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📄 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.