PERSIST: A Multimodal Dataset for the Prediction of Perceived Exertion During Resistance Training
Authors/Creators
- 1. Digital Health - Connected Healthcare, Hasso Plattner Institute, University of Potsdam
- 2. Exercise and Human Movement Science, Department of Sport and Sport Science, University of Freiburg
Description
PERSIST is a novel dataset for predicting PERceived exertion during reSIStance Training. It includes multiple sensor modalities, including inertial measurement units (IMU), electrocardiography (ECG), and motion capture (MoCap). The MoCap data has been synchronized to the IMU and ECG data. Also, it provides heart rate variability (HRV) parameters obtained from the ECG signal. The dataset contains data from twelve young and healthy male participants with at least one year of resistance training experience. Subjects performed twelve sets of squats on a Flywheel platform with twelve repetitions per set. After each set, subjects reported their current RPE.
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The PERSIST dataset may be shared upon request for scientific use only. The participants' consent for this study requires accessing the dataset with legitimate scientific interest. Therefore, please briefly outline your scientific interest and provide your research institution's email address to gain access. The provided personal data will be used solely by the authors to verify your scientific interest and deleted as soon as it is no longer required.
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