Fiber-Optic and IMU Sensors for Muscle Fatigue Detection in Work Settings

Detection of muscle fatigue is essential in industrial environments to prevent work-related disorders and improve worker safety. Also, measuring elbow position is essential in human motion analysis. This paper proposes a novel approach for detecting muscle fatigue using an Optical Fiber (OF) sensor and Inertial Measurement Unit sensors (IMU). Ten healthy subjects performed a repetitive lifting activity using the IMU and OF sensor until reaching muscle fatigue. The study evaluates four machine learning algorithms, including Ensemble Classifiers (EC), Support Vector Machine (SVM), k Nearest Neighbour (k-NN), and Neural Networks (NN). Results of detecting muscle fatigue using the OF and IMU sensors obtained an accuracy of 98.4%. This setup can be easily used by workers and be relevant to identify workers' fatigue during long working shifts.