The effect of skill level matching in dyadic interaction on learning of a tracing task

Kager, Simone; Hussain, Asif; Cherpin, Adele; Takagi, Atsushi; Endo, Satoshi; Burdet, Etienne; Hirche, Sandra; Ang, Marcelo H.; Campolo, Domenico

doi:10.1109/icorr.2019.8779485

Cited by 13 publications

(12 citation statements)

References 29 publications

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“…Reducing a participant's movement errors while they learn a new motor skill using robot-generated haptic assistance rarely transferred into improved subsequent individual performance compared to participants who received no haptic assistance [12][13][14][15][16] . Similarly, several studies on haptic human-human interaction consistently showed that tracking errors are significantly smaller during haptic interaction compared to performing the tracking task alone, particularly if you interact with a partner who is better than you 3,[5][6][7]9,10 . Combining these observations, we would expect little to no benefit of haptic human-human interaction on individual visuomotor adaptation.…”

mentioning

confidence: 85%

“…Van der Wel et al 8 reported that haptically interacting partners learned a novel coordination task (balancing a stick) just as quickly as individuals performing the task alone. Using a tracking task and the same visuomotor perturbation as Ganesh et al 3 , Kager et al 9 found no significant effect of haptic interaction on final individual motor performance. However, their study has a few important differences to Ganesh et al 3 : their tracking task was less challenging, they used a different haptic interaction paradigm and they only tested a limited number of participants.…”

Section: Introductionmentioning

confidence: 93%

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Haptic human–human interaction does not improve individual visuomotor adaptation

Beckers

Asseldonk

Kooij

2020

Sci Rep

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Haptic interaction between two humans, for example, a physiotherapist assisting a patient regaining the ability to grasp a cup, likely facilitates motor skill acquisition. Haptic human–human interaction has been shown to enhance individual performance improvement in a tracking task with a visuomotor rotation perturbation. These results are remarkable given that haptically assisting or guiding an individual rarely benefits their individual improvement when the assistance is removed. We, therefore, replicated a study that reported that haptic interaction between humans was beneficial for individual improvement for tracking a target in a visuomotor rotation perturbation. In addition, we tested the effect of more interaction time and a stronger haptic coupling between the partners on individual improvement in the same task. We found no benefits of haptic interaction on individual improvement compared to individuals who practised the task alone, independent of interaction time or interaction strength.

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mentioning

confidence: 85%

Section: Introductionmentioning

confidence: 93%

Haptic human–human interaction does not improve individual visuomotor adaptation

Beckers

Asseldonk

Kooij

2020

Sci Rep

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“…The unique features of H-Man are its intrinsic safety, its ease of control, owing to its homogenous workspace, and the fact that it is low-cost, compact and lightweight (about 7 kg). It was employed in post-stroke neurorehabilitation therapy, assessment of sensorimotor functions ( 49 , 51 , 53 ), and for human motor control experiments with healthy participants ( 45 , 46 , 48 , 54 ).…”

Section: Methodsmentioning

confidence: 99%

“…The participants who underwent the combinatory training scheme spent one third of the total therapy time in a 1:1 physical training with a therapist. For the rest of the training, the participants used the robot H-Man, a two-degree of freedom and compact upper limb rehabilitation and assessment device (44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54), under the minimal supervision of a therapist. One major aspect of this training scheme is that both of the groups received the same amount of training sessions, at a similar frequency and for the same amount of time, i.e., three therapy sessions per week over a span of 6 weeks.…”

Section: Introductionmentioning

confidence: 99%

Robotic Assisted Upper Limb Training Post Stroke: A Randomized Control Trial Using Combinatory Approach Toward Reducing Workforce Demands

et al. 2021

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Post stroke upper limb rehabilitation is a challenging problem with poor outcomes as 40% of survivors have functionally useless upper limbs. Robot-aided therapy (RAT) is a potential method to alleviate the effort of intensive, task-specific, repetitive upper limb exercises for both patients and therapists. The present study aims to investigate how a time matched combinatory training scheme that incorporates conventional and RAT, using H-Man, compares with conventional training toward reducing workforce demands. In a randomized control trial (NCT02188628, www.clinicaltrials.gov), 44 subacute to chronic stroke survivors with first-ever clinical stroke and predominant arm motor function deficits were recruited and randomized into two groups of 22 subjects: Robotic Therapy (RT) and Conventional Therapy (CT). Both groups received 18 sessions of 90 min; three sessions per week over 6 weeks. In each session, participants of the CT group received 90 min of 1:1 therapist-supervised conventional therapy while participants of the RT group underwent combinatory training which consisted of 60 min of minimally-supervised H-Man therapy followed by 30 min of conventional therapy. The clinical outcomes [Fugl-Meyer (FMA), Action Research Arm Test and, Grip Strength] and the quantitative measures (smoothness, time efficiency, and task error, derived from two robotic assessment tasks) were independently evaluated prior to therapy intervention (week 0), at mid-training (week 3), at the end of training (week 6), and post therapy (week 12 and 24). Significant differences within group were observed at the end of training for all clinical scales compared with baseline [mean and standard deviation of FMA score changes between baseline and week 6; RT: Δ4.41 (3.46) and CT: Δ3.0 (4.0); p < 0.01]. FMA gains were retained 18 weeks post-training [week 24; RT: Δ5.38 (4.67) and week 24 CT: Δ4.50 (5.35); p < 0.01]. The RT group clinical scores improved similarly when compared to CT group with no significant inter-group at all time points although the conventional therapy time was reduced to one third in RT group. There were no training-related adverse side effects. In conclusion, time matched combinatory training incorporating H-Man RAT produced similar outcomes compared to conventional therapy alone. Hence, this study supports a combinatory approach to improve motor function in post-stroke arm paresis.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT02188628.

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“…In this regard, the leaderfollower role allocation presented in this study can as well be beneficial when incorporated in the design of systems that aid in human skill learning for either human or human-robot dyads. Studies by Kager et al in [34] and Avila Mirales et al in [35] showed that practising with a peer was more advantageous to the subject than with an expert. Knowing this, the latter study suggested that the results show the possibility of teaching an expert user to be an expert teacher as the expert teacher must learn how to support, instead of explicitly leading the naive user, in order to leave room for the naive user to learn.…”

Section: Discussionmentioning

confidence: 99%

Leader–Follower Role Allocation for Physical Collaboration in Human Dyads

Leskovar

Čamernik²,

Petrič

2021

Applied Sciences

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People often find themselves in situations where collaboration with others is necessary to accomplish a particular task. In such cases, a leader–follower relationship is established to coordinate a plan to achieve a common goal. This is usually accomplished through verbal communication. However, what happens when verbal communication is not possible? In this study, we observe the dynamics of a leader–follower relationship in human dyads during collaborative tasks where there is no verbal communication between partners. Using two robotic arms, we designed a collaborative experimental task in which subjects perform the task individually or coupled together through a virtual model. The results show that human partners fall into the leader–follower dynamics even when they cannot communicate verbally. We demonstrate this in two steps. First, we study how each subject in a collaboration influences task performance, and second, we evaluate whether both partners influence it equally or not using our proposed sorting method to objectively identify a leader. We also study the leader–follower dynamics by analysing the task performance of partners during their individual sessions to predict the role distribution in a dyad. Based on the results of our prediction method, we conclude that the higher-performing individual performance will assume the role of a leader in collaboration.

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The effect of skill level matching in dyadic interaction on learning of a tracing task

Cited by 13 publications

References 29 publications

Haptic human–human interaction does not improve individual visuomotor adaptation

Haptic human–human interaction does not improve individual visuomotor adaptation

Robotic Assisted Upper Limb Training Post Stroke: A Randomized Control Trial Using Combinatory Approach Toward Reducing Workforce Demands

Leader–Follower Role Allocation for Physical Collaboration in Human Dyads

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