Automatic control of a drop-foot stimulator based on angle measurement using bioimpedance

The topic of this contribution is iterative learning control of a drop-foot stimulator in which a predefined angle profile during the swing phase is realized. Ineffective dorsiflexion is compensated by feedback-controlled stimulation of the muscle tibialis anterior. The ankle joint measurement is based on changes in the bioimpedance (BI) caused by leg movements. A customized four-channel BI measurement system was developed. The suggested control approach and the new measurement method for the joint angle were successfully tested in preliminary experiments with a neurologically intact subject. Reference angle measurements were taken with a marker-based optical system. An almost linear relation between joint angle and BI was found for the angle range applicable during gait. The desired angle trajectory was closely tracked by the iterative learning controller after three gait cycles. The final root mean square tracking error was below 5 degrees.