Adapting directional intention identification in running control of a walker to individual difference with fuzzy learning

An omni-directional walker (ODW) has been developed for walking rehabilitation and walking support in the authors' previous studies. It is necessary for the ODW to know its user's directional intention according to the user's manipulation during walking support. In this paper, a novel method is proposed to recognize a user's directional intention according to his/her forearm pressures to the ODW, which are measured by sensors embedded in the ODW's armrest. First, the relationship between forearm pressure and directional intention was extracted as fuzzy rules. Second, an algorithm is proposed for directional intention identification based on distance-type fuzzy reasoning method (DTFRM). Furthermore, fuzzy learning is introduced to adapt directional intention identification to the individual difference in forearm pressures. The experiment results show that the reasoning results of the proposed method are consistent with the intended directions, and that fuzzy learning can reduce the reasoning errors caused by individual difference.