Small forces that differ with prior motor experience can communicate movement goals during human-human physical interaction

Low-force human-human hand interactions induce gait changes through sensorimotor engagement instead of direct mechanical effects

Physical human-robot interactions (pHRI) often provide mechanical force and power to aid walking without requiring voluntary effort from the human. Alternatively, principles of physical human-human interactions (pHHI) can inspire pHRI that aids walking by engaging human sensorimotor processes. We hypothesize that low-force pHHI can intuitively induce a person to alter their walking through haptic communication. In our experiment, an expert partner dancer influenced novice participants to alter step frequency solely through hand interactions. Without prior instruction, training, or knowledge of the expert's goal, novices decreased step frequency 29% and increased step frequency 18% based on low forces (< 20 N) at the hand. Power transfer at the hands was 3-700 × smaller than what is necessary to propel locomotion, suggesting that hand interactions did not mechanically constrain the novice's gait. Instead, the sign/direction of hand forces and power may communicate information about how to alter walking. Finally, the expert modulated her arm effective dynamics to match that of each novice, suggesting a bidirectional haptic communication strategy for pHRI that adapts to the human. Our results provide a framework for developing pHRI at the hand that may be applicable to assistive technology and physical rehabilitation, human-robot manufacturing, physical education, and recreation.

Human-robot planar co-manipulation of extended objects: data-driven models and control from human-human dyads

Human teams are able to easily perform collaborative manipulation tasks. However, simultaneously manipulating a large extended object for a robot and human is a difficult task due to the inherent ambiguity in the desired motion. Our approach in this paper is to leverage data from human-human dyad experiments to determine motion intent for a physical human-robot co-manipulation task. We do this by showing that the human-human dyad data exhibits distinct torque triggers for a lateral movement. As an alternative intent estimation method, we also develop a deep neural network based on motion data from human-human trials to predict future trajectories based on past object motion. We then show how force and motion data can be used to determine robot control in a human-robot dyad. Finally, we compare human-human dyad performance to the performance of two controllers that we developed for human-robot co-manipulation. We evaluate these controllers in three-degree-of-freedom planar motion where determining if the task involves rotation or translation is ambiguous.

Granger Geweke Causality reveals information exchange during physical interaction is modulated by task difficulty

The haptic sense is an important mode of communication during physical interactions, and it is known to enable humans to estimate key features of their partner's behavior. It is proposed that such estimations are based upon the exchange of information mediated by the interaction forces, resulting in role distribution and coordination between partners. In the present study, we examined whether the information exchange is functionally modified to adapt to the task, or whether it is a fixed process, leaving the adaptation to individual's behaviors. We analyzed the forces during an empirical dyadic interaction task using Granger-Geweke causality analysis, which allowed us to quantify the causal influence of each individual's forces on their partner's. The dynamics of relative phase were also examined. We observed an increase of inter-partner influence with an increase in the spatial accuracy required by the task, demonstrating an adaptation of information flow to the task. This increase of exchange with the spatial accuracy constraint was accompanied by an increase of errors and of the variability of the relative phase between forces. The influence was dominated by participants in a specific role, showing a clear role division as well as task division between the dyad partners. Moreover, the influence occurred in the [2.15-7] Hz frequency band, demonstrating its importance as a frequency band of interest during cooperation involving haptic interaction. Several interpretations are introduced, ranging from sub-division of motion control to phase-amplitude coupling.

Discovering individual-specific gait signatures from data-driven models of neuromechanical dynamics

Locomotion results from the interactions of highly nonlinear neural and biomechanical dynamics. Accordingly, understanding gait dynamics across behavioral conditions and individuals based on detailed modeling of the underlying neuromechanical system has proven difficult. Here, we develop a data-driven and generative modeling approach that recapitulates the dynamical features of gait behaviors to enable more holistic and interpretable characterizations and comparisons of gait dynamics. Specifically, gait dynamics of multiple individuals are predicted by a dynamical model that defines a common, low-dimensional, latent space to compare group and individual differences. We find that highly individualized dynamics-i.e., gait signatures-for healthy older adults and stroke survivors during treadmill walking are conserved across gait speed. Gait signatures further reveal individual differences in gait dynamics, even in individuals with similar functional deficits. Moreover, components of gait signatures can be biomechanically interpreted and manipulated to reveal their relationships to observed spatiotemporal joint coordination patterns. Lastly, the gait dynamics model can predict the time evolution of joint coordination based on an initial static posture. Our gait signatures framework thus provides a generalizable, holistic method for characterizing and predicting cyclic, dynamical motor behavior that may generalize across species, pathologies, and gait perturbations.

Learning acquisition of consistent leader-follower relationships depends on implicit haptic interactions

Are leaders made or born? Leader-follower roles have been well characterized in social science, but they remain somewhat obscure in sensory-motor coordination. Furthermore, it is unknown how and why leader-follower relationships are acquired, including innate versus acquired controversies. We developed a novel asymmetrical coordination task in which two participants (dyad) need to collaborate in transporting a simulated beam while maintaining its horizontal attitude. This experimental paradigm was implemented by twin robotic manipulanda, simulated beam dynamics, haptic interactions, and a projection screen. Clear leader-follower relationships were learned only when strong haptic feedback was introduced. This phenomenon occurred despite participants not being informed that they were interacting with each other and the large number of equally-valid alternative dyadic coordination strategies. We demonstrate the emergence of consistent leader-follower relationships in sensory-motor coordination, and further show that haptic interaction is essential for dyadic co-adaptation. These results provide insights into neural mechanisms responsible for the formation of leader-follower relationships in our society.

Dance-Themed National Biomechanics Day Community Engagement to Inspire our Future STEAM Leaders

Community engagement experiences through National Biomechanics Day (NBD) that focused on dance biomechanics have provided excellent Science, Technology, Engineering, Art, and Math (STEAM) learning opportunities. During these experiences, bidirectional learning has been enjoyed by the biomechanists hosting the events and the kindergarten through 12th grade student attendees. In this article, perspectives are shared about dance biomechanics and hosting dance-themed NBD events. Importantly, examples of high school student feedback are provided that point towards the positive impact of NBD by inviting future generations to advance the field of biomechanics.

Humans modulate arm stiffness to facilitate motor communication during overground physical human-robot interaction

Humans can physically interact with other humans adeptly. Some overground interaction tasks, such as guiding a partner across a room, occur without visual and verbal communication, which suggests that the information exchanges occur through sensing movements and forces. To understand the process of motor communication during overground physical interaction, we hypothesized that humans modulate the mechanical properties of their arms for increased awareness and sensitivity to ongoing interaction. For this, we used an overground interactive robot to guide a human partner across one of three randomly chosen paths while occasionally providing force perturbations to measure the arm stiffness. We observed that the arm stiffness was lower at instants when the robot's upcoming trajectory was unknown compared to instants when it was predicable - the first evidence of arm stiffness modulation for better motor communication during overground physical interaction.

Interacting humans use forces in specific frequencies to exchange information by touch

Object-mediated joint action is believed to be enabled by implicit information exchange between interacting individuals using subtle haptic signals within their interaction forces. The characteristics of these haptic signals have, however, remained unclear. Here we analyzed the interaction forces during an empirical dyadic interaction task using Granger–Geweke causality analysis, which allowed us to quantify the causal influence of each individual’s forces on their partner’s. We observed that the inter-partner influence was not the same at every frequency. Specifically, in the frequency band of [2.15–7] Hz, we observed inter-partner differences of causal influence that were invariant of the movement frequencies in the task and present only when information exchange was indispensable for task performance. Moreover, the inter-partner difference in this frequency band was observed to be correlated with the task performance by the dyad. Our results suggest that forces in the [2.15–7] Hz band constitute task related information exchange between individuals during physical interactions.

Walking paths during collaborative carriages do not follow the simple rules observed in the locomotion of single walking subjects

Some works have already studied human trajectories during spontaneous locomotion. However, this topic has not been thoroughly studied in the context of human-human interactions, especially during collaborative carriage tasks. Thus, this manuscript aims to provide a broad analysis of the kinematics of two subjects carrying a table. In the present study, 20 pairs of subjects moved a table to 9 different goal positions distant of 2.7–5.4 m. This was performed with only one or both subjects knowing the target location. The analysis of the collected data demonstrated that there is no shared strategy implemented by all the pairs to move the table around. We observed a great variability in the pairs’ behaviours. Even the same pair can implement various strategies to move a table to the same goal position. Moreover, a model of the trajectories adopted by collaborating pairs was proposed and optimized with an inverse optimal control scheme. Even if it produced consistent results, due to the great variability which origins were not elucidated, it was not possible to accurately simulate the average trajectories nor the individual ones. Thus, the approach that was shown to be efficient to simulate single walking subjects failed to model the behaviour of collaborating pairs.

Study of Kinesthetic Negotiation Ability in Lightweight Comanipulative Decision-making Tasks: Design and Study of a Virtual Partner based on Human-human Interaction Observation

This article presents the results of an experiment on physical Human-Human Interaction (pHHI), where human dyads cooperate on a one-dimensional comanipulative task in a novel lightweight teleoperation setup. The results of this experiment show that humans are able to handle asymmetrical information about the task and solve conflicts using only the kinesthetic channel. Data from the pHHI experiment is used to design a virtual partner that can perform the task alongside a human. The virtual partner behavior is based on the observation that initiative is highly correlated to decision-making in our pHHI negotiation scenario. The virtual agent is then evaluated in a physical Human-Robot Interaction (pHRI) experiment. The results of the second experiment show that the virtual partner is able to perform the task without compromising the performances of the dyad and that a similar role distribution is observed in human-human and human-robot dyads. Moreover, the knowledge of the partner’s nature does not seem to influence the performances. The results obtained with the virtual partner are encouraging and could be used to design kinesthetic negotiation algorithms in pHRI settings.

The main contributions of this article are: (1) supporting evidence of the possibility for humans to use the kinesthetic channel as mean of negotiation during physical Human-Human Interaction in the lightest known impedance negotiation tasks (with no virtual mass involved), (2) highlighting of the correlation between initiative and dyadic decision making, (3) design of a simple yet efficient virtual partner algorithm capable of realistic physical Human-Robot Interaction in the one-dimension tracking task used in the experimental setup. This design combines minimum jerk trajectory, switching role ability, decision criteria, and statistical parameters that are detailed in this article.

Humans utilize sensory evidence of others' intended action to make online decisions

We often acquire sensory information from another person's actions to make decisions on how to move, such as when walking through a crowded hallway. Past interactive decision-making research has focused on cognitive tasks that did not allow for sensory information exchange between humans prior to a decision. Here, we test the idea that humans accumulate sensory evidence of another person's intended action to decide their own movement. In a competitive sensorimotor task, we show that humans exploit time to accumulate sensory evidence of another's intended action and utilize this information to decide how to move. We captured this continuous interactive decision-making behaviour with a drift-diffusion model. Surprisingly, aligned with a 'paralysis-by-analysis' phenomenon, we found that humans often waited too long to accumulate sensory evidence and failed to make a decision. Understanding how humans engage in interactive and online decision-making has broad implications that spans sociology, athletics, interactive technology, and economics.

Robotic Light Touch Assists Human Balance Control During Maximum Forward Reaching

OBJECTIVE

We investigated how light interpersonal touch (IPT) provided by a robotic system supports human individuals performing a challenging balance task compared to IPT provided by a human partner.

BACKGROUND

IPT augments the control of body balance in contact receivers without a provision of mechanical body weight support. The nature of the processes governing the social haptic interaction, whether they are predominantly reactive or predictive, is uncertain.

METHOD

Ten healthy adult individuals performed maximum forward reaching (MFR) without visual feedback while standing upright. We evaluated their control of reaching behavior and of body balance during IPT provided by either another human individual or by a robotic system in two alternative control modes (reactive vs. predictive).

RESULTS

Reaching amplitude was not altered by any condition but all IPT conditions showed reduced body sway in the MFR end-state. Changes in reaching behavior under robotic IPT conditions, such as lower speed and straighter direction, were linked to reduced body sway. An Index of Performance expressed a potential trade-off between speed and accuracy with lower bitrate in the IPT conditions.

CONCLUSION

The robotic IPT system was as supportive as human IPT. Robotic IPT seemed to afford more specific adjustments in the human contact receiver, such as trading reduced speed for increased accuracy, to meet the intrinsic demands and constraints of the robotic system or the demands of the social context when in contact with a human contact provider.

Inter-personal motor interaction is facilitated by hand pairing

The extent to which hand dominance may influence how each agent contributes to inter-personal coordination remains unknown. In the present study, right-handed human participants performed object balancing tasks either in dyadic conditions with each agent using one hand (left or right), or in bimanual conditions where each agent performed the task individually with both hands. We found that object load was shared between two hands more asymmetrically in dyadic than single-agent conditions. However, hand dominance did not influence how two hands shared the object load. In contrast, hand dominance was a major factor in modulating hand vertical movement speed. Furthermore, the magnitude of internal force produced by two hands against each other correlated with the synchrony between the two hands' movement in dyads. This finding supports the important role of internal force in haptic communication. Importantly, both internal force and movement synchrony were affected by hand dominance of the paired participants. Overall, these results demonstrate, for the first time, that pairing of one dominant and one non-dominant hand may promote asymmetrical roles within a dyad during joint physical interactions. This appears to enable the agent using the dominant hand to actively maintain effective haptic communication and task performance.

Human-Human Hand Interactions Aid Balance During Walking by Haptic Communication

Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x 3.7 m long) and the other person walked overground by their side. We compare balance performance during partnered vs. solo beam-walking to examine the effects of haptic interaction, and we compare hand interaction mechanics during partnered beam-walking vs. overground walking to examine how the interaction aided balance. While holding the hand of a partner, participants were able to walk further on the beam without falling, reduce lateral sway, and decrease angular momentum in the frontal plane. We measured small hand force magnitudes (mean of 2.2 N laterally and 3.4 N vertically) that created opposing torque components about the beam axis and calculated the interaction torque, the overlapping opposing torque that does not contribute to motion of the beam-walker’s body. We found higher interaction torque magnitudes during partnered beam-walking vs. partnered overground walking, and correlation between interaction torque magnitude and reductions in lateral sway. To gain insight into feasible controller designs to emulate human-human physical interactions for aiding walking balance, we modeled the relationship between each torque component and motion of the beam-walker’s body as a mass-spring-damper system. Our model results show opposite types of mechanical elements (active vs. passive) for the two torque components. Our results demonstrate that hand interactions aid balance during partnered beam-walking by creating opposing torques that primarily serve haptic communication, and our model of the torques suggest control parameters for implementing human-human balance aid in human-robot interactions.

Sensing small interaction forces through proprioception

Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human-robot interaction (pHRI). In physical human-human interaction (pHHI), small interaction forces are known to convey their intent between the partners for effective motor communication. The aim of this work is to investigate what affects the human's sensitivity to the externally applied interaction forces. The hypothesis is that one way the small interaction forces are sensed is through the movement of the arm and the resulting proprioceptive signals. A pHRI setup was used to provide small interaction forces to the hand of seated participants in one of four directions, while the participants were asked to identify the direction of the push while blindfolded. The result shows that participants' ability to correctly report the direction of the interaction force was lower with low interaction force as well as with high muscle contraction. The sensitivity to the interaction force direction increased with the radial displacement of the participant's hand from the initial position: the further they moved the more correct their responses were. It was also observed that the estimated stiffness of the arm varies with the level of muscle contraction and robot interaction force.

Factors affecting the sensitivity to small interaction forces in humans. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:6066-6069. [PMID: 34892500 DOI: 10.1109/embc46164.2021.9629751]

Effective physical human-robot interaction (pHRI) depends on how humans can communicate their intentions for movement with others. While it is speculated that small interaction forces contain significant information to convey the specific movement intention of physical human-human interaction (pHHI), the underlying mechanism for humans to infer intention from such small forces is largely unknown. The hypothesis in this work is that the sensitivity to a small interaction force applied at the hand is affected by the movement of the arm that is affected by the arm stiffness. For this, a haptic robot was used to provide the endpoint interaction forces to the arm of seated human participants. They were asked to determine one of the four directions of the applied robot interaction force without visual feedback. Variations of levels of interaction force as well as arm muscle contraction were applied. The results imply that human's ability to identify and respond to the correct direction of small interaction forces was lower when the alignment of human arm movement with respect to the force direction was higher. In addition, the sensitivity to the direction of the small interaction force was high when the arm stiffness was low. It is also speculated that humans lower their arm stiffness to be more sensitive to smaller interaction forces. These results will help develop human-like pHRI systems for various applications.

The Importance of Being in Touch

This paper describes a series of studies resulting from the finding that when free floating in weightless conditions with eyes closed, all sense of one's spatial orientation with respect to the aircraft can be lost. But, a touch of the hand to the enclosure restores the sense of spatial anchoring within the environment. This observation led to the exploration of how light touch of the hand can stabilize postural control on Earth even in individuals lacking vestibular function, and can override the effect of otherwise destabilizing tonic vibration reflexes in leg muscles. Such haptic stabilization appears to represent a long loop cortical reflex with contact cues at the hand phase leading EMG activity in leg muscles, which change the center of pressure at the feet to counteract body sway. Experiments on dynamic control of balance in a device programmed to exhibit inverted pendulum behavior about different axes and planes of rotation revealed that the direction of gravity not the direction of balance influences the perceived upright. Active control does not improve the accuracy of indicating the upright vs. passive exposure. In the absence of position dependent gravity shear forces on the otolith organs and body surface, drifting and loss of control soon result and subjects are unaware of their ongoing spatial position. There is a failure of dynamic path integration of the semicircular canal signals, such as occurs in weightless conditions.

Trends in Haptic Communication of Human-Human Dyads: Toward Natural Human-Robot Co-manipulation

In this paper, we analyze and report on observable trends in human-human dyads performing collaborative manipulation (co-manipulation) tasks with an extended object (object with significant length). We present a detailed analysis relating trends in interaction forces and torques with other metrics and propose that these trends could provide a way of improving communication and efficiency for human-robot dyads. We find that the motion of the co-manipulated object has a measurable oscillatory component. We confirm that haptic feedback alone represents a sufficient communication channel for co-manipulation tasks, however we find that the loss of visual and auditory channels has a significant effect on interaction torque and velocity. The main objective of this paper is to lay the essential groundwork in defining principles of co-manipulation between human dyads. We propose that these principles could enable effective and intuitive human-robot collaborative manipulation in future co-manipulation research.

Haptic human-human interaction does not improve individual visuomotor adaptation

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.

Partnered, adapted argentine tango dance for cancer survivors: A feasibility study and pilot study of efficacy

BACKGROUND

Neurotoxic cancer treatments can cause chemotherapy-induced peripheral neuropathy and postural control deficits that cancer survivors report as a concern. Exercise-based sensorimotor training has emerged as a promising treatment for symptoms including balance deficits, however, more study is needed to optimize engagement and participation. We evaluated feasibility, satisfaction, and preliminary efficacy of a novel balance training program for cancer survivors: partnered, Adapted Argentine Tango dance (Tango).

METHODS

Twenty-two individuals participated (n = 22). Tango classes (1 h) were offered twice/week. At baseline, midpoint (8 classes), and conclusion of the training (15 or 16 classes), we assessed postural control by measuring center-of-pressure (CoP) measures during quiet standing with eyes closed. We also documented attendance, barriers to attendance, and satisfaction (7 point scale; 1 high). At conclusion, we analyzed whether 1) attendance and satisfaction met feasibility criteria; 2) postural control improved among participants who were outside of normal range at baseline; and 3) co-enrolling with a companion increased attendance.

FINDINGS

Feasibility criteria were met: more than half of participants attended more than half the classes offered with a mean satisfaction rate of 1.2 (SD 0.4). Those who enrolled with a companion (n = 9) attended more sessions than those who did not (n = 13) (Mann-Whitney U value = 20; p = 0.012). Participants with demonstrated deficits (n = 9) improved in 3 CoP measures at midpoint (i.e., medial-lateral sway, ellipse area, medial-lateral velocity), retaining improvement in 2 CoP measures at endpoint (i.e., medial-lateral sway, ellipse area).

INTERPRETATION

Partnered, Adapted Argentine Tango is feasible for cancer survivors and may improve postural control. Enrolling with a companion improved attendance.

Rowing together: Interpersonal coordination dynamics with and without mechanical coupling

Although most research on interpersonal coordination focuses on perceptual forms of interaction, many interpersonal actions also involve interactions of mechanical nature. We examined the effect of mechanical coupling in a rowing task from a coupled oscillator perspective: 16 pairs of rowers rowed on ergometers that were physically connected through slides (mechanical coupling condition) or on separate ergometers (no mechanical coupling condition). They rowed in two patterns (in- and antiphase) and at two movement frequencies (20 and 30 strokes per minute). Seven out of sixteen pairs showed one or more coordinative breakdowns, which only occurred in the antiphase condition. The occurrence of these breakdowns was not affected by mechanical coupling, nor by movement frequency. For the other nine pairs, variability of steady state coordination was substantially lower in the mechanical coupling condition. Together, these results show that the increase in coupling strength through mechanical coupling stabilizes coordination, even more so for antiphase coordination.

The Need for Combining Implicit and Explicit Communication in Cooperative Robotic Systems

As the number of robots used in warehouses and manufacturing increases, so too does the need for robots to be able to manipulate objects, not only independently, but also in collaboration with humans and other robots. Our ability to effectively coordinate our actions with fellow humans encompasses several behaviours that are collectively referred to as joint action, and has inspired advances in human-robot interaction by leveraging our natural ability to interpret implicit cues. However, our capacity to efficiently coordinate on object manipulation tasks remains an advantageous process that is yet to be fully exploited in robotic applications. Humans achieve this form of coordination by combining implicit communication (where information is inferred) and explicit communication (direct communication through an established channel) in varying degrees according to the task at hand. Although these two forms of communication have previously been implemented in robotic systems, no system exists that integrates the two in a task-dependent adaptive manner. In this paper, we review existing work on joint action in human-robot interaction, and analyse the state-of-the-art in robot-robot interaction that could act as a foundation for future cooperative object manipulation approaches. We identify key mechanisms that must be developed in order for robots to collaborate more effectively, with other robots and humans, on object manipulation tasks in shared autonomy spaces.

Human-Human Interaction Forces and Interlimb Coordination During Side-by-Side Walking With Hand Contact

Handholding can naturally occur between two walkers. When people walk side-by-side, either with or without hand contact, they often synchronize their steps. However, despite the importance of haptic interaction in general and the natural use of hand contact between humans during walking, few studies have investigated forces arising from physical interactions. Eight pairs of adult subjects participated in this study. They walked on side-by-side treadmills at 4 km/h independently and with hand contact. Only hand contact-related sensory information was available for unintentional synchronization, while visual and auditory communication was obstructed. Subjects walked at their natural cadences or following a metronome. Limb kinematics, hand contact 3D interaction forces and EMG activity of 12 upper limb muscles were recorded. Overall, unintentional step frequency locking was observed during about 40% of time in 88% of pairs walking with hand contact. On average, the amplitude of contact arm oscillations decreased while the contralateral (free) arm oscillated in the same way as during normal walking. Interestingly, EMG activity of the shoulder muscles of the contact arm did not decrease, and their synergistic pattern remained similar. The amplitude of interaction forces and of trunk oscillations was similar for synchronized and non-synchronized steps, though the synchronized steps were characterized by significantly more regular orientations of interaction forces. Our results further support the notion that gait synchronization during natural walking is common, and that it may occur through interaction forces. Conservation of the proximal muscle activity of the contact (not oscillating) arm is consistent with neural coupling between cervical and lumbosacral pattern generation circuitries (“quadrupedal” arm-leg coordination) during human gait. Overall, the findings suggest that individuals might integrate force interaction cues to communicate and coordinate steps during walking.

Balancing the playing field: collaborative gaming for physical training

Background

Multiplayer video games promoting exercise-based rehabilitation may facilitate motor learning, by increasing motivation through social interaction. However, a major design challenge is to enable meaningful inter-subject interaction, whilst allowing for significant skill differences between players. We present a novel motor-training paradigm that allows real-time collaboration and performance enhancement, across a wide range of inter-subject skill mismatches, including disabled vs. able-bodied partnerships.

Methods

A virtual task consisting of a dynamic ball on a beam, is controlled at each end using independent digital force-sensing handgrips. Interaction is mediated through simulated physical coupling and locally-redundant control. Game performance was measured in 16 healthy-healthy and 16 patient-expert dyads, where patients were hemiparetic stroke survivors using their impaired arm. Dual-player was compared to single-player performance, in terms of score, target tracking, stability, effort and smoothness; and questionnaires probing user-experience and engagement.

Results

Performance of less-able subjects (as ranked from single-player ability) was enhanced by dual-player mode, by an amount proportionate to the partnership’s mismatch. The more abled partners’ performances decreased by a similar amount. Such zero-sum interactions were observed for both healthy-healthy and patient-expert interactions. Dual-player was preferred by the majority of players independent of baseline ability and subject group; healthy subjects also felt more challenged, and patients more skilled.

Conclusion

This is the first demonstration of implicit skill balancing in a truly collaborative virtual training task leading to heightened engagement, across both healthy subjects and stroke patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-017-0319-x) contains supplementary material, which is available to authorized users.