Physically interacting individuals estimate the partner’s goal to enhance their movements


From a parent helping to guide their child during their first steps, to a therapist supporting a patient, physical assistance enabled by haptic interaction is a fundamental modus for improving motor abilities. However, what movement information is exchanged between partners during haptic interaction, and how this information is used to coordinate and assist others, remains unclear1. Here, we propose a model in which haptic information, provided by touch and proprioception2, enables interacting individuals to estimate the partner’s movement goal and use it to improve their own motor performance. We use an empirical physical interaction task3 to show that our model can explain human behaviours better than existing models of interaction in literature48. Furthermore, we experimentally verify our model by embodying it in a robot partner and checking that it induces the same improvements in motor performance and learning in a human individual as interacting with a human partner. These results promise collaborative robots that provide human-like assistance, and suggest that movement goal exchange is the key to physical assistance.

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Figure 1: Computational framework to test four models of haptic interaction for comparison against experimental data.
Figure 2: Simulations of four representative models of haptic interaction reveal that the ‘interpersonal goal integration’ model has the most predictive power.
Figure 3: A robot partner embodying the ‘interpersonal goal integration’ model physically assists human users as human partners do.


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We thank C. Clopath, P. Bentley, S. Mussa-Ivaldi, Y. Sasaki and T. Watanabe for their comments on an earlier version of this manuscript. This work was funded in part by the EU-FP7 grants ICT-231554 HUMOUR, ICT-601003 BALANCE, ICT-611626 SYMBITRON, EU-H2020 ICT-644727 COGIMON, UK EPSRC MOTION grant EP/NO29003/1 and by the Great Britain Sasakawa Foundation. This work was also partially supported by a contract with the National Institute of Information and Communications Technology entitled “Development of Network Dynamics Modelling Methods for Human Brain Data Simulation Systems”, and by “Development of BMI Technologies for Clinical Application” of the Strategic Research Program for Brain Sciences supported by the Japan Agency for Medical Research and Development (AMED). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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A.T., G.G., M.K. and E.B developed the computational model. G.G. and T.Y. conducted the empirical experiments with human pairs, and A.T. and T.Y. tested human users with the robot assistant. A.T. and G.G. analysed the data and simulated the models. A.T., G.G., M.K. and E.B. wrote and edited the manuscript.

Corresponding authors

Correspondence to Atsushi Takagi or Etienne Burdet.

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The authors declare no competing interests.

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Supplementary Methods; Supplementary Figures. (PDF 408 kb)

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Takagi, A., Ganesh, G., Yoshioka, T. et al. Physically interacting individuals estimate the partner’s goal to enhance their movements. Nat Hum Behav 1, 0054 (2017).

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