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# WearMoCap Dataset
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We collected this data to develop and test WearMoCap, a system facilitating multimodal pose tracking from smartwatch and smartphone data.
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Its source code and tutorials are available on [__github__](https://github.com/wearable-motion-capture).
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Details about data composition and collection setups are described in a published technical report [__here__](https://doi.org/10.3389/frobt.2024.1478016).
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A video showcasing the WearMoCap system is available [__here__](https://www.youtube.com/watch?v=hyQY5dyWPLU).
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# Repository Structure
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As described in the [__technical report__](https://doi.org/10.3389/frobt.2024.1478016), we partitioned data for operating WearMoCap in three modes: __Watch Only__, __Phone Uarm__, and __Phone Pocket__.
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Each mode is one subfolder, which contains a README with more information
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# WearMoCap Dataset
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__TLDR:__ This dataset comprises optical motion capture data of left arm motions and body orientations, which are paired with smartwatch and phone sensor measurements. All synced, calibrated, and preprocessed time series data is stored as CSVs.
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We collected this data to develop and test the open-source library WearMoCap, a system facilitating multimodal pose tracking from smartwatch and smartphone data.
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Its source code and tutorials are available on [__github__](https://github.com/wearable-motion-capture).
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Details about data composition and collection setups are described in a published technical report [__here__](https://doi.org/10.3389/frobt.2024.1478016).
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A video showcasing the WearMoCap system is available [__here__](https://www.youtube.com/watch?v=hyQY5dyWPLU).
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# Repository Structure
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As described in the [__technical report__](https://doi.org/10.3389/frobt.2024.1478016), we partitioned data for operating WearMoCap in three modes: __Watch Only__, __Phone Uarm__, and __Phone Pocket__.
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Each mode is one subfolder, which contains a README with more information and subfolders spliting the data by human subjects.
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Simplified directory structure overview:
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mode
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