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Human Activity Recognition (HAR) using wearable devices such as smart watches embedded with Inertial Measurement Unit (IMU) sensors has various applications relevant to our daily life, such as workout tracking and health monitoring. In this paper, we propose a novel attention-based approach to human activity recognition using multiple IMU sensors worn at different body locations. Firstly, a sensor-wise feature extraction module is designed to extract the most discriminative features fromarXiv:2112.11224v1 fatcat:it42nxqxorchdkruhjer7cutoe