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

Abstract

This paper presents a real-time standalone computing system's design and development using an Arduino Nano controller for human gait phase detection. It acquires the lower limb segment angles using 3-inertial measurement units and foot insole-based force data using 2-force sensitive resistor sensors for each leg. Arduino IDE-based algorithms are designed to get thigh, shank, and foot angles using the I2C protocol. The force information is achieved using an insole that gathers data from the heel and toe regions. A fuzzy logic-based algorithm is developed in the Arduino IDE for the detection of 7-gait phases. MATLAB's neuro-fuzzy designer toolbox is utilized to obtain a rule base for these gait phases. The results showed that the present system gives a prediction accuracy of 89.65 (± 3)% that is good enough, along with a 20 ms prediction time to make it real-time gait phase detection. This study finds the application of a fuzzy-logic algorithm for real-time control of the ankle-foot prosthesis in an open space using a standalone system with an amputee.