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ABSTRACT: 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.
IEEE Transactions on Industrial Electronics 09/2011; · 5.16 Impact Factor
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ABSTRACT: In this paper the authors introduce a smart module designed to provide, effortless, Attitude and Heading Reference System (AHRS) capabilities to a host application processor on an embedded system. The underling idea is to combine digital processing and Inertial Measurement Units (IMU) in a single module giving, not only sensors measurement, but especially a reliable orientation measure without any additional external computational power. In this way the target application should not face math operations and/or strict timing typical of this kind of algorithms.
Robotics and Automation (ICRA), 2011 IEEE International Conference on; 06/2011
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ABSTRACT: Nowadays the opportunity to have a smart human motion tracking systems represents an interesting instrument in a wide range of advanced application, such as gaming, augmented reality, telemedicine, rehabilitation and many other human machine interaction applications. In this paper the authors want to propose system architecture to implement a wearable system for real-time human motion capture. The presented system are based on a network of smart inertial measurement units (IMUs) distributed on the human body to estimate the orientation of the limbs. Each of these modules is provided by miniature MEMS 3-axes accelerometer, three MEMS gyroscopes, a MEMS 3-axes magnetometer, and a MCU for collecting measurements from the sensors and compute the orientation through a customized Extended Kalman Filter (EKF) for sensor fusion.
Human System Interactions, 2009. HSI '09. 2nd Conference on; 06/2009
