During movement, our central nervous system (CNS) takes into account the dynamics of our environment to optimally adapt our joint dynamics. In this study we explored the adaptation of shoulder joint dynamics when a participant interacted with a time-varying virtual environment created by a haptic manipulator. Participants performed a position task, i.e., minimizing position deviations, in face of continuous mechanical force perturbations. During a trial the environmental damping, mimicked by the manipulator, was either increased (0 to 200 N s/m) or decreased (200 to 0 N s/m) in 1 s or 8 s. A system identification technique, kernel-based regression, was used to reveal time-varying shoulder joint dynamics using the frequency response function (FRF). The FRFs revealed that the rate at which shoulder joint dynamics is adapted depends on the rate and direction of change in environmental damping. Adaptation is slow, but starts immediately, after the environmental damping increases, whereas adaptation is fast but delayed when environmental damping decreases. The results obtained in our participants comply with the framework of optimal feedback control, i.e., adaptation of joint dynamics only takes place when motor performance is at risk or when this is energetically advantageous.
|Title of host publication||BIOROB 2018 - 7th IEEE International Conference on Biomedical Robotics and Biomechatronics|
|Place of Publication||Piscataway, NJ, USA|
|Publication status||Published - 2018|
|Event||7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018 - Enschede, Netherlands|
Duration: 26 Aug 2018 → 29 Aug 2018
|Conference||7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018|
|Period||26/08/18 → 29/08/18|