Integrated multimodal sensory and intelligent adaptive control system and method for prosthetic limbs

A method for controlling a prosthetic limb, the method comprising:

• acquiring multimodal sensor data, wherein the multimodal sensor data is collected from a plurality of sensors integrated into the prosthetic limb, including:
• accelerometers and gyroscopes for linear and angular motion, pressure sensors for force distribution across a foot, electromyography (EMG) sensors, and environmental sensors including inclinometers for slope detection and ultrasonic sensors for obstacle detection;
• processing the sensor data, wherein the processing includes:
• filtering and normalizing the sensor data to remove noise and ensure consistency in data format,
• extracting features from the sensor data to identify subject movement patterns and environmental conditions, and
• generating predicted prosthetic limb parameters and predicted subject intent, wherein the features are input into a machine learning (ML) model trained on training data including sensor data and corresponding subject intent and corresponding prosthetic limb parameters, the ML model outputting the predicted subject intent and the predicted prosthetic limb parameters;
• and
• generating a control signal based on the processed sensor data, wherein the control signal is generated by a control system comprising a fuzzy logic controller and a proportional-integral-derivative (PID) controller, wherein the control signal is used to adjust the prosthetic limb parameters in real time.