An Improved Design of Knee Orthosis Using Self-Adaptive Bonobo Optimizer (SaBO)

In medical sector, the necessity of developing orthotic devices has been felt, nowadays, due to the increasing number of patients with stroke or spinal injury cases. In this regard, knee orthosis plays a vital role to enliven the patients having issues related to knee movements. There exist a few designs of orthotic devices in the literature. However, these are yet to be made more compact and energy efficient. In this study, a novel optimal design of an energy-economic knee orthosis has been obtained. To serve this purpose, an efficient and intelligent optimization algorithm, namely Self-adaptive Bonobo Optimizer (SaBO), has been developed with the inclusion of memory, past experiences, and novel repulsion-based learning for the parameters’ updating. To examine the performance of the proposed SaBO, initially, thirty difficult-to-solve CEC’14 benchmark functions have been solved and the obtained results are found to be the better compared to that of other six recently developed optimization techniques. Next, it has been applied to solve the complex knee-orthosis design problem. Here, the optimal design of knee-orthosis yielded by the developed SaBO is seen to be the most energy-efficient one. It is to be noted that the required maximum motor torque is found to be decrease up to 22% compared to that obtained using other optimization tools. [ABSTRACT FROM AUTHOR]