NASA 

NASA Technical Memorandum 102204 

U” 

Results and Applications of a 

Space Suit 

Range-of-Motion Study 

AI Reinhardt 

{NASA-Tn- 102204) RESULTS AND APPLICATIONS ~a9-26398 

OF A SPACE SUIT EANGE-OF-HOTION STUDY 

(NASA. Arnes Research Cater) 16 p CSCL 058 

Unclas 

G3/54 3223913 

July 1989 

National Aeronautics and 

Space Administration 
~~~~ ~ ~~ ~ 

NASA Technical Memorandum 102204 

Results and Applications of a 

Space Suit 

Range-of-Motion Study 

AI Reinhardt 

U.S. Air Force Office of Scientific Research, Ames Research Center, Moffett Field, California 

July 1989 

NASA 

National Aeronautics and 

Space Administration 

Ames Research Center 

Moffett Field, California 94035 
ABSTRACT assesses the value-added potential of the overall technique 

to the madmachine design process. 

The range of motion of space suits has traditionally 

been described using limited two-dimensional mapping of 

limb, torso, or arm movements performed in front of an 

orthogonal grid. A new technique for recovering extravehicular (EVA) space suit range-of-motion data during 

underwater testing was described in a paper presented by 

the author at the 1988 conference. The new technique uses 

digitized data which is automatically acquired from video 

images of the subject. Three-dimensional trajectories are 

recovered from these data, and can be displayed using twodimensional computer graphics. Results of using this technique in a study of the current shuttle EVA suit during 

underwater simulated weightlessness testing are discussed. 

Application of the data for use in animating anthropometric 

computer models is highlighted. 

DIFFERENT METHODS OF MEASURING 

The range of motion of a subject wearing a space suit 

during underwater simulated weightlessness testing was 

discussed by Reinhardt and Walton in “The Recovery and 

Use of Space Suit Range-of-Motion Data” (I).* One of the 

systems described in that paper was the Motion Analysis 

ExpertVisionm system (2). The Expenvision system was 

used to describe the range of motion of the current space 

shuttle extravehicular activity (EVA) suit in a study conducted at Marshall Space Flight Center’s (MSFC) Neutral 

Buoyancy Simulator (NBS) in August 1988. 

This paper consists of two sections. The first section 

describes the experiment setup, discusses the results, and 

offers suggestions on how to improve the procedure for 

collecting space suit range-of-motion data during underwater testing. The second section of this paper discusses 

applications of the data to an animated computer model and 

*Numbers in parentheses denote references at end of paper. 

SECTION ONE: THE STUDY 

MOTION ANALYSIS EXPERTVISION SYSTEM 

Expertvision is described in detail in Ref. 1. Briefly, 

the system uses passive, retroreflective targets which can be 

attached to isolated landmarks. Data are collected using 

four standard industrial video cameras which are precisely 

placed within underwater housings to compensate for 

refraction. The four camera housings are mounted in the 

underwater test facility so that any two of the four cameras 

can always “see” the targets to be tracked. Video signals 

from each of the cameras are fed to a video processor 

(VP310) at the surface where the outlines of the various 

targets are extracted and passed to the system host 

(SUN 3/110C workstation). 

Target identification is achieved by contrast. Using 

on-axis, underwater lighting, the retroreflective targets 

attached to the space suit are, theoretically, considerably 

brighter than other elements of the image. The video processor describes the location of each target by generating a 

list of pixels which form the outline of each spot in the 

video images. This is done at standard video rates 

(60 frames per second from each of the four cameras) 

and can be sustained for 20 to 25 seconds. 

When the raw (pixel) coordinates have been passed to 

the SUN host, they are manipulated by the system software 

which incorporates the photogrammetric algorithms 

described by Walton (3) to produce the required threedimensional (3-D) trajectories of the landmarks. Actual 

target position is defined as the centroid of the outline 

described by the pixels. With 3-D histories available, the 

standard system software can be used to manipulate and 

display results in various forms, including component time 
histories (x vs t. y vs t, z vs t), orthographic projections of 

reach envelopes (x vs y, x vs z, y vs z), and stick figures. 

The raw trajectories can also be converted to ASCII files, 

which can be ported to another host system if desired. 

---I 

EXPERIMENT SETUP 

‘I 

The system was set up in MSFC’s NBS. The NBS is a 

cylindrical water tank 70 feet in diameter and 40 feet deep. 

Descriptions of the experiment setup and of the problems 

overcome during installation follow. 

Subject Position -- A mockup of the shuttle cargo bay 

was placed in the bottom of the NBS. Shuttle foot restraints 

were mounted on a crossbar of the cargo bay and positioned 

so that the foot restraints were in the center of the tank. The 

foot restraints were thus approximately 11 feet above the 

bottom of the tank. 

Camera Position -- Four NEC CCD cameras (Model 

#TI-22A) with 17-mm lenses were mounted inside rectangular watertight aluminum housings which contained an 

optical quality dome at one end (Fig. 1). The cameras were 

positioned inside the housings to eliminate refraction using ~ techniques described by Walton (4). 

The housings were then mounted on simple support 

brackets which allowed for swivel and tilt adjustment. The 

four camera housings and brackets were bolted to the sides 

of the NBS at 90” intervals as shown in Fig. 2. 

The cameras were mounted 8 feet above and 35 feet 

away from the subject’s foot restraints. Once the camera 

position was verified, the adjustments on the mounting 

brackets were secured to prevent camera movement. The 

video signals were linked, as described earlier, to the video 

processor (VP310) located on the topside deck of the tank 

with the SUN host system. 

, r12’‘-Id 

Fig. 1 Underwater camera housing 

Fig. 2 Experiment setup 

Target Selection -- During camera installation, it was 

determined that the size of the facility and the lighting conditions were not conducive to using on-axis camera lighting 

and the bright remoreflective targets as planned. The study 

had originally been planned for Johnson Space Center 

(JSC), but was switched to MSFC due to schedule 

constraints. 

The cameras and targets were originally selected for a 

distance of 24 feet between camera and subject at JSC. The 

additional 11 feet at MSFC caused the illuminative power 

of the single on-axis light to fall by a factor of 4 while the 

relative target size was reduced by a factor of 1.5. In addition, relative light losses due to scatter are far greater under 

water than in air. Thus, the single on-axis underwater light 

was not strong enough to illuminate the targets for consistent data tracking. 

Furthermore, the NBS is housed in a large building 

which has an overhead skylight above the tank. This caused 

the lighting conditions to vary with weather conditions 

during the test. During camera installation, it was noted that 

the support divers’ flippers tracked clearly at the other end 

of the contrast spectrum (i.e., dark targets on a bright background.) A decision was made to use dark targets for the 

study so ordinary black racquet balls were chosen. Fifteen 

of these “targets” were affixed to the current shuttle EVA 

suit in the positions shown in Fig. 3. The on-axis underwater lights were removed from the cameras and were not 

used. 

System Calibration -- An 8-foot cubic aluminum 

framework with targets suspended at known distances was 

centered over the foot restraints. Once positioned, the 

structure was filmed by the system to establish a coordinate 

reference system around the foot restraints. Once this was 

2 
Fig. 3 Suited subject target location 

complete, the framework structure was removed and the 

range-of-motion study began. 

TEST PROTOCOL 

Fourteen motions were recorded of a subject in the foot 

restraints wearing the shuttle EVA suit with targets attached 

as described above. The motions performed were taken 

from the current NASA test plan for evaluating range-ofmotion performance of advanced suits and are listed below 

(5). 

1. Neutral or reference position 

2. Upward reach right arm 

3. Upward reach left arm 

4. Overhead reach from side of body 

5. Inboard reach 

6. Side-to-side reach 

7. Torso rotation 

8. Torso bend-windmill 

9. Straight front kick, left leg 

10. Hip abduction, left leg 

11. Straight front kick. right leg 

12. Hip abduction, right leg 

13. Forward torso bending 

14. Backward torso bending 

The same protocol was used for two different suited 

subjects. The first subject repeated the procedure on different days for a total of three trials. 

TEST RESULTS 

OVERVIEW -- Target outlines as acquired by 

Expertvision appear on the monitor screen as in Fig. 4. 

The target outlines are described visually as small, closed, 

irregular polygons. Each of the four cameras has a similar 

view of the targets, but from the viewpoint of the camera's 

position. To simplify the data analysis of the study, targets 

of interest for a given motion were specifically selected for 

tracking, while miscellaneous targets were blocked out 

through the editing system of the SUN host. Thus for 

upward reach, right arm, only the three targets of the right 

arm were tracked by the processor. For full body motions, 

this editing feature was not used. 

-I 

4 

F: 

ce 

w 

> 

-r 

* 

t 

1.1 '.I * -.-.- 

a ,- -, i 

-6 

HORIZONTAL POSITION, pixels 

Fig. 4 Target outlines 

Data from the first trial were unusable due to weather 

conditions. The weather was partly cloudy, which caused 

the NBS lighting conditions to vary significantly and 

resulted in extremely noisy data. Noisy data, in this study, 

is defined as unclear target identification. If target contrast 

was not clear due to lighting conditions, reflections, and 

shadows, the system had difficulty tracking and identifying 

the targets during movement. 

The second and third trials, however, were run under 

much better conditions for data tracking, because the 

weather was sunny. Of the 14 motions studied, only 3 were 

not digitized. These were.side-to-side reach, torso rotation, 

and torso bend-windmill. The raw data in these three 

motions contained too much noise for accurate 3-D digitizing. The remaining motions were edited from the third 

3 
mal, except for motion #1 (neutral position) and motion 

#14 (backward torso bending). These two motions were 

processed from the second mal.. 

RANGE-OF-MOTION GRAPHS 

Graphic plots of the motions that were successfully 

tracked and digitized are discussed in the following section. 

The coordinate axes used for data editing are provided in 

Fig. 5. The suited subject is facing forward along the 

y-axis. The right side of the space suit (facing forward) is in 

the positive x-axis, while the left side is in the negative x 

direction. The positive z-axis then follows the right-hand 

thumb rule. Thus, an XY plot is a top-down view of the 

subject, while YZ provides a sagittal view. An XZ view is a 

view of the subject from the rear. (-X)Z views provide the 

subject’s motion from the perspective of a viewer directly 

in front of the subject. A simple stick figure construction is 

used to connect target positions in all of the plots. To aid in 

understanding the graphic plots, a small reference model 

was added to each plot to visualize the orientation of the 

printout. 

Y 

Fig. 5 Coordinate axes reference system 

Each plot represents a significant amount of data. As 

shown in Table 1, for every 1 second of data, each target’s 

position is described at the rate of 60 Hertz (Hz). or 60 

frames per second on each camera. For 9 seconds of a typical motion, this equates to 540 individual frames of x,y, and 

z data for each target after digitizing. For the full body 

shots where 15 targets are tracked, this corresponds to 

8100 lines of x,y, and z data for each camera view. Thus, 

4 c 

the graphic plots represent a more easily understood interpretation of the data. 

The reference or neutral body position is recorded in 

Figs. 6 and 7. This motion or position is the position the 

suited subject’s body assumes when relaxed in the foot 

restraints. Upward reach right arm is shown in Figs. 8 

and 9, while upward reach left arm is shown in Figs. 10 

and 11. 

Overhead reach from side of body is shown from three 

different viewpoints in Figs. 12 through 14. The (-X)Z 

view of this motion defines the envelope for this particular 

motion. The axis provides a measurement of the envelope. 

An exact measurement can be obtained by referring to the 

tabular x,y,z target data in the ASCII files. In Fig. 14, for 

example, the maximum span along the x-axis, which 

corresponds to the two hand-held targets, is approximately 

69 inches, while the maximum z-span for the same two 

targets are 40 inches for the right hand and 42 inches for the 

left hand. 

Inboard reach is viewed in Figs. 15 through 18. Note 

that Figs. 17 and 18 are from the same viewpoint. The difference is that Fig. 17 connects the elbow target to the head, 

while Fig. 18 does not. 

Two views of straight front kick, left leg are provided in 

Figs. 19 and 20. Hip abduction, left leg is shown in Figs. 21 

and 22. The extreme reversed knee angle indicates that target identification was reversed during editing. This example 

was intentionally left reversed to illustrate an example of 

what errors can occur during digitizing the target information and how readily they’re identified. A correct plot of hip 

abduction is provided in Figs. 23 and 24 for the right leg. 

Note how limited this particular motion is for the current 

shuttle suit. 

A test of the system’s capability to track all 15 targets is 

provided in forward torso bending (Figs. 25-27). Figure 26 

vividly shows the limitations of the current EVA suit in 

bending forward at the hips. Another demonstration of 

tracking all 15 targets is shown in backward torso bending 

(Figs. 28 and 29). 

SUGGESTED IMPROVEMENTS FOR DATA 

COLLECTION 

As demonstrated in the preceding section, the Motion 

Analysis Expertvision system was able to successfully 

track and digitize targets for 11 of 14 motions of a spacesuited subject during underwater testing. The editing and 

analysis effort was made more difficult than necessary 

because of variations in ambient lighting during the test. 

Reducing this noise level will improve the tracking capability of the processor and simplify the digitizing process. 
~ ~~ 

Path 

number 

Object name: 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

~~ 

TABLE 1. AN EXAMPLE OF DIGITIZED TARGET DATA 

Frame 

number 

1. elbow 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

Time 

(seconds) 

0. 

0.167e-01 

0.333e-01 

0.500e-01 

0.667e-01 

0.833e-01 

0.100 

0.1 17 

0.133 

0.150 

0.167 

0.183 

0.200 

0.217 

0.233 

0.250 

0.267 

0.283 

0.300 

0.317 

0.333 

0.350 

0.367 

0.383 

Based on the experience gained during this study, the following improvements are suggested: 

a) Facility lighting: All light sources should be noted 

and controlled to maximize the contrast desired. Skylights and windows shouId be covered to eliminate 

sources of light variation. Underwater lights should be 

kept at a constant setting. In-tank hardware, such as 

mockups, is a source of reflection and contrast and 

should be removed. The field of view for each camera 

should be maintained as uniform as possible. 

b) Target selection: Spherical markers, as opposed to 

ring-banded markers, should be used where possible to 

maintain a consistent target outline for the processor. 

When possible, remove extraneous targets before a particular motion study rather than having all targets present for all studies. This will reduce the chances of 

incorrect target identification. 

c) Camera placement and selection: Lower the camera 

placement to achieve a more head-on field of view and 

record each camera’s view on videotape, even though 

the data is transferred directly to the host system. This 

will provide a reference to resolve target identification 

problems during the data analysis phase. Care should be 

used if underwater lights are used with bright targets to 

avoid shining a light in an opposing camera. 

X 

(inches) 

26.5837 

26.6229 

26.6348 

26.6573 

26.6565 

26.6800 

26.6254 

26.71 19 

26.6054 

26.7048 

26.7056 

26.5594 

26.7790 

26.6829 

26.5862 

26.7 139 

26.6902 

26.5807 

26.6449 

26.624 1 

26.727 1 

26.6432 

26.6363 

26.3561 

Y 

(inches) 

4 1.9279 

42.1478 

42.0609 

42.08 18 

42.0847 

42.0044 

42.0554 

42.0307 

42.1 145 

42.3059 

42.3028 

42.1807 

42.2252 

42.3650 

42.2176 

42.3278 

42.3890 

42.2885 

42.3266 

42.4262 

42.5492 

42.6915 

42.6809 

42.5467 

Z 

(inches) 

41.9139 

42.0096 

41.9376 

41.9545 

4 1.9403 

4 1.922 1 

41.9561 

41.9205 

42.03 13 

42.0854 

42.1006 

42.1666 

42.2807 

42.3749 

42.4401 

42.5586 

42.6303 

42.67 5 9 

42.8429 

42.9722 

43.129 1 

43.3462 

43.3913 

43.6346 

d) Data acquisition rate: Consider a tradeoff between 

reducing the data acquisition rate and running a particular motion longer. A 60-Hz rate is faster than necessary when capturing voluntary human motion, encumbered by a space suit and limited by the underwater 

environment. The rate could possibly be reduced to 

30 Hz or less without losing critical data. This would 

allow analysis of longer duration motions. 

SECTION TWO: DATA APPLICATIONS 

DIGITIZED PLOTS 

The digitized plots generated by ExpertVision are useful for comparative purposes. Possible uses for a space suit 

designer include a comparison of reach performance of different suit designs for the same.subject, or the effect on 

reach performance of a modification to an existing suit 

design. As mentioned in Ref. 1, the ExpertVision approach 

has the potential to improve the accuracy over the existing 

grid method of measuring reach performance, from 

f3.0 inches to M. 1 inches. 

COMPUTER ANIMATION 

Perhaps a more visually descriptive use of the data and 

one that is currently the subject of much interest, is the 

application of the data to aid or drive the animation of an 

5 
anthropometric computer model. Dr. M. Ayoub, of Texas 

Technical University, has used the Expertvision system to 

drive the animation of simple stick figures performing lifting tasks (6). He also incorporates complex force, acceleration, and velocity equations in his model of back forces 

during lifting. The equations are driven by the coordinate 

data obtained from Expertvision. 

The data files themselves can be readily viewed as raw 

animated files. At 60 Hz, there is more than enough data for 

use as an animated script. In fact, for a goal-oriented model 

such as POSIT, the data could be filtered down to approximately 20 Hz to achieve animation and thus save computer 

time (1). 

Another use for the data is as an aid in animating more 

detailed anthropometric models. One such model, Crew 

Chief, developed by J. McDaniel, et al. at the U.S. Air 

Force Harry G. Armstrong Aerospace Medical Laboratory, 

Wright-Patterson AFB, achieves animation through programmed algorithms (7). The strategy for the Expertvision 

data is as a check and refinement of the motions generated 

by Crew Chief. Thus a program for overhead reach of a 

space-suited model is created by Crew Chief, and then 

refined by the data generated by Expertvision of a human 

subject performing the same task. 

VALUE-ADDED POTENTIAL 

One key question which requires discussion might be 

phrased as, “What does the value-added capability of 

Expertvision, and the use of the data files created by 

Expertvision for animating computer models, represent 

to the overall system-design process?” 

As stated earlier, Expertvision provides an increase in 

accuracy over the current grid method for describing space 

suit range-of-motion performance. In addition, it is believed 

that once a system like Expertvision is set up and properly 

adjusted, that the time and labor required to generate the 

plots of interest would decrease, thus realizing a savings. 

The intriguing application from a systems viewpoint is 

the possibility of animating computer models based on data 

collected directly from a human subject. Such a capability, 

when finally realized, might offer the following benefits: 

1) The animated files created from a subject offer a 

direct way for the computer modeler to validate animation 

algorithms. This is the method currently under study with 

the Crew Chief model. 

2) The animated files provide an interactive tool for the 

workstation designer to verify human reach restriction 

requirements. For EVA workstations and space suits this is 

extremely important. Providing the designer with files of 

EVA work tasks based on suited-subject data would provide the capability to assess the effect of proposed workstation design changes on reach capability. 

3) Crew Chief includes key anthropometric data such as 

strength capabilities for various tasks (7). Coupling the 

motion data with strength data obtained from instruments 

like the Cybex Dynamometer used in current space suit 

tests would define a functional reach and strength envelope 

for the computer model. Thus a workstation designer could 

evaluate the effects of a proposed change to the workstation 

by using an animated model to assess if the range of 

expected users could reach the required task, and, more 

importantly, perform the task. 

4) The approach does not have to be limited to EVA 

workstations. The same technique could be applied to any 

madmachine interface to optimize a workstation with 

regard to human performance. 

SUMMARY 

An experiment was conducted which assessed the 

capability of the Expertvision system to describe space suit 

range of motion during underwater testing. The results of 

the experiment indicate the system successfully tracked targets during the test for two different subjects. Suggestions 

were made on how to improve the data collection technique 

during underwater testing. With a properly calibrated 

system, this experiment demonstrates the validity of the 

approach for quantifying space suit reach performance and 

the use of Expertvision as a comparative measurement tool 

for space suit designers. A discussion of the application of 

the data files to animated computer models indicated significant areas of potential benefit to the system design process. The technique described could be applied to any 

madmachine interface to optimize human performance 

during the design phase of the system process. 

ACKNOWLEDGMENT 

The success of this experiment was the direct result of a 

dedicated and enthusiastic support team, which spanned 

government agencies and contractors alike. The following 

people bear special mention: 

Dr. Jim Walton, President of 4-D Video, Sebastopol, CA, 

whose “on-the-fly” adjustments salvaged the experiment; 

Mr. Shelbome Fung, Vice President of Engineering, 

Motion Analysis Corporation, Santa Rosa, CA, for completing the data analysis and graphic display portions of the 

experiment; 

6 
Mr. Vyga Kulpa and the rest of the MSFC diver support 

group for a superb professional job during the week of 

testing; and 

LEFT 

Mr. Medhat Korna, Human Resources Lab, WPAFB, for 

his support and use of the data in conjunction with the 

Crew Chief model. 

REFERENCES 

1. Reinhardt, A. and Walton, J. S., “The Recovery and 

Utilization of Space Suit Range-of-Motion Data,” SAE 

Paper 881091, July 1988. 

2. Motion Analysis Corporation, Expertvision 3D System 

Specification and 3D Software Specifications, 

3650 North Laughlin Road, Santa Rosa, California 

95403. 

3. Walton, J. S., “Close Range Cine-Photogrammetry: A 

Generalized Technique for Quantifying Gross Human 

Motion,” Doctoral Dissertation, The Pennsylvania State 

University, 1981. 

Y 

LEFT HAND 

RIGHT TOE 

29.07 63.59 

HORIZONTAL POSITION, in. 

Fig. 6 Referencdneutral position, XY view 

4. Walton, J. S., “Underwater Tracking in ThreeDimensions Using the Direct Linear Transformation 

and a Video-Based Motion Analysis System.” 

Proceedings of the 32nd International Technical 

Symposium on Optical and Optoelectronic Applied 

Science and Engineering. Volume 980: Underwater 

Imaging. San Diego, California, August 1988. 

5. Kosmo, J. J. and Spenny, W. E., “Space Suit WETF 

Evaluation Test Plan,” CTSD-SS-201, Johnson Space 

Center, Jan. 1988. 

6. Ayoub, M., “Biomechanical Modeling,” Presentation 

Notes, NASA Ames, March 30, 1988. 

7. McDaniel, J., et al.. “User’s Guide for Crew Chief A 

Computer Graphics Simulation of an Aircraft Maintenance Technician,” AAMRL-TR-88-034, May 1988. 

RIGHT 

63.59 

EFT HIP 

LEFT KNEE 

.EFT ANKLE 

29.07 

HORIZONTAL POSITION, in. 

Fig. 7 Reference/neutral position, (-X)Z view 

7 
z 

I 

ORIGINAL PAGE IS 

OF POOR QUAUTY 

z 

I 

15.19 61.83 

HORIZONTAL POSITION, in. 

Fig. 8 Upward reach right arm, YZ view 

71.87 55.35 

HORIZONTAL POSITION, in. 

Fig. 9 Upward reach right arm (-X)Z view 

I .. I 

30.63 61.31 

HORIZONTAL POSITION, in. 

Fig. 10 Upward reach left arm, YZ view 

2 

t 

44.20 23.07 

HORIZONTAL POSITION, in. 

Fig. 11 Upward reach left arm, (-X)Z view 

8 
Y ORIGINAL 

OF POOR 

13.51 82.2 

HORIZONTAL POSITION. in. 

'Fig. 12 Overhead reach from side of body, XY view 

2 

t 

PAGE 

QUAL1 

'3 

-Y 

r ~~~ I 

37.12 60.43 

HORIZONTAL POSITION, in. 

Fig. 13 Overhead reach from side of body, YZ view 

82.n 13.51 12.20 80.82 

HORIZONTAL POSITION, in. HORIZONTAL POSITION, in. 

Fig. 14 Overhead reach from side of body, (-X)Z view Fig. 15 Inboard reach, XY view 

9 
t i 

49.10 73.62 

HORIZONTAL POSITION, in. 

Fig. 16 Inboard reach, YZ view 

I .. I 

80.82 12.20 

HORIZONTAL POSITION, in. 

Fig. 18 Inboard reach, (-X)Z view 

I 

80.82 12.20 

HORIZONTAL POSITION, in. 

Fig. 17 Inboard reach, connected (-X)Z view 

20.55 58.49 

HORIZONTAL POSITION, in. 

Fig. 19 Straight front kick, left leg, YZ view 

10 
z 

33.75 45.26 

HORIZONTAL POSITION, in. 

ORIGINAL PAGE IS 

OF POOR QUALITY 

Y 

I 

I /A I 

45.43 25.72 

HORIZONTAL POSITION, in. 

Fig. 21 Hip abduction, left leg, (-X)Z view 

'Y 

Fig. 20 Straight front kick, left leg, XY view 

30.25 52.01 

HORIZONTAL POSITION, in. 

Fig. 22 Hip abduction, left leg, YZ view 

11 
57:81 

HORIZONTAL POSITION, in. 

z 

n 

I 

Fig. 23 Hip abduction, right leg, (-X)Z view 

z 

L ANKLE 

L TOE 

29.51 

J 

68.02 

HORIZONTAL POSITION, in. 

Fig. 25 Forward torso bending, (-X)Z view 

12 

-Y 

32.41 52.59 

HORIZONTAL POSITION, in. 

Fig. 24 Hip abduction, right leg, YZ view 

39.93 90.42 

HORIZONTAL POSITION, in. 

Fig. 26 Forward torso bending, YZ view 
I LEFT HAND GHT HAND 

29.51 68.02 

HORIZONTAL POSITION, in. 

Fig. 27 Forward torso bending, XY view 

-19.08 +46.73 

HORIZONTAL POSITION, in. 

Fig. 28 Backward torso bending, YZ view 

20.85 64.08 

HORIZONTAL POSITION, in. 

Fig. 29 Backward torso bending, XY view 

13 
Nalonl runsn Awmubci Md Report Documentation Page Spa Admnt.b.lim 

1. Report No. 

NASA TM-102204 

2. Government Accession No. 3. Recipient's Catalog No. 

4. Title and Subtitle 

Results and Applications of a Space Suit Range-of-Motion Study 

7. Author@) 

A1 Reinhardt 

National Aeronautics and Space Administration 

Washington, DC 20546-0001 

5. Report Date 

July 1989 

6. Performing Organization Code 

8. Performing Organization Report No. 

A-89164 

10. Work Unit No. 

c 14. Sponsoring Agency Code 

9. Performing Organization Name and Address 

Ames Research Center 

Moffett Field, CA 94035 

2. Sponsoring Agency Name and Address 

I 

5. Supplementary Notes 

Point of Contact: A1 Reinhardt, Ames Research Center, MS 239-15, Moffett Field, CA 94035 

(415) 694-6728or FI'S 464-6728 

Report submitted as meeting paper for SAE Intersociety Conference on Environmental Systems, 

11. Contract or Grant No. 

13. Type of Report and Period Covered 

Technical Memorandum 

July 24-27, 1989 

6. Abstract 

7. Key Words (Suggested by Author(s)) 

Space suit 

The range of motion of space suits has traditionally been described using limited two-dimensional 

mapping of limb, torso, or arm movements performed in front of an orthogonal grid. A new technique 

for recovering extra-vehicular (EVA) space suit range-of-motion data during underwater testing was . 

described in a paper presented by the author at the 1988 conference. The new technique uses digitized 

data which is automatically acquired from video images of the subject. Three-dimensional trajectories 

are recovered from these data, and can be displayed using two-dimensional computer graphics. Results 

of using this technique in a study of the current shuttle EVA suit during underwater simulated weightlessness testing are discussed. Application of the data for use in animating anthropometric computer 

models is highlighted. 

18. Distribution Statement 

Unclassified-Unlimited 

9. Security Classif. (of this report) 

Unclassified 

Range of motion 

Study results and applications 

20. Security Classif. (of this page) 21. No. of Pages 

Unclassified 14 

Subject Category - 54 

I 1 

\SA FORM 1626 OCT 86 

For sale by the National Technical Information Service, Springfield, Virginia 221 61 

22. Price 

A02