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arxiv_cv 88% Match Dataset Paper Machine Learning Researchers,Robotics Engineers,Biomedical Engineers,Sports Scientists,Rehabilitation Specialists,Wearable Technology Developers 20 hours ago

StrengthSense: A Dataset of IMU Signals Capturing Everyday Strength-Demanding Activities

robotics › manipulation
📄 Abstract

Abstract: Tracking strength-demanding activities with wearable sensors like IMUs is crucial for monitoring muscular strength, endurance, and power. However, there is a lack of comprehensive datasets capturing these activities. To fill this gap, we introduce \textit{StrengthSense}, an open dataset that encompasses IMU signals capturing 11 strength-demanding activities, such as sit-to-stand, climbing stairs, and mopping. For comparative purposes, the dataset also includes 2 non-strength demanding activities. The dataset was collected from 29 healthy subjects utilizing 10 IMUs placed on limbs and the torso, and was annotated using video recordings as references. This paper provides a comprehensive overview of the data collection, pre-processing, and technical validation. We conducted a comparative analysis between the joint angles estimated by IMUs and those directly extracted from video to verify the accuracy and reliability of the sensor data. Researchers and developers can utilize \textit{StrengthSense} to advance the development of human activity recognition algorithms, create fitness and health monitoring applications, and more.

Key Contributions

Introduces 'StrengthSense', a comprehensive, open dataset of IMU signals capturing 11 strength-demanding activities from 29 subjects. It includes comparative analysis of IMU-derived joint angles against video ground truth, addressing the lack of such datasets.

Business Value

Enables the development of advanced wearable systems for monitoring physical health, guiding rehabilitation, and optimizing athletic performance, potentially leading to new health tech products and services.