Design of an Intelligent Controller for Above Knee Prostheses based on an Adaptive Neuro-Fuzzy Inference System

Abstract

The number of Above Knee (AK) amputees has increased in recent years and this has led to a need for urgent work on the design of proper lower limb prostheses. Lower limb prosthetics can be divided into active and passive devices. However, passive prosthetics cannot fully provide the natural motion of a healthy leg, and the technologies used in active prosthetics with knee joints are often far too expensive for amputees in developing countries such as Iraq. In this paper, an active lower limb prosthesis with an efficient knee joint is thus designed. Two strategies were used to collect data for gait cycle analysis of the leg in the sagittal plane: the first was based on the use of a force platform device to obtain the foot ground force according to the foot position (x, y), while the second utilised a video-camera based system to examine knee joint angles. The obtained data were all sent to an intelligent controller that uses an Adaptive Neuro-based Fuzzy Inference System (ANFIS). The ANFIS controller determines the ground force, mimicking the moment of the active knee with a DC motor and flexion-extension angle values. The experimental data for the motion of the knee joint were collected in the Gait Laboratory, then transformed to joint angles using the ANFIS controller. The results show excellent response in the proposed ANFIS controllers in terms of determining angle and moment values of the knee joint with a very low RMS error of 0.006.

Design and Control of Transfemoral Prosthesis Prototype with Magneto-Rheological Damper

“…For the analysis done on the sagittal plane of the gait cycle, they used two strategies for collecting the data that are sent to the controller. The results of the research show that the ANFIS controllers had an excellent response when determining values of a knee joint such as moment and angle values which had an RMS error value of 0.006 [13]. In 2018, Fahad M Kadhim et al designed and fabricated a microcontroller-based smart transfemoral prosthetic knee joint.…”

Design an intelligent hybrid position/force control for above knee prosthesis based on adaptive neuro-fuzzy inference system

“…In gait control, the position, force and speed, are the parameters that can be changes or control to have the final goal, the gait process for the amputee person. D. A. Kadhim et al [27], the work was done by using the ANFIS controllers that regulate the ground force, simulating the flexion-extension angle values and the moment of DC motor for the designed active knee. The gait laboratory was used to collect the experimental motion data of the revolute knee joint, and then the ANFIS controller transform them to joint angles.…”

A Standalone Real-Time Gait Phase Detection Using Fuzzy-Logic Implementation in Arduino Nano

“…This difficulty can be solved by extending the fuzzy-logic principle to detect gait phases for fuzzy membership values [14]. Researchers have used fuzzy-logic techniques to control upper limbs [15] and lower limb prostheses [16]. Among these studies, a few researchers worked on image-based control [17], whereas others have used wearable sensors such as Electromyography (EMG), IMU sensors, FSR sensors on foot insole, and knee and ankle angle sensors [18].…”