Neural network aided prosthetic alignment

Some 43,000 lower-limb amputations are performed in the United States each year. Current procedures for fitting a prosthesis to an amputee are somewhat time-consuming and costly, requiring the subjective judgement of trained prosthetists, but necessary to avoid discomfort and ensure successful rehabilitation of the patient. We consider a neural network model which automatically recognizes certain types of misalignment using data obtained from an instrumented shank. Training procedures and partial results are described