In this chapter an agent-based ambient system is presented to support persons in learning specific movement patterns. The ambient system serves as a personal coach that observes a person’s movement pattern, and analyses this based on comparison with an ideal pattern generated by optimisation using a computational musculoskeletal model for this type of pattern minimizing knee joint loading. Based on this analysis the Personal Coach generates advice to adapt the person’s pattern in order to better approximate the ideal pattern. The Personal Coach has been designed using the agent design method DESIRE, thereby reusing an available generic agent model. The system was evaluated (a proof of principle) by setting up an environment in which sensoring of body part positions was incorporated. In evaluations with a few subjects substantial improvement of the movement pattern compared to the ideal movement pattern was achieved.
|Title of host publication||Human Aspects in Ambient Intelligence|
|Subtitle of host publication||Contemporary Challenges and Solutions|
|Editors||T. Bosse, D.J. Cook, M. Neerincx, F. Sadri|
|Number of pages||18|
|Publication status||Published - 2013|
|Name||Atlantis Ambient and Pervasive Intelligence|