Non-weight-bearing neural control of a powered transfemoral prosthesis

Lower limb prostheses have traditionally been mechanically passive devices without electronic control systems. microprocessor-controlled passive and powered devices have recently received much interest from the clinical and research communities. the control systems for these devices typically use finite-state controllers to interpret data measured from mechanical sensors embedded within the prosthesis. in this paper we investigated a control system that relied on information extracted from myoelectric signals to control a lower limb prosthesis while amputee patients were seated. sagittal plane motions of the knee and ankle can be accurately (>90%) recognized and controlled in both a virtual environment and on an actuated transfemoral prosthesis using only myoelectric signals measured from nine residual thigh muscles. patients also demonstrated accurate (∼90%) control of both the femoral and tibial rotation degrees of freedom within the virtual environment. a channel subset investigation was completed and the results showed that only five residual thigh muscles are required to achieve accurate control. this research is the first step in our long-term goal of implementing myoelectric control of lower limb prostheses during both weight-bearing and non-weight-bearing activities for individuals with transfemoral amputation. © 2013 hargrove et al.; licensee biomed central ltd.