# Endless Knob with Programmable Resistive Force Feedback

Yuri de Pra, Federico Fontana, Stefano Papetti

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Yuri de Pra, Federico Fontana, Stefano Papetti. Endless Knob with Programmable Resistive Force Feedback. 18th IFIP Conference on Human-Computer Interaction (INTERACT), Aug 2021, Bari, Italy. pp.580-589, 10.1007/978-3-030-85610-6_32. hal-04215517

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# Endless knob with programmable
resistive force feedback

Yuri De Pra<fnref n="1" />, Federico Fontana<fnref n="1" />, and Stefano Papetti<fnref n="2" />

**Abstract.** Touchscreens today represent the most versatile solution for configuring user interfaces. A toll for this versatility is the intangibility of the displayed virtual controls. The addition of haptic feedback can improve their manipulation by reinforcing or even substituting visual information. While haptic rendering of virtual buttons is advancing, tangible knobs seem yet to come, possibly due to the inherent difficulty to conceptualize rotation as an interaction primitive in absence of a physical control. To address this issue, we propose a hybrid solution consisting in an endless knob with programmable resistance to rotation. Compared to existing related devices, it minimizes costs, encumbrance and power consumption, making its installation also possible on portable equipment. After describing its design and main features, we present a test which assessed how haptic feedback rendered by the knob affects performance in a visual target-matching task: users had to select targets placed on a horizontal slider by dragging its cursor through knob rotation. Results show that haptic augmentation significantly improved target acquisition.

## 1 Introduction

In the last decades, interaction with machines has undergone radical changes. In spite of a long-established design tradition of their physical layouts, typical controls such as buttons, switches and knobs have often been replaced by virtual counterparts finding place on touchscreens and capacitive surfaces. Whenever direct manipulation provides safer and simpler interactions, however, tangible controls are still preferred. In today's cars, for instance, most auxiliary functions are accessible from touchscreens, whereas those which more closely affect driving are still a domain of physical knobs and selectors [18]. Tangible controls in fact provide rich haptic feedback allowing safe eyes-free selection while performing other main tasks such as driving [23]. Furthermore, by distributing part of the cognitive load onto the somatosensory channel, they ensure control accuracy in several everyday contexts and work environments [16].

Even if eyes-free interaction can be partially enabled on touchscreens through advanced vibrotactile feedback [21], electroadhesion [26] and friction modulation [28], on the other hand such augmentations do not guarantee more efficient interactions. For instance, no significant effect on performance was found using

<footnote n="1">¹ University of Udine, Udine, Italy</footnote>

<footnote n="2">² Zurich University of the Arts, Zurich, Switzerland</footnote>
touchscreens with vibrotactile feedback under demanding conditions (e.g., when dialing a telephone number while driving a car) [16].

In between virtual and physical layouts, tangible digital controls can be pro-
vided with variable haptic feedback: programmable buttons [17] and sliders [4]
can render different force/displacement curves, whereas haptic knobs can gener-
ate multiple effects such as detents, barriers, spring repulsion through variable
torque (see Sec. 2). The main downside of devices offering force feedback usu-
ally reside in their size, power requirements, and cost which may be several
orders of magnitude higher than that of their purely mechanical counterparts.
For instance, a mechanical detented knob can cost less than 1 USD, whereas
a programmable haptic knob may easily be 100 times as expensive (e.g. [2,6]);
moreover, a haptic knob requires electrical power and is usually much larger.
These drawbacks typically limit the use of such haptic devices to expensive or
safety-critical control panels [29] and to the research laboratory [14].

Here we propose a low-cost, compact knob with programmable resistive force,
built around an electromagnetic braking system. Because of the absence of a
motor and other active components, power consumption is much lower than
that required by similar existing products. The effectiveness of the implemented
resistive force effect was tested in a visual target-matching task operated using
the knob with or without feedback: the former resulted in higher accuracy and
shorter execution time.

## 2 Related work

Different studies focusing on the manual control of visual tasks, occurring es-
pecially during machine operation, have found that the inclusion of context-
dependent haptic feedback can improve human performance, particularly when
the cognitive load is high and multiple tasks are performed at the same
time [24, 7, 16].

For instance, experiments comparing physical and virtual knobs have shown
that tangibility has positive effects on several interaction efficiency mea-
sures [30,23]. More in detail, physical knobs decrease error rate and speed up
task completion up to 20% as compared to their virtual counterparts. Mainly
for this reason, some recent smart gadgets incorporate or offer additional phys-
ical knobs: examples include Google Nest [11], an intelligent touchscreen-based
thermostat, and the remote multimedia controllers Griffin PowerMate [12] and
Microsoft Surface Dial [19].

These evidences suggest that the tangibility of physical knobs is still appeal-
ing. At the same time, today it would be desirable to expand their flexibility
towards multi-parametric control as currently offered by virtual knobs, which,
on the other hand, cannot be operated when visual attention is focused elsewhere
(e.g., during teleoperation) [22,7].

One way to make the manipulation of multiple quantities through a single
physical knob more intuitive is to provide it with haptic effects simulating various
mechanics. However, this comes at the cost of embedding actuators and their
<figure><img src="image_3.png" /><figcaption>Fig. 1: Schematic of the haptic knob: the end effector (A) is connected to an encoder (C) by means of an electromagnetic braking system (B).</figcaption></figure>

relative electronics in the knob, adding cost, complexity, encumbrance and power
consumption. As a result, force-feedback rotary controllers are found only where
this can be tolerated: car dashboards, piloting systems, professional audio/video
editors, robot controls and medical devices. Most such controllers make use of
DC motors to generate force feedback [3,25,13]. Hybrid solutions that combine
motors and brakes have been proposed as well [6]: while allowing the design of
subtle effects, they further increase hardware complexity. Even more expensive
and technologically advanced solutions make use of magneto-rheological fluids
in which the knob shaft is immersed [29,2]: in this case, magnetic-field variations
are used to change the density of such fluids, allowing precise control of the
resistive torque.

Finally, programmable haptic feedback is going beyond the mere reproduc-
tion of mechanical features like torque and detents, as the idea of branding
machine interfaces with a unique haptic “feel” is progressively finding a relevant
place in current technology trends [27,14,5,25]. In synergy with rigorous func-
tional design constraints, this idea has nurtured controllers such as the jog wheel
aboard the recent Traktor Kontrol S4 DJ console [20]. With this design scenario
in mind, we have prototyped an endless knob with programmable resistive force
feedback, which is described in what follows.

3 Hardware / software design

Our knob can be programmed to generate frictional patterns which, by resist-
ing against rotation, induce resistive force-feedback effects. Its main hardware
components consist of a rotary encoder coupled with an electromagnetic braking
system that is controlled by an Arduino microcontroller through its pulse-width
modulation (PWM) output. The details of the hardware have been filed in view
of patenting the technology [9], whereas its application as a multimedia produc-
tion controller has been presented in [10]

Compared to existing haptic knobs, the proposed electromagnetic braking
system has advantages and drawbacks. The main advantage is that it can easily
couple a standard knob to an encoder (see Fig. 1), resulting in a thin, lightweight
and low-cost device. It also needs less power than DC motors [3], hence enabling
battery-supplied portable solutions. The main shortcoming is lack of active force,
which limits the feedback to changes in torque, and reproduction of detents
as well as end-stops. The implemented control algorithm samples the encoder
position and estimates its rotation speed during unidirectional shifts; these data
are then used to set the magnitude and duration of the resistive force. The
current prototype mounts a magnetic encoder with a resolution of 4096 points
per revolution, that is, less than 0.1 degrees.

The output voltage of the microcontroller (between 0 and V<sub>CC</sub>) depends on the relative length of the PWM duty cycle, and directly controls the resistive torque of the knob. For example, if the output maintains a constant voltage, then a proportionally constant torque is applied against rotation.

Detents are reproduced as follows: once the encoder detects the position oc-
cupied by a detent, the algorithm sets the length of the PWM duty cycle and
the value of a counter, depending on the programmed resistance and estimated
rotation speed. The counter is decremented at every cycle, and the electromag-
netic system operates at a constant PWM value until the counter reaches zero.
The harder the detent, the longer the knob resists against motion.

Fig. 2a shows the temporal evolution of the mentioned variables for two
different haptic effects: in the first event (E1), a soft detent is simulated by
applying the highest possible resistance for 50 ms; in the second (E2), the action
of the braking system is modulated with short activations so as to generate a
lower resistance, slowing down hand movement however without stopping it.

In addition to rotation, the knob can also be pushed as a button. Overall,
six different input modes are made available by combining clockwise and coun-
terclockwise rotation with no, short or long push.

4 Evaluation

A visual target-matching task was set up to test the effect of resistive feedback
while performing an action that was functionally equivalent to a drag-and-drop
action.

## 4.1 Procedure

Participants were asked to sit at a desk where a computer screen, keyboard and
the knob were placed. The screen displayed a GUI developed in Processing 3.5
(see Fig. 3): using the knob, a red vertical segment representing a cursor could be
dragged horizontally along a virtual slider which contained five equally spaced
round markers. Two buttons completed the GUI, labeled ‘Confirm’ and ‘Reload’:
<figure><img src="image_4.png" /><figcaption>Fig. 2: Temporal evolution of control variables for various haptic effects: when the encoder position (blue line) reaches a predefined value, resistive force is generated by activating the output signal (black line) until the counter (green line) is decremented to zero. The generated resistive force is proportional to the length of the PWM duty cycle.</figcaption></figure>

they were operated by the computer keyboard respectively for confirming that a target was successfully matched, thus ending the trial, or for repeating the current trial.

The shift of the cursor had an accuracy equal to 11.4 pixels per degree of rotation; the markers were set 320 pixels apart from each other, corresponding to a rotation by about 28 degrees.

At the beginning of each trial, the cursor was reset to the position marked with 'Home' in Fig. 3, and one of the markers along the slider was surrounded by a red circle, symbolizing the current target. Participants had to select this target by dragging the cursor over it: in order to move the cursor they had to push down the knob and turn it. When they reached the target, they released the knob and chose whether confirming or repeating the trial by pressing the respective button on the keyboard using the other hand. At each trial, haptic feedback was either present or absent; when present, it reproduced a hard detent (see Fig. 2b) in correspondence of a marker. Each factor combination of 5 targets
<figure><img src="image_5.png" /><figcaption>Fig. 3: The GUI used in the experiment. A vertical red cursor is controlled by the haptic knob; it moves along a virtual horizontal slider which hosts five round markers. At each trial, one marker is highlighted with the red color, thus becoming the current target. The blue squares are activated by pressing the corresponding buttons on the computer keyboard.</figcaption></figure>

× 2 feedback conditions was repeated 10 times, hence resulting in 100 trials which were randomly balanced for each participant.

A repetition was typically invoked when participants released the knob off-target, similarly to what happens when a wrong drag-and-drop action made with the mouse must be undone. If a trial was confirmed, then the time elapsed from the knob initial press to its release was measured, along with the distance of the cursor from the target (called mismatch from now on).

Ten participants (7 males, 3 females) aged between 24 and 57 (M = 39.9, SD = 10.3), all right-handed, took part in the test on a voluntary basis and were not paid. Before the test, participants performed a training session consisting of 10 trials, in which each factor combination was presented once in random order.

## 4.2 Results

Fig. 4 and 5 respectively show box plots of the mismatch in pixel and time-to-match in ms, for each factor combination. Tests on the data distributions with the D'Agostino method [8] confirmed no significant deviation from normality.

A two-way ANOVA was conducted to study the influence of the two independent variables (target position, feedback condition) on mismatch. Using a Greenhouse-Geisser correction for insphericity, the main effect for feedback yielded F(1,9) = 13.4, p < .005, indicating a significant difference between trials in presence of haptic feedback (M = 3.7, SD = 0.31) and without it (M = 4.54, SD = 0.31). The main effect for position instead was not significant with F(1.5,13.6) = 0.2, p > .05, and so was the interaction effect: F(2.5, 22.5) = 2, p > .05. In agreement with previous studies [24], our results
<figure><img src="image_6.png" /><figcaption>Fig. 4: Box plots showing the mismatch for each factor combination.</figcaption></figure>

show that haptic feedback significantly improved the precision of the action. The smaller mismatch did not come unexpected though, as the increased resistance to rotation occurring while traversing a marker supported participants to stop the cursor at the right location. A further two-way ANOVA was performed to study the influence of the two independent variables on the time-to-match. After a Greenhouse-Geisser correction for insphericity, the main effect for feedback was not significant with F(1,9) = 0.43, p > .05. The main effect for position yielded F(1.4,12.8) = 22.3, p < .001, indicating a significant difference between position 1 (M = 1396, SD = 150), position 2 (M = 1720, SD = 145), position 3 (M = 1799, SD = 133), position 4 (M = 2049, SD = 184) and position 5 (M = 2223, SD = 170). The interaction effect was not significant: F(1.5,13.3) = 1.4, p > .05. The time-to-match depended on the position, with longer time associated to farther targets. While this result may appear obvious at first, one must consider that haptic feedback caused resistance to knob rotation each time a marker had to be traversed, however this had no significant effect on time-to-match. Even further, the time-to-match in presence of haptic feedback was on average generally lower, suggesting that resistive force potentially enables even faster execution of target-matching tasks.

# 5 Conclusions

A low-cost knob controller with programmable resistive feedback was prototyped.
<figure><img src="image_7.png" /><figcaption>Fig. 5: Box plots showing the time-to-match for each factor combination.</figcaption></figure>

Its effectiveness was assessed in a visual target-matching test that showed a significant reduction of the positional mismatch when resistive feedback was applied to the knob.

Our study suggests that, even in absence of active forces as those provided by more expensive, bulky and power hungry motorized knobs, resistive feedback has concrete potential to support effective visual browsing of sequential domains such as sliders, top-down menus, and in general all those maps where physical rotary controls can be conveniently employed for the selection of targets.

Future plans include the design of refined haptic effects and the development of a systematic software communication framework operating between the knob and applications able to send/receive control messages belonging to standard protocols.

# 6 Acknowledgments

This research was partially supported by project HAPTEEV funded by the Swiss National Science Foundation (grant 178972). Yuri De Pra's Ph.D. is funded with a scholarship of The Research Hub by Electrolux Professional SpA.

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