Analyzing Compensation Strategy in Impaired Walking Using a Humanoid Robot

In order to overcome the risk of falling-down, people usually develop different kinds of compensated gait in response to their local function impairment. Compensated walking has been analyzed empirically in the area of gait analysis, but it has not been analyzed considering underlying mechanism of walking function, such as the nervous system . In this study, we employed a bio-mimetic humanoid robot with a Central Pattern Generator (CPG) neural model to emulate a hemiplegic gait with spasticity in the gastrocnemius muscle. The CPG parameters were decided using the genetic algorithm (GA). This impairment was implemented by limiting the output of the right ankle flex ion . Then, a compensatory mechanism was explored by adjusting the outputs of the other neuron s. The results show that, it is possible to use this approach to analyze a hemiplegic gait and its compensation strategy. Thus, w e were able to improve the behavioral understanding of a compensated gait .