An Energy-Efficient Smart Gait System

We present here proof of concept for a smart energy-efficient hybrid gait monitoring system. It consists of a hybrid Inertial Measuring Unit (IMU) and Triboelectric Nanogenerator (TENG) sensing module, and it utilizes multiple strategies to reduce the computational load and energy overhead of the device while maintaining accuracy. It meets the lower energy demands through a self-powered mechanism, thus eliminating the need for batteries. Firstly, a TENG harvests the biomechanical energy of human movement and is optimized for high energy output. Then the IMU sensor collects and processes only sparse data. An algorithm is implemented to select the best sampling points in the gait data, and it adapts as it gains knowledge of the user’s walking pattern. The IMU sensor is powered intermittently through the TENG and a power management unit while the person is walking. Finally, a TinyML algorithm is employed for data intelligence at the device level.