 5.6% of 17 Hz). It was found that increasing FR 

from 17 to 25 Hz did not significantly improve grasping performance, as hypothesized. 

Improved placement performance occurred at higher mean FRs and lower standard deviations, as 

was also found in Experiment 1. Overall, these results suggest that there may be a grasping 

performance threshold at higher FRs (such as at 17 Hz) and that grasping performance may be 

compromised only at lower mean FRs (such as 9 and 13 Hz). 

Methods of calculating SDs in frame time have also been compared. In a third experiment, 

Watson et al. (1998) tested the hypothesis that SDSR control via absolute values was inferior to 

SDSR control via percentages of mean FR. The SDs were manipulated as absolute values of 

FRs (e.g., 4 Hz). Results showed that there was a significant increase in grasp time only when 

the FR was at the lowest (17 Hz) and SDSR was highest (7.56 Hz). A reduction in the SR range 

occurred at higher FRs, and therefore absolute FR control did not yield many significant effects. 

Thus, Watson et al. suspected that SR control based on absolute FR values may be inferior to SR 

control based on percentages of mean FRs. 

2.1.1 Placement Task Conclusion 

Results from studies that have manipulated a constant FR indicate that 10 Hz and less can be 

detrimental to placement performance in a VE; higher FRs are needed for participant 

performance and comfort. Specifically, the research has indicated that FRs less than 4 Hz seem 

to dramatically increase the difficulty level of the task (Bryson, 1993). Also, participants in VEs 

experience discomfort, balance loss, and increased heart rate at 10 Hz (Meehan et al., 2002). 

However, the variable FR approach may be more accurate when FRs are low, since standard 

deviations and fluctuations of FRs are important considerations (Watson et al., 1997). FR 

thresholds for ideal performance in variable FR configurations are probably similar to constant 

FR thresholds. Watson et al. (1997) found that grasping performance was compromised only at 

lower mean FRs such as the 9 and 13 Hz. For improved placement performance, the average FR 

should increase to at least 17.5 Hz (Watson et al., 1998) or 20 Hz (Watson et al., 1997). 

2.2 Tracking Performance 

Bryson (1993, Experiment 1) assessed tracking performance at various FRs and found that in 

general, normalized error was linearly dependent on frame time. Furthermore, the slope of this 

linear relationship depended on the frequency of the targets moving in a sinusoidal path. Thus, 

longer frame times (i.e., lower FRs) at higher frequencies of target motion produced the greatest 
10 

tracking error. In consideration of these results and those from Experiment 1 (see placement 

performance section), Bryson (1993, Experiment 1) concluded that frame time effects are 

congruent with those of delay in tracking tasks. Cai (2004) found that human figure recognition 

and tracking in a video were found to be a logarithmic function of FR, and a major improvement 

in this performance occurs by increasing FR from 0.05 Hz to 1 Hz. Thus, the minimal 

satisfactory FR was 1 Hz in normal viewing conditions. Performance increases somewhat 

between 1 and 7 Hz and then seems to stabilize from 7 Hz until the maximum tested value of 

17 Hz. 

Ware and Balakrishnan (1994) assessed the effects of low FR as well as lag in a target 

acquisition in VR display. Reaction time reductions were the most dramatic until 5 Hz but 

stabilized at around 10 Hz, beyond which, performance improvements are minimal. Thus, it may 

not be worth the extra cost to increase FRs beyond 10 Hz for this type of task and setting. 

Vehicle control is considered to be a tracking task since the driver must maintain position of the 

vehicle within the lanes following a specific pathway (Watson et al., 2003). In a study of 

teleoperation of unmanned ground vehicles (UGVs), McGovern (1991) did not find driving 

performance degradation when image update rates were lowered from 30 to 7.5 Hz. On the other 

hand, Van Erp and Padmos (2003) reported that, when update rate dropped below 5 Hz in an 

indirect driving task, participants’ lateral control significantly degraded. Day (1999) also 

assessed the effects of low FRs on a remote vehicle driving task. Mean task completion times 

and mean time in error increased as FR decreased, and performance for FRs 1 through 4 Hz was 

significantly lower than for the control condition, 25 Hz. Not surprisingly, post-task 

questionnaires indicated that 50% of participants felt they would have performed tasks 

significantly better with higher quality video. 

Teleoperation-based tracking performance is of particular importance in FR studies, as 

communication problems can arise from bandwidth limitation (Liu et al., 1993). The UGV 

operator faces possible sources of signal degradation in the forms of physical distance from the 

UGV, obstacles, and electronic jamming (French et al., 2003). Successful teleoperation 

therefore relies on tracking performance in terms of navigation as well as target tracking. Liu et 

al. found that, similar to their placement task performance previously discussed, operators who 

were experienced with HMDs were able to perform tracking tasks at update rates as low as 

10 Hz but had significantly more errors below 2 Hz. Inexperienced operators, on the other hand, 

showed a performance degradation almost immediately when FRs started to decrease. French et 

al. found that low FRs (i.e., 2 and 4 Hz) yielded significantly longer navigation times and higher 

cognitive, visual, and subjective workload ratings, but not target identification or situational 

awareness. French et al. concluded that 16 Hz is ideal for UGV teleoperation. However, to 

obtain effective task performance, a minimum of 8 Hz is necessary. 
11 

Display format and viewing characteristics can also interact with FR to impact manual tracking 

performance. Lion (1993) considered the differential effects for stereoscopic and monoscopic 

displays, as well as the use of head-coupled imagery. 

The 33-Hz FR yielded better manual tracking performance than the 22-Hz FR. The cursor was 

also kept closer to the target 21% more of the time in the 33-Hz condition as opposed to the 

22-Hz condition. There was also a significant interaction between stereo displays and FR, with 

better performance in the stereo 33-Hz condition. 

An interaction between viewing condition and FR was found by Richard et al. (1996). Tracking 

time was fastest and stable in the range of 14 Hz to 28 Hz in the mono condition but remained 

stable at FRs as low as 7 Hz in the stereo condition. Stereo vision also continued to improve 

performance much more than that of mono vision when the FR dropped below 7 Hz. After 10 

trials at 1 to 7 Hz in the mono condition, the mean target capture time produced a flat curve, 

suggesting cessation of learning. However, in the stereo condition, the mean capture time was 

lower overall, and the curve appeared mostly flat from the earliest trials. Thus, less learning took 

place at 1 to 7 Hz in the stereo condition. 

Lampton, Knerr, Goldberg, Bliss, Moshell, and Blau (1994) observed that FR degradations affect 

participants’ tracking performance in a VE. Although the FRs were not systematically manipulated, Lampton et al. did find that the slow FRs (i.e., approximately 5 Hz) made the 3-D tracking 

tasks very difficult. It was reported that participants were able to keep the cursor on the moving 

target less than 9% of the time. 

Ellis et al. (1999) examined tracking performance in VEs at various FRs and degrees of latency. 

Decreased FR (e.g., 6 Hz versus 20 Hz) significantly increased root mean square (rms) error, 

increased perceived control, and decreased feelings of stability. Participants’ judged realism was 

not affected by the various FR and latency values, however. 

Arthur et al. (1993) manipulated the effects of stereo versus mono displays as well as the use of 

head-coupled imagery. Error rates in a 3-D tree-tracing task were measured. Response time 

increased along with increased lag and the lower FR of 10 Hz. Regression equations indicated 

that lag likely contributed more to performance effects than did reduction in FR. 

2.2.1 Tracking Task Conclusion 

Overall, higher FRs such as 20 Hz and 33 Hz yielded better manual tracking performance than 

lower FRs such as 6 Hz and below (see Ellis et al., 1999; Lion, 1993). The detrimental effect of 

low FR is especially notable when the target moved at higher frequencies (Bryson, 1993, 

Experiment 1). 
12 

Teleoperation may require higher FRs. French et al. (2003) suggested that 16 Hz is ideal for 

tracking in UGV teleoperation, and that 8 Hz is an absolute minimum requirement. Additionally, 

Day (1999) demonstrated that remote vehicle control was significantly better at 25 Hz than at 

4 Hz. 

Acceptable tracking performance was found to be possible at very low FRs. Rates above 10 Hz 

may not be necessary for some applications; thus, systems with smaller bandwidth capability 

may still be effective. The minimal satisfactory FR was 1 Hz for tracking a moving human 

figure (Cai, 2004) and 2 Hz to 10 Hz for teleoperation for experienced operators (Liu et al., 

1993). Finally, target acquisition in a 3-D environment seems to benefit most when FRs are 

increased to 10 Hz (Ware & Balakrishnan, 1994). 

There may also be a significant interaction between stereo and FR, with better performance in 

stereo at higher FRs. It seems, therefore, that the combination of high FRs and stereo displays 

more closely mimics the real-world visual experience, thereby requiring less user adaptation and 

learning (Richard et al., 1996). This suggests that overall, if lower refresh rates are used, 

stereoscopic displays may compensate to boost operator performance. Based on these results, 

Lion (1993) proposes the importance of giving design priority to the development of systems 

with stereoscopic displays and higher FR. 

A summary of these research findings is presented graphically in figure 1 and is also provided in 

more detail in appendix A. 

Summary of Frame Rate Effects on Psychomotor 

Performance

0

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25

30

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Arthur 93

Bryson 93-2

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McGovern

Massimino &Richard et alRichard et al

van Erp &

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Frame Rate

FR-Normal

FR-Degrade

(Note: Pink squares signify the FR level where human performance starts to significantly degrade. Blue 

diamonds signify the lowest FR levels where participants perform normally.)

Figure 1. Summary of FR effects on psychomotor performance. 
13 

3. Perceptual Performance 

3.1 Target Recognition Performance 

Some researchers examined the effects of slow FR on target recognition performance in the 

military context. For example, French et al. (2003) investigated robotic operators’ target 

identification performance using a UGV. Their simulated degradation of video feed from the 

UGV included 2, 4, 8, and 16 Hz. They found that FRs as slow as 2 Hz did not significantly 

affect their performance, including target identification and situational awareness. 

Chen, Durlach, Sloan, and Bowens (2005) conducted a robotic control study in a simulated 

military environment. They manipulated the FRs (5 versus 30 Hz) of the sensor video feed of 

the simulated unmanned aerial vehicle and UGV. Participants’ tasks included target detection 

and acquisition. Neither performance was significantly degraded as FRs dropped from 30 to 

5 Hz. 

Perception of the visual cues associated with speech and lip reading may also be considered a 

form of target recognition. Visual information can aid interpersonal communication for those 

with impaired hearing by means that coupled the visual cues of speech reading or “lip reading” 

with the limited auditory perception that remains. Sign language interpretation is a pattern 

recognition task which may depend on temporal resolution. FR is thought to impact specific 

aspects of lip reading, including the apparent duration of visual speech components such as 

mouth movements (Massaro, Beskow, Cohen, Fry, & Rodriguez, 1999) and dynamic 

components such as syllable timing (Summerfield, 1979). 

3.1.1 Constant FR Effects of Target Recognition 

Johnson and Caird (1996) found that low FR can impair recognition of American Sign Language 

gestures. Although there was no significant main effect for FR, means indicated a trend for 

impaired performance and increased error rate at lower FRs (e.g., 1 and 5 Hz). However, over 

the course of additional trials, there was an improvement in performance. Training may 

therefore be useful when bandwidth is limited. 

Adding audio cues to visual presentation can aid target recognition. Frowein et al. (1991) 

assessed speech reception target recognition in the domain of video telephony. Audio-visual 

recordings of common sentences were presented in both audio-visual and audio-only modes. 

Participants were asked to repeat each sentence immediately after the presentation. At 5 to 6 Hz, 

performance in the audiovisual condition was significantly better than the audio condition, and at 

15 Hz, the added performance improvement stabilized, with no further performance benefits for 

the 30-Hz condition. Thus, there may be an interaction between presentation mode and FR in 

speech perception. 
14 

Vitkovitch and Barber (1994) hypothesized that the perception of the speaker’s facial movement 

was important to help listeners to perceive speech. In this study, participants listened to two 

simultaneous recordings of a message and shadowed (i.e., repeated) the words of the target 

message. Recordings were in either audio-only or audio-visual format. Having a visual display 

did improve performance over an audio-only display. Even audio-visual video presented at the 

lowest FR (8.3 Hz) yielded improved performance over the audio-only condition; this is 

consistent with Frowein et al. (1991). Across all FRs, performance improved when FR was 

increased. However, there was no significant performance benefit from increasing the FR from 

16.7 Hz to 25 Hz, which suggests that 16.7 Hz may be adequate for video transmission for 

recognition tasks of this nature; this is also consistent with Frowein et al. 

In another study by Vitkovitch and Barber (1996, Experiment 1) participants lip read number 

sequences in the range of 1 through 30 in a visual-only condition. By turning off the sound, 

Vitkovitch and Barber (1996) were able to determine that the detrimental effect of low FR is not 

attributable to audiovisual asynchrony. GL of the image was also manipulated. Performance 

accuracy significantly improved when FRs were increased from 8.3 Hz to 25 and from 8.3 Hz to 

16.7. There was no significant gray scale and FR interaction, which suggests that both may be 

independent (yet additive) sources of visual cues in lip reading ability. In a second experiment, 

Vitkovitch and Barber (1996) sought to assess whether repeated exposures to stimuli of low FR 

and limited gray scales can aid participants’ lip reading ability. Both digital and analog formats 

as well as GL were compared. There was no improvement in accuracy over time for those in the 

low FR (8.3 Hz). This may indicate that the high perceptual demand of the low FR was too 

great, and thus increased experience was not enough to allow participants to compensate for the 

visual degradation. Main effects of both FR and GLs indicate that performance was higher at 

25 Hz than 8.3 Hz as well as 16 GL compared to 8 GL. Results of both experiments show that 

FRs higher than 8.3 Hz are necessary for lip reading with 16.7 Hz being adequate. 

Williams, Rutledge, Garstecki, and Katsaggelos (1997) investigated the effects of FR and the 

recognition of visemes or visual phonemes (Fisher, 1968), which are the visual speech cues such 

as mouth movements and teeth positions that accompany speech sounds. Generally, viseme 

recognition decreased along with decreasing FR. Often, viseme recognition dramatically 

dropped when the FR was reduced from 5 Hz to 2 Hz. 

The visual distortion caused by low FR can result in an asynchrony with the audio components 

of the presentation. Knoche et al. (2005) manipulated both FR and audiovisual skew upon the 

ability of participants to identify the middle consonants of nonsense words. Results showed that 

lower FRs worsen the effects of negative audio skew (in which audio leads visual). Conversely, 

positive skews (in which visual leads audio) can improve consonant comprehension. At FRs 

between 10 and 15 Hz, audio lags between +127 ms and +167 ms can improve comprehension 

beyond that which normally occurs at 30 Hz. This may be because longer frame times allowed 

participants to “close the gap” between audio and visual stimuli. Additionally, the authors 

suspect there is a ±120-ms limit on the ability for humans to integrate audiovisual information 
15 

(any more or less suggests great asynchrony and possible failed integration). Whereas audio and 

video can be perceived in synchronization with each other anywhere between ±120 ms and 

30 Hz, this window changes to -54 ms to +186 ms at 10 Hz. The implications of these results are 

that in a “noisy” environment, video at 10 Hz will be effective if audio lags visual by +120 ms to 

+170 ms. 

FR studies can also apply to dynamic medical displays, such as x-ray fluoroscopy, cardiac 

cineangiography, real-time two-dimensional (2-D) ultrasound, rapid sequence nuclear magnetic 

resonance imaging (MRI), radioisotope ventriculography, and ultrafast computer tomography. 

There is also a degree of “noise” and contrast involved in these displays, which can further 

complicate the detection of low contrast signals. Whiting et al. (1991) examined the effects of 

FR on signal detection in a radiological application. Higher FRs aided signal detection 

performance, specifically as the FR progressed from 0 Hz (static image) to approximately 4 Hz. 

It then improved modestly until the FR increased to 16 Hz, then mildly improved at higher FRs 

thereafter. Although 100 to 200 msec was previously suggested as the maximum persistence of 

visual memory, the results of current study suggest a 1500-msec decay time in this task. 

3.1.2 Variable FR Effects of Target Recognition 

Variable FR configurations have been tested in target recognition. Parkhurst and Niebur (2001) 

employed the velocity-based LOD graphics rendering technique to present target objects in a 

virtual room. FRs were held constant at 6 Hz or were variable so that they were allowed to 

increase with decreasing LOD as the observer turned his or her head to search for targets. Target 

detection accuracy did not change because of LOD changes. Reaction times increased with 

decreasing LOD in the constant FR condition, but in the variable FR condition, reaction times 

decreased when LOD decreased, likely because the extra bandwidth was allocated toward 

generating a higher FR. Overall, there was support for the velocity-based LOD rendering 

technique, since faster rendering times associated with decreased LOD can aid visual search 

performance. 

3.1.3 Target Recognition Performance Conclusion 

Some researchers examined the effects of slow FR on target recognition performance in the 

military context. For example, French et al. (2003) investigated robotic operators’ target 

identification performance and found that FRs as slow as 2 Hz did not significantly affect their 

performance (as compared to when FRs were 4, 8, and 16 Hz). Similarly Chen et al. (2005) did 

not observe significant target detection performance degradation as FRs dropped from 30 to 

5 Hz. 

Speech reading is one form of target recognition. Frowein et al. (1991) concluded that FR is an 

important contributor to speech reading perception and that FRs until 15 Hz can improve this 

performance. Comparably, Vitkovitch and Barber (1994, 1996) concluded that 16.7 Hz may be 
16 

adequate, and lower rates, such as 8.3 Hz to 12.5 Hz, may result in a great loss of dynamic visual 

information and audio-visual mismatch, thereby causing major performance decrements. 

Conversely, Williams et al. (1997) considered the low rate of 5 Hz to be the minimum threshold 

for continuous speech reading. Another important aspect of speech reading is the potential for 

audio accompaniment, which can be skewed at lower visual FRs. For instance, at 10 Hz, the 

audio presentation should lag the visual presentation by at least +40 ms (Knoche et al., 2005). 

Observers may be able to adapt to low FRs, however. If there is enough opportunity to learn 

sign language gestures, low multimedia rates of 1 and 5 Hz may be adequate (Johnson & Caird, 

1996). 

Continuous FR presentation in a purely visual signal detection task demonstrated an apparent 

16-Hz threshold for adequate performance. Increasing FR beyond this level improved 

performance only mildly (Whiting et al., 1991). 

Another approach to the target detection environment is the use of a variable FR system. The 

velocity-based LOD rendering technique is one such approach to determining FR. It can yield 

faster graphics rendering times when high LOD is not necessary, and this in turn can improve 

visual search performance (Parkhurst & Niebur, 2001). 

3.2 Perception and Psychophsics 

The effects of slow FRs on human perception have been examined in a wide variety of 

environments. For example, in a study conducted in a VE, Piantanida, Boman, and Gille (as 

cited in Reddy, 1997) found that participants’ depth and egomotion perception degraded when 

FRs dropped. On the other hand, Van Erp and Padmos (2003) assessed the effects of slow 

update rates on the viewing system for indirect driving and observed that an update rate as low as 

3 Hz did not appear to affect participants’ speed perception. 

Augmented reality (AR), in which computer graphics are overlaid onto the physical environment 

through transparent HMDs, has also been used to study the effects of slow FRs. Effective AR 

depends, in part, on the mechanisms of human visual perception, such as depth cues and motion 

detection. Lai and Duh (2004) assessed the role of different FRs on the perception of 

visualization dynamic information via the change in bar graphs. (The bar graphs were presented 

in an HMD.) Users can visualize changes in dynamic information displays by tracking the 

motion of the stimulus (e.g., vertical changes bar graph height). Users can also anticipate the 

future motion of the stimulus change as a function of the implied velocity of the stimulus (i.e., 

representational momentum; see Freyd & Finke, 1985). Thus, the display’s ability to convey 

motion can impact the perception of dynamic information representation. Participants judged the 

percentage change in a dynamic 3-D bar chart (e.g., the rate at which the height of a bar graph 

was increasing). Interestingly, the greatest judgment inaccuracies were made at the fastest FR, 

160 Hz. It was found that participants overestimated the percentage at lower speeds and 

underestimated at higher speeds. This may be because in the slower speeds, participants use 
17 

cognitive resistance (see Finke & Shyi, 1988) in later stages of the presentation to reduce the 

degree of representational momentum. It is also important to consider the typical human 

cognitive processing speed of 170 msec (Card et al., 1983) since changes that occur below this 

threshold may not be accurately perceived. This may explain the performance improvements for 

the longer frame times (i.e., slower FRs). 

Mastoropoulou and Chalmers (2004) hypothesized that music could be used as a distractor to 

affect the user’s perception of time enough to de-emphasize slower rendering times. Participants 

with computer graphics experience were tested. Animated clips were compared at different FRs, 

and each compared pair had a difference of 4 Hz (16 versus 20 Hz or 12 versus 16 Hz). The two 

types of music that accompanied the animations were “slow tempo and relaxing” and “fast tempo 

and exciting”. Frequency analyses showed that slow tempo music decreased the perceived scene 

velocity. Contrary to the hypothesis, playing fast tempo music did not convince observers that 

the clip was shorter and progressed at a higher temporal rate. The lack of support for the 

hypothesis could be because a difference of 4 Hz was not enough for participants to perceive a 

velocity difference when the two different FRs were compared. 

Pfautz (2002, Experiment E) was interested in the impact of spatio-temporal sampling on the 

perception of constant velocity motion. There was an interaction between FR and stimulus 

velocity, so that higher velocities at higher FRs (e.g., 15 and 60 Hz versus 5 and 7.5 Hz) yielded 

more accurate response distances. In a second related experiment, Pfautz (2002, Experiment F) 

assessed the effects of viewpoint manipulation in an air traffic control collision task. The task 

involved making a time-to-contact judgment for two moving aircraft on a screen. The higher 

FR, 20 Hz, provided greater judgment accuracy than 7.5 Hz. Allowing participants to alter their 

viewpoint impaired this accuracy, however. 

Reddy (1997, Experiment 1) assessed performance in a virtual heading task while manipulating 

FR at either 2.3 Hz (considered to be excessively low) or 11.5 Hz (considered to be moderately 

acceptable). In the heading task, the subject was passively navigated through the VE with his or 

her direction of fixation oriented differently from the direction of movement, and the task was to 

determine whether he or she was moving toward the left or right of the fixation point. The 

higher FR of 11.5 Hz had clear performance benefits in terms of accuracy and task completion 

time. The same task was again executed in a second experiment (see Reddy, 1997, Experiment 

2). Higher FRs were manipulated in this experiment, this time with 6.7 Hz and 14.2 Hz. As in 

the first experiment, similar trends were found, so that accuracy and reaction time were better in 

the higher FR condition. More precise angle discriminations were possible at this higher FR. 

3.2.1 Perception and Psychophsics Conclusion 

Van Erp and Padmos (2003) assessed the effects of slow update rates of the viewing system for 

indirect driving and observed that an update rate as low as 3 Hz did not appear to affect 

participants’ speed perception. Piantanida, Boman, and Gille (as cited in Reddy, 1997), on the 
18 

other hand, found that participants’ depth and egomotion perception degraded when FRs 

dropped. 

The perception of constant velocity motion seems to be best served by higher FRs such as 15, 20, 

and 60 Hz (Pfautz, 2002, Experiments E and F). However, there is an upper limit to the ideal 

FR. Excessively rapid FRs (e.g., 160 Hz) can impair the apparent rate of change in dynamic 

informational displays (Lai & Duh, 2004). On the other hand, differences of 4 Hz at modest FRs 

(e.g., in the range of 12 to 20 Hz) may be undetected by viewers, even if they are experienced 

with computer graphics (Mastoropoulou & Chalmers, 2004). 

In heading performance, there is a strong performance benefit when the FR increases to 10 to 

15 Hz; however, performance improvements taper off afterwards at higher rates. Thus, it seems 

that 15 Hz might be considered the minimum threshold for VEs. FRs below 10 Hz will yield 

sharp performance degradations, in terms of both response time and heading accuracy. Heading 

tasks have many parallels to other VE applications, such as driving and flight simulators, and so 

the results can extend to these domains, as well (Reddy, 1997). 

A summary of these research findings is presented graphically in figure 2 and is also provided in 

more detail in appendix B. 

Summary of Frame Rate Effects on Perceptual 

Performance

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Chen, Durlach

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Figure 2. Summary of FR effects on perceptual performance. 
19 

4. Behavioral Effects 

Eye movements are considered important in our understanding of visual perception, attention, 

and cognitive processes. The eye will focus on particularly informative areas of a display (Peiz, 

Canosa, & Babcock, 2000); thus, poor visual quality may fail to attract eye fixation. Quality of 

Service (QoS) refers to the goodness or degree to which the multimedia presentation is 

considered tolerable in terms of viewing experience and is partially determined by FR, which, in 

turn, is attributable to bandwidth limitation implications. 

Gulliver and Ghinea (2004a) investigated changes in eye movements as influenced by low FRs. 

It was hypothesized that jerkier and disjointed video presentations from the low FRs would be 

more perceptually intolerable and annoying, thereby causing more variability in eye paths. 

Interestingly, no correlation was found between FR and eye path movements. Thus, Gulliver 

and Ghinea (2004a) suggest that lower FRs (e.g., 5 Hz) do not influence the flow of 

informational assimilation. 

Individuals are able to conduct video-mediated conversations with the use of hand motions at 

FRs as low as 1 Hz (Chen, 2002) and one frame change every 5 seconds, although subjective 

measures indicated that participants thought this extremely low FR was ineffective (Chen, 2003). 

Thus, despite noticeably low temporal quality, these types of visual cues can retain their 

effectiveness. 

Extremely slow FRs and their associated visual lag may cause cue conflict (i.e., discrepancy 

between visual and vestibular systems), which has been shown to induce cyber/simulator 

sickness (Kolasinski, 1995; Stanney, Mourant, & Kennedy, 1998). 

5. Subjective Assessment 

Varying FRs may influence the subjective ratings of video quality and viewing enjoyment. This 

may be of importance to service providers who need to know the minimum level of quality that 

their customers find acceptable, as well as viewers who need to be able to recognize the subject 

matter and observe smoother movements (McCarthy, Sasse, & Miras, 2004). 

QoS involves spatial (intraframe) characteristics (e.g., picture resolution, color depth), temporal 

(interframe) characteristics (e.g., FR), as well as a spatiotemporal integration (e.g., as auditory 

effects that are in synchrony with the visual cues) (Apteker, Fisher, Kisimov, & Neishlos, 1995). 

It is related to the image quality or FR trade-off in bandwidth allocation, in which FR can be 

reduced in order to improve the spatial aspects of the video. 
20 

“Watchability” is a characteristic of video which includes the viewer’s acceptance of the video’s 

audio signals, the continuity of visual messages, lip movement-speech synchronization, and the 

relationship between the audio and visual message components (Apteker et al., 1995). Lowering 

FRs has been shown to reduce the watchability of video clips, so that 15 Hz might be just 

acceptable, 10 Hz is much less acceptable, and 5 Hz is very unacceptable (Apteker et al.). High 

action videos (e.g., sports clips) on a desktop display with a resolution of 352 x 288 pixels have 

yielded similar satisfaction ratings across the FRs of 25, 15, and 5 Hz (Ghinea & Thomas, 1998) 

and have been considered acceptable 80% of the time when FRs were only 6 Hz (McCarthy et 

al., 2004). When videos were viewed on a palmtop display (sized 176 x 144), low FR was found 

to be less acceptable than on a desktop display, so that the critical lowest acceptable FR value 

was 12 Hz, and 6 Hz was considered acceptable only 50% of the time. 

Gulliver and Ghinea (2004b, 2004c, 2004d) found that degradation of perceived video quality 

and satisfaction was not noticeable when FR was reduced from 25 Hz to 15 Hz, but it was 

noticeable when the FR was reduced to 5 Hz. Thus, presentations made at 15 Hz and 25 Hz 

appear perceptually similar to the participants. An FR reduction from 30 to 1 frame changes 

every 5 seconds had minimal effect on engagement and enjoyment in a video-mediated 

conversation (Chen, 2003). Other studies have found that reductions in FR (i.e., from 25 to 15, 

and then to 5 Hz) often do not impair viewing enjoyment; however, there is a reduction in 

perceived quality (Gulliver, Serif, & Ghinea, 2004). 

The relationship between FR and perceived quality may, however, be context dependent. Masry 

and Hemami (2001) found that perceived quality was higher for lower FRs (such as 10 and 

15 Hz) in higher action sequences, but it was found unacceptable in clips involving less motion; 

this indicates a possible preference specific to motion types. In a similar vein, video clip subject 

matter may result in different levels of perceptual quality and user satisfaction, independent of 

FR (Gulliver & Ghinea (2004b). For example, across all FRs (5, 15, and 25 Hz), popular music 

videos had higher subjective quality and satisfaction ratings than a chorus video. 

Quality of perception (QoP) is the perceptual experience of the user, including the enjoyment of 

watching the video, as well as the ability to analyze, synthesize, and assimilate information 

presented (see Ghinea & Thomas, 1998; Ghinea & Chen, 2003; Gulliver & Ghinea, 2004a, 

2004b, 2004c, 2004d). Thus, QoP involves the viewer’s information processing. Multimedia 

can often be greatly degraded before perception, information assimilation, and learning are 

impaired. Ghinea and Thomas (2000) demonstrated that viewers could integrate visual details to 

learn and then correctly answer questions about the content of videos, even as FR was reduced 

from 25 to 5 Hz. Often, lower FRs (5 Hz) resulted in more correct answers about what had been 

viewed, possibly because there was more time to view frames before they changed (at 25 Hz, 

each frame is visible for 40 ms, but at 5 Hz, a frame is visible for 200 ms). The robustness of 

information assimilation despite low FR has been documented in other studies (see Ghinea & 

Thomas, 1998; Gulliver & Ghinea, 2000; Ghinea & Chen, 2003; Gulliver & Ghinea, 2004a, 

2004b, 2004c, 2004d; Gulliver, Serif et al., 2004). 
21 

According to Ghinea and Chen (2003), cognitive style, such as field dependence (i.e., degree to 

which a person’s perception of information is influenced by the contextual field) and field 

independence, were not moderators in the relationship between FR and QoP. Furthermore, eye 

path movement, which is associated with attentional and cognitive processes, did not differ 

across FRs of 5, 15, or 25 Hz (Gulliver & Ghinea, 2000d). 

Van Breda, Jansen, and Veltman (2005) reported that UAV operators assessed their effort in 

viewing the simulated sensor feed as higher when the frame rate for the camera image was low 

(i.e., 3 Hz) compared to normal frame rates. Wilson and Sasse (2000) have shown that low FRs 

can cause viewers physiological strain, despite the fact that most of them did not report noticing 

a difference between videos presented at 5 and 25 Hz. Exposure to the 5-Hz condition resulted 

in greater experiences of stress, characterized by increased galvanic skin response, increased 

heart rate, and decreased blood volume pulse. The results of this study suggest that it may not be 

sufficient to measure subject reactions alone, since physiological effects can also occur. This 

partially corroborates the findings of Meehan et al. (2002), in which 10 Hz caused large 

increases in heart rate compared to higher FRs. 

A summary of these research findings is presented graphically in figure 3 and is also provided in 

more detail in appendix C. Figures 1 through 3 are summarized graphically in figure 4. 

Summary of Frame Rate Effects on Subjective 

Assessment

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Apeteker

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French et

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Wilson &Wilson &

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Figure 3. Summary of FR effects on subjective assessment. 
22 

Effects of Slow Frame Rate

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10

15

20

25

30

35

0 10 20 30 40 50 60

Study

Frame Rate

FR-Normal

FR-Degrade

Perceptual Psychomotor Subjective

Figure 4. Summary of effects of slow FR (figures 1 through 3). (Note: The x-axis denotes the 

number that the study was designated. The list of studies with their corresponding numbers 

is provided in appendices A through C. Pink squares signify the FR level where human 

performance starts to significantly degrade. Blue diamonds signify the lowest FR levels 

where participants perform normally.) 

6. Conclusions 

Robotic systems of various sizes and capabilities will play an integral role in the U.S. Army’s 

FCS program (Barnes, Cosenzo, Mitchell, & Chen, 2005). According to Mait and Grossman 

(2002), 

...although the operational concept for FCS requires UGVs to sense the 

battlefield and react on their own with minimal human interaction, current 

technology can best be described as remote controlled or teleoperated. 

Semiautonomous operation, suitable for sensing and indirect fire functions, will 

not be available until 2010, and fully autonomous systems (necessary for direct 

fire, battle damage assessment, and reconnaissance, surveillance, targeting, and 

acquisitions) will not be available until 2015 or later. (http://www.ndu.edu/ 

inss/DefHor/DH13/DH13.htm) 

Effectiveness of employing these robotic assets, especially if teleoperation will be involved, will 

in large part be determined by the quality of the video feeds of the remote environment, which 

will be the main source of information for the robotic operator to perform his or her tasks (e.g., 

target detection, tele-manipulation). Since bandwidth constraints may be an issue in the future 

battlefield (Mait & Grossman, 2002) and high FR streaming video may not be available at all 
23 

times, it is important to examine human performance issues that may be associated with low 

FRs. 

In this report, we reviewed more than 50 studies and summarized them in the areas of 

psychomotor performance, perceptual performance, behavioral effects, and subjective 

perception. Generally, psychomotor performance improves at higher FRs and lower standard 

deviations of FR. In placement tasks, 4 Hz may be too low for VE performance, and 10 Hz may 

disrupt human balance. Experimental results have suggested a minimum threshold of 17.5 Hz 

for successful placement performance (Watson et al., 1997). Tracing performance may also 

require more than 10 Hz. 

For teleoperation, higher FRs such as 16 Hz are suggested to aid in navigation and target 

tracking. A rate of approximately 10 Hz may suffice for HMD-facilitated tracking. This lower 

required FR will be useful for releasing bandwidth for other uses, such as rendering more 

graphically detailed images. 

Speech reading is an often-studied form of target recognition. Generally, 13 Hz may be too low 

for speech reading from video transmission; rather, at least 15 Hz may be necessary. However, 

with appropriate learning opportunity, rates around 5 Hz (and possibly less) may be sufficient. 

As with video speech reading, target detection in a visual radiological task may be significantly 

more successful at 16 Hz. Perceptual VE task performance seems to be best served by FRs 

above 15 Hz. This includes perceiving motion of a constant velocity and heading performance. 

Individuals seem to be able to gather content-based information about videos that are viewed at 

low FRs such as 5 Hz. While this FR is very low, it may benefit information assimilation 

because each frame remains on the screen for a relatively longer duration compared to frames 

that are presented at higher rates. This provides viewers with more time to observe each frame. 

Eye movement studies support these findings; the lack of effect for FR upon eye movements 

indicates that there are not significant changes in attentional and cognitive processes. 

In terms of watchability and satisfaction, FRs of 5 Hz can appear “unacceptable” and of lower 

visual quality. Still, they are often considered to be enjoyable to watch despite the temporal 

distortion. However, FR reductions from 25 to 15 Hz are often perceptually similar in 

appearance to viewers. 

Also, FRs at 10 Hz and below have been shown to cause stress in terms of physiological 

reactions in addition to general performance decrements. 

Overall, there seems to be strong support for a threshold of around 15 Hz for many tasks, 

including those that are psychomotor and perceptual in nature. Only Lion (1993) and Watson et 

al. (1998, Experiment 2) (of the 56 studies reviewed) showed significant performance 

degradation associated with FRs higher than 15 Hz. Less impressive yet acceptable performance 

may be accomplished at around 10 Hz for many tasks. However, it is important to consider that 

individuals may be more susceptible to stress symptoms at FRs at and below 10 Hz. Information 
24 

assimilation seems to be far more impervious to the detrimental effects of FR, since participants 

can observe and retain much information from clips presented at rates as low as 5 Hz. Subjective 

reactions to quality and watchability of videos seem to support rates of 5 Hz, although videos 

presented at 15 Hz and above are generally more widely preferred. 

These generalizations regarding superior and acceptable FRs may also be subject to the effects of 

several moderators. The majority of the studies reviewed have involved other independent 

variables and equipment characteristics that could be contributing to or detracting from the 

proposed effects of various FRs. 

The use of variable FR manipulation has been recommended over constant FRs because of its 

proposed accuracy advantage (Watson et al., 1997). There are many different ways to determine 

the standard deviations in laboratories; however, some techniques may be more accurate in terms 

of how FR truly varies in real-world systems (e.g., standard deviations based on percentages of 

mean FRs). 

Stereoscopic displays will likely enable a performance advantage over monoscopic displays, and 

when possible, they should be used to assist operators in compensating for lower FR 

presentations. If displays are stereoscopic, FRs as low as 7 Hz may be adequate, but monoscopic 

displays may only be useful for FRs as low as 14 Hz (Richard et al., 1996). 

User experience may also be an important moderator. Individuals with HMD use experience 

were able to tolerate FRs as low as 10 Hz in tracking, whereas inexperienced participants needed 

30 Hz (Liu et al., 1993). This difference in tolerable FR is quite large, and so it is clear that 

demographics should be measured and controlled when temporal distortion is manipulated. 
25 

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Appendix A. Summary of FR Effects on Psychomotor Performance 

Study 

No. 

Author(s) 

and Date 

FR Manipulation Task Type Measures Findings 

1 Arthur et al. 

(1993) 

10, 15, 30 Hz 3-D treetracing Accuracy 

Speed 

Highest response time at lowest FR (10 Hz 

condition). 

2 Bryson (1993, 

Experiment 1) 

2, 3, 4, 6, 10, 20, 

30, 60 Hz 

Tracking Accuracy Longer frame times (i.e., lower FRs) at higher 

frequencies of target motion produced the 

greatest tracking error. 

2 Bryson (1993, 

Experiment 2) 

2, 3, 4, 6, 10, 20, 

30, 60 Hz 

Placement Accuracy 

Speed 

Performance worsened by increased lag and 

lower FR, especially frame times longer than 

0.25 sec. Experienced participants less 

impaired by low FR. 

3 Cai (2004) Range from 0.5, 1, 

to 17 Hz 

Tracking a 

moving human 

figure 

Accuracy Minimal satisfactory FR was 1 Hz for this 

type of task in normal viewing conditions. 

4 Day (1999) 1, 2, 3, 4, and 25 Hz Tracking Accuracy 

Speed 

25 Hz is ideal; overall performance is worse 

for FRs of 1 to 4 Hz. 

5 Ellis et al. 

(1999) 

6, 12, and 20 Hz Tracking Accuracy 

Perceived 

control & 

stability 

Decreased FR significantly increased rms 

error, increased adapted Cooper-Harper scale 

scores, and decreased stability. 

6 French et al. 

(2003) 

2, 4, 8, and 16 Hz Tracking Accuracy 

Speed 

16 Hz is ideal for UGV teleoperation. To get 

effective task performance, at least 8 Hz 

should be used. 

7 Lampton et al. 

(1994) 

5 Hz 3-D Tracking Accuracy Participants could only keep the cursor on the 

moving target less than 9% of the time. 

8 Lion (1993) 22 and 33 Hz Tracking Accuracy 33 Hz FR yielded better performance than 22 

Hz FR. 

9 Liu et al. (1993) 0.1, 0.25, 0.5, 1, 

1.5, 2, 3, 5, 10 & 30 

Hz 

Trackingexperienced 

participants 

Accuracy 

Speed 

Suggest a minimum update rate of 2 Hz for 

experienced VE users. 

10 Liu et al. (1993) 0.1, 0.25, 0.5, 1, 

1.5, 2, 3, 5, 10 & 30 

Hz 

Trackinginexperienced 

participants 

Accuracy 

Speed 

Suggest a minimum update rate of 10 Hz for 

inexperienced users. 

11 Liu et al. (1993) 0.25, 1, 1.5, 2, 3, 10

& 30 Hz 

Placement Accuracy 

Speed 

Suggest a minimum update rate of 2 Hz for 

experienced VE users and 10 Hz for 

inexperienced users. 

12 McGovern 

(1991) 

7.5, 30 Hz Tracking Vehicle 

Control 

Low FR did not significantly affect driving 

performance on a cone-marked route. 

13 Massimino & 

Sheridan (1994) 

3, 5, 30 Hz Placement Accuracy 

Speed 

Task completion time at 3 Hz was 

significantly slower than 5 and 30 Hz. While 

FR of 30 Hz is best, reduced FRs are viable, 

especially if force feedback is provided. 

14 Richard et al. 

(1996) 

1, 2, 3, 7, 14, 28 Hz Tracking & 

Grasping - 

Mono 

condition 

Accuracy 

Speed 

Within the mono condition, completion time 

was fastest and stable from 28 Hz down to 14 

Hz. 

15 Richard et al. 

(1996) 

1, 2, 3, 7, 14, 28 Hz Tracking & 

Grasping - 

Stereo 

condition 

Accuracy 

Speed 

Within the stereo condition, it was fastest and 

remained stable from 28 Hz down to 7 Hz. 

16 Van Erp & 

Padmos (2003) 

3, 5, 10, 30 Hz Tracking Vehicle 

Lateral 

Control 

Lateral control of vehicle movement was 

degraded when FR dropped below 5 Hz. 

17 Ware & 

Balakrishnan 

(1994) 

0.666, 1, 2, 3, 5, 10, 

15, 60 Hz 

Target 

acquisition in 

a 3-D 

environment 

Speed 10 Hz is approximately the lowest threshold 

for adequate target acquisition performance. 
32 

18 Watson et al. 

(1997) 

10 and 20 Hz Placement Speed 

Accuracy 

Performance significantly improves when 

average FR increases to 20 Hz. Average 

number of grab attempts and percentage of 

correct attempts were significantly lower at 20 

Hz. 

19 Watson et al. 

(1998, 

Experiment 1) 

9, 13, and 17 Hz Placement 

Grasping 

Speed 

Accuracy 

Grasping performance may be compromised 

only at lower mean system responsiveness 

(MSR) FRs (such as 9 and 13 Hz MSRs. A 

2Hz SDSR may be the lowest threshold at 

which grasp time performance is affected. 

Lower standard deviations (e.g., 0.5 Hz) may 

not impact grasping time. 

20 Watson et al. 

(1998, 

Experiment 2) 

17, 25, and 33 Hz Placement 

Grasping 

Speed 

Accuracy 

Better placement performance at higher MSRs 

and lower SDSRs. There may be a grasping 

performance threshold at 17 Hz. 

21 Watson et al. 

(1998, 

Experiment 3) 

mean FRs 17, 33, 

and 41 Hz, each 

with SDs of 0.50, 

3.78, and 7.56 Hz 

Placement 

Grasping 

Speed 

Accuracy 

Increase in grasp time only when the FR was 

at the lowest (17 Hz) and SDSR was highest 

(7.56 Hz). Placement time was longer when 

FR was 17 Hz. 
33 

Appendix B. Summary of FR Effects on Perceptual Performance 

Study 

No. 

Author(s) 

and Date 

FR Manipulation Task Type Measures Findings 

22 Chen et al. 

(2005) 

5 and 30 Hz Target 

detection 

Accuracy No differences between the FRs. 

23 French et al. 

(2003) 

2, 4, 8, and 16 Hz Target 

identification 

Accuracy No differences among the FRs. 

24 Frowein et al. 

(1991) 

5, 6, 7.5, 10, 15, and 

30 Hz 

Target 

recognition 

& Info 

processing 

Verbal 

information 

recall 

FRs up to 15 Hz can improve speech reading 

perception. FRs higher than 15 Hz do not 

further improve performance. 

25 Ghinea & 

Thomas (2000) 

5, 15, 25 Hz Information 

processing 

Information 

assimilation 

Information assimilation can be successful at 

5 Hz, and this low FR may provide the viewer 

with more time to learn the content of the 

frame. 

26 Gulliver & 

Ghinea (2004a) 

5, 15, and 25 Hz Information 

processing 

Eye path 

movement 

No correlation was found between FR and eye 

path movements. In this setting, 5 Hz was 

equally effective as 25 Hz. 

27 Gulliver & 

Ghinea (2004, b, 

c, & d) 

5, 15, and 25 Hz Information 

processing 

Information 

assimilation 

Eye path 

movement 

Low FR of 5 Hz has no effect on information 

assimilation. Eye path movement, which is 

associated with attentional and cognitive 

processes, did not differ across FRs of 5, 15, 

or 25 Hz. 

28 Gulliver, Serif, 

& Ghinea, 

(2004) 

5, 15, 25 Hz Information 

processing 

Information 

assimilation 

Low FR of 5 Hz has no effect on information 

assimilation. 

29 Johnson & 

Caird (1996) 

1, 5, 15, or 30 Hz Target 

recognition 

Information 

processing 

Learning 1 and 5 Hz may be adequate for learning these 

types of gestures in multimedia, if there is 

enough learning opportunity. 

30 Knoche et al. 

(2005) 

10, 15, 30 Hz Target 

recognition 

Accuracy In a “noisy” environment, video at 10 Hz will 

be effective if audio lags visual by +120 ms to 

+170 ms. If the audio lags by more than 170 

ms, a full FR of 30 Hz should be reduced to 

10 Hz.

31 Lai & Duh 

(2004) 

10, 40, 80, 120, 160 

Hz. 

Judgment of 

visual 

percentage 

change 

Accuracy Greatest inaccuracies were made at the fastest 

FR, 160 Hz (excessively rapid). In AR, 

participants underestimated the percentage 

increase, except for in the 10-Hz condition. 

32 Mastoropoulou 

& Chalmers 

(2004) 

16 vs. 20 Hz 

or 

12 vs. 16 Hz 

Viewing 

animated 

clips 

Temporal 

perception 

A difference of 4 Hz was not enough for 

participants with computer experience to 

perceive a velocity difference between the two 

FRs (12 vs. 16 Hz and 16 vs. 20 Hz). 

 Parkhurst & 

Niebur (2001) 

Constant at 6 Hz, or 

varied (median FRs 

ranged from 9 to 

31.5 Hz) 

Target 

recognition 

Accuracy 

Reaction time 

FRs and frame 

rendering 

times 

(computer 

performance) 

Reaction times increased with decreasing 

LOD in the constant FR condition, but in the 

variable FR condition, reaction times 

decreased when LOD decreased. 

33 Pfautz (2002, 

Experiment E) 

5, 7.5, 15, 60 Hz Time-tocontact 

judgment 

Accuracy No significant main effect for FR. Interaction 

between FR and velocity; higher velocities at 

higher FRs yielded more accurate response 

distances. 

34 Pfautz (2002, 

Experiment F) 

7.5 Hz vs. 20 Hz Time-tocontact 

judgment 

Accuracy 20 Hz FR provided greater judgment 

accuracy. 
34 

35 Reddy (1997, 

Experiment 1) 

2.3 Hz and 11.5 Hz Directional 

(orientation) 

judgment 

Accuracy 

Reaction time 

in heading 

task 

11.5 Hz had significantly better performance 

than 2.3 Hz condition. 

36 Reddy (1997, 

Experiment 2) 

6.7 Hz and 14.2 Hz Directional 

(orientation) 

judgment 

Accuracy 

Reaction time 

in heading 

task 

15 Hz might be considered the minimum for 

VEs, and higher FRs will continue to show 

better performance, but at a reduced rate. FRs 

below 10 Hz will yield sharp performance 

degradations, in terms of both response time 

and heading accuracy. 

37 Van Erp & 

Padmos (2003) 

3, 5, 10, 30 Hz PerceptionSpeed & 

Distance 

Estimation 

Accuracy No effects were observed. 

38 Vitkovitch & 

Barber (1994) 

12.5, 16.7, 25 Hz Target 

recognitionlip reading 

Accuracy Performance improved when FR was 

increased. 16.7 Hz may be adequate for 

recognition tasks of this nature. 

38 Vitkovitch & 

Barber (1996, 

Experiment 1) 

8.3, 12.5, 16.7, 25 

Hz 

Target 

recognitionlip reading 

Accuracy Accuracy significantly improved from 53% to 

69% correct when FRs were increased from 

8.3 Hz to 25 Hz. The change from 8.3 Hz to 

16.7 Hz was also significant (52 % to 61% 

accuracy). 

39 Vitkovitch & 

Barber (1996, 

Experiment 2) 

8.3, 12.5, and 25 Hz Target 

recognitionlip reading 

Accuracy FRs higher than 8.3 Hz are necessary for lip 

reading, with 16.7 Hz being adequate. 

40 Whiting et al. 

(1991) 

0, 2, 4, 8, 16, and 32 

Hz 

Target 

detection 

Accuracy Correct detection decreased as FR decreased. 

16 Hz may be the lowest acceptable FR. 

41 Williams et al. 

(1997) 

2, 5, 10, 15, and 30 

Hz 

Target 

recognitionspeech 

reading 

Accuracy 5 Hz is considered to be the minimum 

requirement for continuous speech reading 

presentation. 
35 

Appendix C. Summary of FR Effects on Subjective Assessment 

Note: FR values in Red signify the FR levels where human performance starts to significantly 

degrade. FR values in Blue signify the lowest FR levels where participants perform normally. 

Study 

No. 

Author(s) 

and Date 

FR Manipulation Task Type Measures Findings 

42 Apeteker et al. 

(1995) 

5, 10, 15 Hz Viewing video 

clips 

Watchability 

QoS 

15 Hz considered “just acceptable” for 

watchability. 

43 Chen (2003) 0.2 & 15 Hz, , 

variable (motionsensitive) 

Conversational 

behavior 

Perceived 

engagement/ 

enjoyment 

FR of 1 new image per 5 seconds is 

considered acceptable for engagement and 

enjoyment in video-mediated conversation, 

but “ineffective” for perceiving hand 

movements; 15 Hz considered to be useful. 

44 French et al. 

(2003) 

2, 4, 8, and 16 Hz Teleoperating 

ground robots 

Perceived 

workload 

FR of 2 Hz is associated with significantly 

greater workload 

45 Ghinea & Chen 

(2003) 

5, 15, 25 Hz Information 

assimilation 

QoP Information assimilation and enjoyment can 

occur for films presented at 5 Hz. 

46 Ghinea & 

Thomas (1998) 

5, 15, 25 Hz Information 

assimilation 

QoP 5 Hz can impair satisfaction; 5 Hz may be 

acceptable in terms of watchability for high 

action and low resolution video. 

47 Gulliver & 

Ghinea (2004, b, 

c, & d) 

5, 15, and 25 Hz Information 

assimilation 

QoP Low FR of 5 Hz has no effect on information 

assimilation. Level of enjoyment and level of 

quality are impaired when reducing FR from 

15 to 5 Hz. Thus, 15 Hz may be the critical 

value for QoP. 

48 Gulliver, Serif, 

& Ghinea, 

(2004) 

5, 15, 25 Hz Information 

assimilation 

QoP Low FR of 5 Hz has no effect on enjoyment 

49 Masry & 

Hemami 

(2001) 

10, 30 Hz Viewing 

motion clips 

Perceived 

quality 

(lower 

motion clips) 

Perceived quality can be content dependent. 

10 Hz is acceptable for higher action 

sequences, but not lower motion clips. 

50 Masry & 

Hemami 

(2001) 

10, 30 Hz Viewing 

motion clips 

Perceived 

quality 

(higher 

action 

sequences) 

Perceived quality can be content dependent. 

10 Hz is acceptable for higher action 

sequences, but not lower motion clips. 

51 McCarthy et al. 

(2004, 

Experiment 1) 

6, 10, 12, 15, 18, 

20, 24 Hz 

Viewing video 

on desktop 

display 

Visual 

acceptability 

(subjective) 

Proportion of 

eye 

movements 

At 6 Hz, desktop quality was acceptable 80% 

of the time. 

52 McCarthy et al. 

(2004, 

Experiment 2) 

6, 10, 12, 15, 18, 

20, 24 Hz 

Viewing video 

on palmtop 

display 

Visual 

acceptability 

(subjective) 

Critical value for FR in the palmtop is 12 Hz, 

but 6 Hz is acceptable 50% of the time. 

53 Meehan et al. 

(2002) 

10, 15, 20, and 30 

Hz 

Placement task Physiological 

Subjective 

presence 

Lower FRs can impair performance and 

feelings of presence; 10 Hz causes subjective 

discomfort. The increase in heart rate was 

greater at 10 Hz than at 15 Hz, indicating 

higher stress at 10 Hz. 

54 Van Breda et al. 

(2005) 

3, 10, and 30 Hz Viewing 2-D 

vs. 3-D maps 

Subjective 

effort rating 

Greater perceived effort associated with 3 Hz; 

positive effect of 3-D map was largest when 

FR was lowest 

55 Wilson & Sasse 

(2000) 

5 and 25 Hz Viewing video Subjective 

quality rating 

5 Hz is acceptable for subjective quality 
36 

56 Wilson & Sasse 

(2000) 

5 and 25 Hz Viewing video Physiological 

measure 

(stress) 

5 Hz caused greater stress (as evidenced by 

physiological measures) 

42 Apeteker et al. 

(1995) 

5, 10, 15 Hz Viewing video 

clips 

Watchability 

QoS 

15 Hz considered “just acceptable” for 

watchability. 

43 Chen (2003) 0.2 & 15 Hz, , 

variable (motionsensitive) 

Conversational 

behavior 

Perceived 

engagement/ 

enjoyment 

FR of 1 new image per 5 seconds is 

considered acceptable for engagement and 

enjoyment in video-mediated conversation, 

but “ineffective” for perceiving hand 

movements; 15 Hz considered to be useful. 

44 French et al. 

(2003) 

2, 4, 8, and 16 Hz Teleoperating 

ground robots 

Perceived 

workload 

FR of 2 Hz is associated with significantly 

greater workload 

45 Ghinea & Chen 

(2003) 

5, 15, 25 Hz Information 

assimilation 

QoP Information assimilation and enjoyment can 

occur for films presented at 5 Hz. 

46 Ghinea & 

Thomas (1998) 

5, 15, 25 Hz Information 

assimilation 

QoP 5 Hz can impair satisfaction; 5 Hz may be 

acceptable in terms of watchability for high 

action and low resolution video. 

47 Gulliver & 

Ghinea (2004, b, 

c, & d) 

5, 15, and 25 Hz Information 

assimilation 

QoP Low FR of 5 Hz has no effect on information 

assimilation. Level of enjoyment and level of 

quality are impaired when reducing FR from 

15 to 5 Hz. Thus, 15 Hz may be the critical 

value for QoP. 

48 Gulliver, Serif, 

& Ghinea, 

(2004) 

5, 15, 25 Hz Information 

assimilation 

QoP Low FR of 5 Hz has no effect on enjoyment 
37 

Glossary of Acronyms 

2-D two-dimensional 

3-D three-dimensional 

AR augmented reality 

FCS Future Combat System 

FR frame rate 

GL gray scale level 

HMD head-mounted display 

LOD level of detail 

MRI magnetic resonance imaging 

MSR mean system responsiveness 

QoP quality of perception 

QoS quality of service 

rms root mean square 

SD standard deviation 

SDSR standard deviation of system responsiveness 

SL system latency 

SR system responsiveness 

UGV unmanned ground vehicle 

VE virtual environment 

VR virtual reality 
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