# Trimanipulation: Evaluation of human performance
in a 3-handed coordination task

Yanpei Huang1,2∗, Jonathan Eden1∗, Ekaterina Ivanova1, Soo Jay Phee2 and
Etienne Burdet1∗ This work was funded by the Singapore National Research
Foundation through the NRF Investigatorship Award (NRF-NRFI 2016-07), by the
UK EPSRC FAIRSPACE, and EU H2020 PH-CODING (FETOPEN 829186), TRIMANUAL (MSCA
843408), NIMA (FETOPEN 899626) grants.1Authors are with the Department of
Bioengineering, Imperial College of Science Technology and Medicine, London,
UK. 2Authors are or were with the School of Mechanical and Aerospace
Engineering, Nanyang Technological University, Singapore. ∗Corresponding
authors: {yanpei.huang, j.eden<EMAIL_ADDRESS>
###### Abstract

Many teleoperation tasks require three or more tools working together, which
need the cooperation of multiple operators. The effectiveness of such schemes
may be limited by communication. Trimanipulation by a single operator using an
artificial third arm controlled together with their natural arms is a
promising solution to this issue. Foot-controlled interfaces have previously
shown the capability to be used for the continuous control of robot arms.
However, the use of such interfaces for controlling a supernumerary robotic
limb (SRLs) in coordination with the natural limbs, is not well understood. In
this paper, a teleoperation task imitating physically coupled hands in a
virtual reality scene was conducted with 14 subjects to evaluate human
performance during trimanipulation. The participants were required to move
three limbs together in a coordinated way mimicking three arms holding a
shared physical object. It was found that after a short practice session, the
three-hand trimanipulation using a single subject’s hands and foot was still
slower than dyad operation, however, they displayed similar performance in
success rate and higher motion efficiency than two person’s cooperation.

##  I Introduction

Teleoperation is a key solution for interacting with remote objects and in
dangerous environments [1, 2]. Many teleoperation tasks require more than two
instruments for successful task completion, e.g in robotic laparoscopic
surgery, three instruments are required including the laparoscopic camera.
Currently these tasks are executed by a team working together. However,
cooperation between two people may lower the operation efficiency due to
communication errors [3] or uncoordinated motion. Three-handed trimanipulation
using SRLs controlled by one operator can be a solution to the communication
issue coming from multiple operators.

SRLs can be controlled by hands-free interfaces using the human body as a
reference including control from the head [4], tongue [5], foot [6], gaze [7]
and voice [8]. Among these hands-free control strategies, the use of foot
motion is an attractive source due to the foot’s ability to control in
multiple DoFs and its relative independence from the subject’s hands and/or
eyes [9, 10, 11]. The analysis of subject’s performance while using foot to
control a SRL has only recently been considered.

Abdi et al. [12, 13] first conducted studies of trimanual control using the
foot and demonstrated that a virtual “third hand” can be controlled by the
foot with the natural hands to head towards objects. For the given reaching
task, they found that users preferred to use three hands compared to only two.
The capability of subjects to use two additional arms was also considered in
the later studies [10, 11], in which a single subject performed bipedal tel-
emanipulation of two robotic arms demonstrating a quad-manual operation. These
studies were either limited to the control of a single axis motion using the
SRL or still in the demonstration stage without a systematic study of the
user’s ability for different kinds of tasks. Particularly, the studies have
not yet considered tasks which required simultaneous coordination of more than
two hands.

To investigate different tasks on trimanual performance, Huang et al. [14]
compared the impact of the addition of a third hand to bimanual tasks
involving the hands acting independently or having coupled motion. It was
found that the addition of the foot controlled hand slowed operation time,
however, when the hands acted independently of one another there was otherwise
no reduced performance when the hands were uncoupled. The relative performance
of trimanipulation was then compared to the use of multiple operators [15].
Three different levels of coupling between the hands were considered, where in
all cases the couple outperformed a single trimanual subject. This study,
however, showed evidence of an unsaturated learning effect in trimanual
condition. The authors suggested that the differences in performance between
the dyad and trimanipulation were the smallest for the case in which the
subject limbs were continuously coupled together.

In this paper, we extend the study of [15] to specifically account for the
effect of learning on coupled tri-manipulation. We investigated i) the
learning of tri-manipulation with the addition of supernumerary limb in a
three hand coordination task; ii) compared the users’ performance to dyadic
operation of one person performing bi-manipulation and another person using
their foot, and iii) studied the effect of an unpredictable environment on the
operation. A tri-manipulation teleoperation platform was built with two hand
interfaces, one foot interface and a virtual reality scenario. We recruited 14
subjects for a study taking place over two days in which we asked the subjects
to perform a trimanual virtual task requiring coordination of three limbs. The
results show that solo trimanual performance could achieve similar level to
two person’s cooperation in the aspects success rate and coordination. In
addition, the participants seem to have a more efficient motion in trimanual
mode than when cooperating with a partner.

Figure 1: (a) Experimental setup. (b) Mapping between hand/foot and virtual
hands (VHs). VH1 (blue) is controlled by left hand, VH2 (red) is controlled by
right hand and VH3 (green) is controlled by the foot.

##  II Method and material

###  II-A System and task

The trimanipulation system is comprised of two hand interfaces (Omega.7 from
Force Dimension Inc., Switzerland), one foot interface [16], and a virtual-
reality testing environment. Fig. 1a shows the experimental setup with the
trimanipulation system and the operator. Throughout the study, the operator
sat comfortably on a chair, holding the handles of the hand interfaces, whose
height could be adjusted using the mounting table, with both hands and placing
their right foot on the pedal of the foot interface. They faced the monitor
which displayed feedback of the virtual task. As shown in Fig. 1b, the
position of the hands $x_{hi}$ and $y_{hi}$ (workspace 16 $\times$ 16 cm2) and
foot $x_{f},y_{f}$ (workspace 4 $\times$ 4cm 2) in the horizontal plane were
used to control VHs 1, 2 and 3 respectively in the vertical
$x^{\prime}-y^{\prime}$ plane.

Figure 2: Experimental protocol. (a) Training scene. (b) Trimanual task scene.
(c) Experimental procedure flow chart.

The virtual task with VHs (Fig. 2a) simulated a three-hand coordination
scenario. This task was designed to simulate everyday activities requiring
physical coordination of each hand, e.g. holding a tray or the case when
assembling furniture. In the task, an elastic triangle object was held by
three VHs and its center of mass (CoM) controlled by the coordinated movement
of the three VHs. Haptic feedback was provided to hands to rendering the
elastic force. The participants were asked to maintain the length of the three
elastic edges within a set range and to move the CoM to the target. The target
was updated on the screen every three seconds and changed from black to green
color when it was reached. When the elastic edge was not in the required range
(i.e. smaller than 0.7, or larger than 1.3 times the initial length), the
elastic bar either ‘broke’ or a ‘collision’ was indicated through visual cues.
A supplementary video is attached to show the task operation.

###  II-B Experimental procedure

Fourteen participants (eight females), without motor impairment, with an
average age of $28.8\pm 2.5$ years were recruited. All subjects were right
footed according to the ball-kick dominant leg test [17], and none of them
regularly used any foot based gesture system. The experiment contains two days
(Fig. 2c).

On the first day, the subject conducted a training phase and a practice phase.
In the training phase, the three limbs controlled a single VH one by one using
either the hand/foot interfaces. A single target was shown on the screen and
one of three VH were used to reach the target. This phase was designed to help
the participants understand the mapping and control scheme. Each session
included 20 targets. The training was stopped when the hand-controlled VHs
reached 90% of the target and the foot controlled VH reach 80% of the targets.
After the training phase, the subjects were asked to control the three VHs
together and practice the trimanual task. Ten sessions of 200 trials (each
session including 20 trials) were conducted in this phase. Between sessions,
the subject are given 30 seconds to take a rest.

On the second day, the subjects conducted the test phase, which is same as the
practice, and the Reference phase, in which two subjects were randomly paired
to perform the same task in ten sessions: one operator used their natural
hands and their partner used their right foot to cooperatively perform the
task. Half of the subjects performed the test phase first and the other half
subjects completed the reference phase first. In the assessment phase, the
subject finally filled in two assessment questionnaires. We arranged the
reference phase on the second day to pursue a relatively fair comparison
between dyad and trimanual control modes as the tri-manipulation practice may
also improve bi-manual and foot operation.

In addition, to study the sensitivity of trimanual and dyad operation to a
dynamic environment (target sequence), we separated subjects into two groups
with a fixed or random ordering of targets. In the fixed group, 20 targets in
each session were shown in fixed order in all phases; while in random group,
the targets were shown in an unpredictable sequence. Eight of the 14
participants used the fixed target sequence and the six subjects applied the
random sequence with the same targets.

###  II-C Evaluation measures

Subject trial performance was evaluated based upon different quantitative
measurement types and additionally subjective measures from the questionnaire
responses.

####  II-C1 Measures of performance

  * •

Success rate defined as the ratio of the number of successful trials divided
by the total number of trials in each session. Success occured when the CoM
reached the target within a hold time that was more than 0.1s.

  * •

Efficiency ratio was calculated by taking the real travel distance of the CoM
and dividing by the straight/optimal distance to the target in successful
trials. In the optimal case, the efficiency ratio is equal to 1.

  * •

Operation time was the difference in time between the instant where the target
was shown on the screen to the instant in which the CoM reach the target. The
operation time is also calculated in the successful trials and normalized by
dividing the optimal distance to the target.

####  II-C2 Measure of coordination

The coordination level of every two hands was measured by the coordination
error, which is the sum of of the dynamic deviation of each elastic band. For
example, the elastic band connecting VH1 & 2, controlled by left and right
hands (L-R) is calculated through:

$\displaystyle
E=\frac{\sum_{2}^{N}{(L_{1}(n)-L_{1}(n-1))}}{\sum_{2}^{N}(P_{CoM1}(n)-P_{CoM1}(n-1)})$
(1)

where $L_{1}$ is the dynamic length of the elastic band derived from the
position of VH1 & 2, $P_{CoM1}$ is the position of the CoM of the bar 1,
$P_{CoM1}=(P_{VH1}+P_{VH2})/2$, $N$ is the number of recorded data point in
each session, $n$ = 2,3…$N$. The coordination error of elastic bands
controlled by left hand & foot (L-F), right hand& foot (R-F) are derived in
the same way.

####  II-C3 Subjective measures

Each participant was asked to fill a questionnaire after each control mode in
the test and reference phases (Fig. 5). This questionnaire provided a
qualitative evaluation of the efficiency, mental effort, control and
coordination. At the end of the experiment, the participants were required to
fill a comparative questionnaire, asking how 3-handed operation perform
compared to the dyad 2-handed/foot operation using 5-Point-Likert scale in
difficulty and preference.

Figure 3: Three-hand operation (3H) performance and coordination in practice
and test phases. (a) Success rate. (b) Efficiency ratio. (c) Operation time.
Coordination error of (d) left and right hands (L-R), (e) left hand and foot
(L-F), (f) right hand and foot (R-F). (P1, P2, P3 are the average of
measurements in sessions of 2-4, 5-7, 8-10 of the practice phase; T1, T2, T3
are the average of measurements in trials 2-4, 5-7, 8-10 of the test phase.
Asterisks denote significant effects at *p$<$0.05, ** p$<$0.01, *** p$<$0.001.

###  II-D Statistical analysis

A Shapiro-Wilk test was conducted to examine the distribution of the data. The
quantitative measurement data except success metric were found to be normally
distributed. The statistical analysis was then conducted in three steps.
First, the changes in the performance parameters of trimanual operation in the
practice and test phases were studied. The data for motion efficiency and
completion time were analyzed using one-way repeated measurements ANOVA.
Custom comparisons between single conditions were conducted using post-hoc
paired t-tests. The success rate (non-normally distributed) was evaluated
using non-parametric one-way repeated measurements ART ANOVA with Wilcoxon
signed-rank post-hoc tests. For coordination measure, two-way repeated
measurements ANOVA was employed that considered changes in coordination with
trials and differences between the limbs. Second, we analysed differences in
success, motion efficiency and operation time between trimanual and dyad
operations in the test and reference phases with two-way mixed ANOVA, the in-
between factor of target sequence was also inspected. For the coordination
measure a three-way mixed ANOVA was employed with an additional inter-limb
predictor. All p-values of post-hoc tests in the first and second steps were
adjusted with Holm-Bonferroni method to prevent type I error by multiple
comparisons. Lastly, the questionnaires used an ordinal scale, therefore, a
non-parametric repeated measures Friedman test was chosen for the analysis of
each item. For pairwise comparisons between single conditions, the Nemenyi
post-hoc test (which accounts for multiple comparisons) was employed.

Figure 4: Performance and coordination in test phase of three hands and dyad.
The result is plotted in average values of ten sessions. Asterisks denote
significant effects at *p$<$0.05, ** p$<$0.01, *** p$<$0.001.

##  III Results

###  III-A Learning of the tri-manipuation

We examined the changes in success, motion efficiency and operation time to
determine whether the participants improved their trimanual performance over
this time. We compared the first and last trials of the practice and test
phases as well as the first and last trials of the experiment. The task
success (Fig. 3a) significantly improved with a growing (practice) trial
number ($F(5,65)=3.3303,\,p=0.00971$): success at the beginning (P1) of the
practice phase was significantly lower than at the end (P3)
($Z=-2.6723,\,p=0.013$) as well as significantly lower as at the end of the
test phase (T3) ($Z=-2.3231,\,p=0.035$). However, no changes in success within
the test phase were detected ($Z=-0.86809,\,p=0.414$), so that the subjects
improved regarding success mostly in the practice phase.

We observed a similar significant tendency for motion efficiency
($F(5,65)=6.493,\,p<0.0001$). The participants improved mostly in the practice
phase ($t(65)=4.623,\,p<0.0001$ for comparison between P1 and P3), but not in
the test phase, where the efficiency was close to 1 during the entire phase
($t(65)=0.541,\,p=0.590$ for comparison between T1 and T3). Significant
improvement of the efficiency between the beginning and the end of the two
sessions was observed ($t(65)=4.756,\,p<0.0001$ for comparison between P1 and
T3).

The completion time used with the trimanual condition (Fig. 3c) also improved
with trials ($F(5,65)=4.255,\,p=0.002$). Compared to the first trials (P1),
the time was significantly reduced at the end of the practice phase (P3)
($t(65)=3.460,\,p=0.002$) as well as at the end of the test phase (T3)
($t(65)=3.884,\,p=0.001$). Again no improvement was observed within the test
phase ($t(65)=0.081,\,p=0.934$ for difference between T1 and T3).

A two-way repeated measurement ANOVA yielded a significant effect of trials
number ($F(5,221)=11.963,\,p<0.0001$), as well as limbs combination
($F(2,221)=41.132,\,p<0.0001$) on coordination error (see Fig. 3d-f). Since
interaction between both predictors was not significant, we analysed the
change in coordination with respect time over all limb combinations and the
differences between the limbs over all trials. Similar to the previous
metrics, coordination mostly improved in the practice phase
($t(221)=6.057,\,p<0.0001$ for comparison between P1 and P3) and then
stagnated in the test phase ($t(221)=1.280,\,p=0.202$ between T1 and T3).
Compared to the first trials (P1) the error became significantly smaller in
the last trials (T3) ($t(221)=6.538,\,p<0.0001$). Both conditions that
involved the foot showed higher coordination error than coordination between
the hands: $t(221)=7.072,\,p<0.0001$ for comparison between L-F and L-R,
$t(221)=-8.454,\,p<0.0001$ between L-R and R-F. No difference was found
between L-F and R-F groups ($t(221)=-1.382,\,p=0.168$).

###  III-B Three hands vs. dyad hands/foot control

We compared the two operation modes of trimanual and dyad control of two
operators using the average result in the test and reference phases. As shown
in Fig. 4a, no differences were found between the different conditions in
terms of the task success rate ($F(1,12)=1.918,\,p=0.191$). However, the
motion efficiency was closer to 1 in trimanual group, which means higher
efficiency, compared to the dyad group conducting the task with a partner
(Fig. 4b, $F(1,12)=6.4898,\,p=0.026$). In contrast, the dyad control completed
the task significantly faster than solo tri-manipulation controlling three
limbs (Fig. 4c, $F(1,12)=5.2432,\,p=0.041$).

Trimanual and dyad controls did not differ significantly in coordination
($F(1,12)=1.8643,\,p=0.197$). The combination of different limbs resulted in
significant coordination error contrasts ($F(1.41,16.93)=11.788,\,p=0.001$):
movements with two hands were more coordinated than both other conditions
($t(12)=-4.987,\,p=0.001$ for comparison between L-R and L-F,
$t(12)=-3.336,\,p=0.012$ between L-R and R-F), no significant differences
between the conditions involving the foot were found
($t(12)=-0.189,\,p=0.854$).

###  III-C Sensitivity to target sequence

In the same analysis with the previous section we analysed the effect of the
target sequence. Using a random or fixed sequence has no impact on the success
($F(1,12)=0.0701,\,p=0.796$), but significantly influenced the motion
efficiency ($F(1,12)=13.1419,\,p=0.003$) and has a tendency to have an impact
on completion time ($F(1,12)=3.8793,\,p=0.072$). The Target sequence also
significantly influenced the coordination error of participants
($F(1,12)=22.698,\,p<0.001$). The fixed target sequence could be achieved by
subjects faster, more efficiently and coordinated. Importantly, no interaction
effect between trimanual and cooperation and target sequence was found for any
of metrics.

###  III-D Subjective assessment

The results of the first questionnaire are shown in Figs. 5a-d. No significant
difference was found for the time to reach the target perception
($\chi^{2}(2)\,=\,2.6667,\,p\,=\,0.264$). The medians for each of the three
conditions were equal to 2, which indicates that the time was sufficient to
achieve the task with three and two hands as well as with the foot. The
conditions were perceived differently regarding required mental effort
($\chi^{2}(2)\,=\,13.40,\,p\,=\,0.001$). In the trimanual condition subjects
reported significantly higher mental effort than when performing the task with
two hands together with a partner ($p\,=\,0.029$). However, no difference
regarding the perceived effort was found between the task execution with a
foot and using three or two hands ($p\,=\,0.029$).

In terms of the level of control felt for the virtual limbs, a Friedman test
showed significant differences between the groups
($\chi^{2}(2)\,=\,6.3429,\,p\,=\,0.042$). However, Nemenyi post-hoc test did
not reveal any significant pairwise contrasts between conditions (all
$p\,>\,0.1$). Significant differences in perceived performance were detected
($\chi^{2}(2)\,=\,7.85,\,p\,=\,0.0197$): by interaction with three hands
subjects rated the performance lower than when achieving the task with two
hands ($p\,=\,0.048$). Other differences were not found to be significant
(both $p\,>\,0.3$).

The user assessment of difficulty and preference are shown in Figs. 5e,f. A
Friedman test revealed significant differences for the difficulty
($\chi^{2}(2)\,=\,14.105,\,p\,<\,0.001$): the trimanual condition was found
more difficult ($p\,=\,0.007$) and has a tendency to seem more difficult than
control of the foot, but this comparison was not significant ($p\,=\,0.094$).
However, a difference between the interactive conditions was not found
($p\,=\,0.612$). The conditions were also different in participants’
preferences ($\chi^{2}(2)\,=\,11.261,\,p\,=\,0.004$). People preferred more to
achieve the task with a partner, interacting with two hands than completing
the task alone ($p\,=\,0.010$). While interacting with a partner, subjects
tend to prefer to control two hands instead of the foot ($p\,=\,0.076$), but
this comparison was not significant.

Figure 5: Assessment of user experience. a-d: Histograms of assessment, where
questions were answered after each section. (a) Did the subject feel they had
sufficient time to complete the task, -2/+2 corresponds to
insufficient/sufficient time. (b) How much mental load did the subject feel
during task operation, -2/+2 corresponds to more/less mental load. (c) Agency
question about whether the subject felt in control of the virtual hands
(-2/+2: strongly dis/agree). (d) Did the subject feel that they were in
control of the coordination of the three limbs (-2/+2: very poor/good). e,f:
Final comparison of the three control modes according to (e) “difficulty” and
(f) “preference”, the shade of the color present the answers of from
difficult/less preferred (light color) to easy/most preferred (deep color).

##  IV Discussion

This study explored the human capability to trimanipulate in a coordination
task. The experiment was conducted with a platform including two hand
interfaces, one foot interface and a virtual reality scenario. The subjects
were in general able to successfully perform the task, where after the
trimanual group’s learning that took place during the practice phases, there
was no clear difference was observed between the trimanual and dyadic
conditions in the test phase. This suggests that trimanipulation can be
performed successful by a single subject in coupled motions.

The motion characteristics of the subjects showed a similar trend where after
the initial learning similar performance was observed between the dyadic and
trimanual conditions in the test phase. There were however two points of
difference: the trimanual condition produced more efficient motion, while the
dyads were able to complete the task quicker. This appears to reflect the
trade-off present between the two strategies, in which the solo subject is
able completely plan all of its motion allowing for more efficient overall
strategies, while the dyad benefits from parallelisation of the planning which
can lead to fast planning and performance.

The rankings show a clear preference for working in a dyad and the belief that
trimanual operation was inherently more difficult. This may be reflective of
the dyad being more familiar and as suggested by the questionnare requiring
less mental effort, or it could suggest a strong preference to the cooperation
and parallelisation that the condition offers. Despite these results, it is
interesting to find that the participants did not feel that the trimanual
hands-foot control requires more physical effort than the dyad. Furthermore,
the subjects appears to already feel they were capable of controlling the foot
and had sufficient time for its operation. These results suggest that the
difference in mental is specifically associated with the need to plan for the
third limb. It is unclear if further learning resulting in a more clear body
representation of the foot being the third hand could help make such planning
more natural or if this is a suggestion of a clear difference between the
conditions.

Compared to the results of [15], which considered the same coupled motion
task, the findings of this study suggests that with additional sessions to
account for learning to perform trimanual actions, subject can prove similarly
capable to a dyad. Throughout the practice phase learning was clearly observed
in all metrics. For some metrics such as the success rate and motion
efficiency, this learning effect appears to have hit a clear ceiling by the
test phase. However, for other metrics including the time to completion and
coordination, the results show that even in the test phase there is continuing
evidence that learning is taking place. It is worth noting that the metrics in
which the trimanual condition gives as good as or superior performance to the
dyad corresponds to those that show an apparent ceiling effect. This suggests
that future work should investigate the effect of additional sessions to
account for any potential additional learning.

While the results suggest potential for trimanual performance to outperform
dyads, only an abstract version of a task requiring physical coupling has been
considered. Future work will therefore focus on evaluating if such results are
also possible in the context of other kinds of potential supernumerary tasks
or with more realistic case studies matching the presented scenario.

## Acknowledgment

We thank the subjects for joining the experiment. The experiment was approved
by the Institutional Review Board of Nanyang Technological University
(IRB-2018-05-051).

## References

  * [1] Z. Wang, H. Lam, B. Xiao, Z. Chen, B. Liang, and T. Zhang, “Event-triggered prescribed-time fuzzy control for space teleoperation systems subject to multiple constraints and uncertainties,” _IEEE Transactions on Fuzzy Systems_ , pp. 1–1, 2020.
  * [2] Z. Wang, B. Liang, Y. Sun, and T. Zhang, “Adaptive fault-tolerant prescribed-time control for teleoperation systems with position error constraints,” _IEEE Transactions on Industrial Informatics_ , vol. 16, no. 7, pp. 4889–4899, 2020.
  * [3] M. Nurok, T. M. Sundt, and A. Frankel, “Teamwork and communication in the operating room: Relationship to discrete outcomes and research challenges,” _Anesthesiology Clinics_ , vol. 29, pp. 1–11, 2011.
  * [4] S. S. Kommu, P. Rimington, C. Anderson, and A. Rané, “Initial experience with the endoassist camera-holding robot in laparoscopic urological surgery,” _Journal of Robotic Surgery_ , vol. 1, pp. 133–137, 2007.
  * [5] D. Johansen, C. Cipriani, D. B. Popović, and L. N. S. A. Struijk, “Control of a robotic hand using a tongue control system—a prosthesis application,” _IEEE Transactions on Biomedical Engineering_ , vol. 63, no. 7, pp. 1368–1376, 2016.
  * [6] Y. Huang, E. Burdet, L. Cao, P. T. Phan, A. M. H. Tiong, P. Zheng, and S. J. Phee, “Performance evaluation of a foot interface to operate a robot arm,” _IEEE Robotics and Automation Letters_ , vol. 4, no. 4, pp. 3302–3309, 2019.
  * [7] D. P. Noonan, G. P. Mylonas, J. Shang, C. J. Payne, A. Darzi, and G. Yang, “Gaze contingent control for an articulated mechatronic laparoscope,” in _2010 3rd IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics_ , 2010, pp. 759–764.
  * [8] G. Yulun Wang and S. N. Darrin Uecker, “Speech interface for an automated endoscopic system,” 2002, US Patent 6463361 B1.
  * [9] J. Cunningham, A. Hapsari, P. Guilleminot, A. Shafti, and A. Faisal, “The supernumerary robotic 3 rd thumb for skilled music tasks,” 08 2018, pp. 665–670.
  * [10] M. Y. Saraiji, T. Sasaki, K. Kunze, K. Minamizawa, and M. Inami, “Metaarms: Body remapping using feet-controlled artificial arms,” in _User Interface Software and Technology_ , 2018, pp. 65–74.
  * [11] J. Hernández, W. Amanhoud, A. Haget, H. Bleuler, A. Billard, and M. Bouri, “Four-arm manipulation via feet interfaces,” 09 2019.
  * [12] E. Abdi, E. Burdet, M. Bouri, and H. Bleuler, “Control of a supernumerary robotic hand by foot: An experimental study in virtual reality,” _PLoS ONE_ , vol. 10, p. e0134501, 2015.
  * [13] E. Abdi, E. Burdet, M. Bouri, S. Himidan, and H. Bleuler, “In a demanding task, three-handed manipulation is preferred to two-handed manipulation,” _Scientific Reports_ , vol. 6, p. 21758, 2016.
  * [14] Y. Huang, J. Eden, L. Cao, E. Burdet, and S. J. Phee, “Tri-manipulation: An evaluation of human performance in 3-handed teleoperation,” _IEEE Transactions on Medical Robotics and Bionics_ , vol. 2, no. 4, pp. 545–548, 2020.
  * [15] A. Noccaro, J. Eden, G. Di Pino, D. Formica, and E. Burdet, “Human performance in three-hands tasks,” 2021. doi: 10.21203/rs.3.rs-209540/v1, preprint available at research square doi: 10.21203/rs.3.rs-209540/v1.
  * [16] Y. Huang, E. Burdet, L. Cao, P. T. Phan, A. H. T. Meng, and L. Phee, “A subject-specific four-degree-of-freedom foot interface to control a surgical robot,” _IEEE/ASME Transactions on Mechatronics_ , vol. 25, no. 2, pp. 951–63, 2020.
  * [17] N. van Melick, B. M. Meddeler, T. J. Hoogeboom, M. W. G. Nijhuis-van der Sanden, and R. E. H. van Cingel, “How to determine leg dominance: The agreement between self-reported and observed performance in healthy adults,” _PLoS ONE_ , vol. 12, p. e0189876, 2017.