This paper presents a modular architecture to develop a wearable system for real-time human motion capture. The system is based on a network of smart inertial measurement units (IMUs) distributed on the human body. Each of these modules is provided with a 32-bit RISC microcontroller (MCU) and miniaturized MEMS sensors: three-axis accelerometer, three-axis gyroscopes, and three-axis magnetometer. The MCU collects measurements from the sensors and implement the sensor fusion algorithm, a quaternion-based extended Kalman filter to estimate the attitude and the gyroscope biases. The design of the proposed IMU, in order to overcome the problems of the commercial solution, aims to improve performance and to reduce size and weight. In this way, it can be easily embedded in a tracksuit for total body motion reconstruction with considerable enhancement of the wearability and comfort. Furthermore, the main achievements will be presented with a performance comparison between the proposed IMU and some commercial platforms.
- extended Kalman filter (EKF)
- MEMS sensor
- motion capture
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications