{'fraction_non_alphanumeric': 0.02074688796680498, 'fraction_numerical': 0.0, 'mean_word_length': 5.266233766233766, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Ant Colony Optimization Tuning PID Algorithm for Precision Control of Functional Electrical Stimulation

Functional electrical stimulation (FES) can restore motor function in individuals with spinal cord injury (SCI). Neuroprostheses based on FES apply electric stimuli to induce muscle contractions and the corresponding joint movements. The goal of this study was to design a novel FES controller, and the attention is focused on the feedback control of the knee-joint movements induced by electrical stimulation of the quadriceps muscle group. Ant colony optimization algorithm is employed to modulate the propor- tional, integral and derivative values of PID controller. The promising results showed the ACO-PID controller func- tioned as expected and performed better than the GA-PID controller. This method for a knee-joint movement resulted in decrease of the tracking error and shortened delay in the response, which may be applied in walking-assisted FES.