How Long Are Various Types of Daily Activities? Statistical Analysis of a Multimodal Wearable Sensor-based Human Activity Dataset

Hui Liu, Tanja Schultz

2022

Abstract

Human activity research in the field of informatics, such as activity segmentation, modeling, and recognition, is moving in an increasingly interpretable direction with the introduction of sports and kinematics knowledge. Many related research topics face a question: How long is the typical duration of the activities needed to be modeled? Several public human activity datasets do not strictly limit single motions’ repetition times, such as gait cycle numbers, in recording sessions, so they are not statistically significant concerning activity duration. Standing on the rigorous acquisition protocol design and well-segmented data corpus of the recently released multimodal wearable sensor-based human activity dataset CSL-SHARE, this paper analyzes the duration statistics and distribution of 22 basic single motions of daily activities and sports, hoping to provide research references for human activity studies. We discovered that (1) the duration of each studied human daily activity or simple sports activity reflects interpersonal similarities and naturally obeys a normal distribution; (2) one single motion (such as jumping and sitting down) or one cycle in the activities of cyclical motions (such as one gait cycle in walking) has an average duration in the interval from about 1 second to 2 seconds.

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Paper Citation


in Harvard Style

Liu H. and Schultz T. (2022). How Long Are Various Types of Daily Activities? Statistical Analysis of a Multimodal Wearable Sensor-based Human Activity Dataset. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF, ISBN 978-989-758-552-4, pages 680-688. DOI: 10.5220/0010896400003123


in Bibtex Style

@conference{healthinf22,
author={Hui Liu and Tanja Schultz},
title={How Long Are Various Types of Daily Activities? Statistical Analysis of a Multimodal Wearable Sensor-based Human Activity Dataset},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,},
year={2022},
pages={680-688},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010896400003123},
isbn={978-989-758-552-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,
TI - How Long Are Various Types of Daily Activities? Statistical Analysis of a Multimodal Wearable Sensor-based Human Activity Dataset
SN - 978-989-758-552-4
AU - Liu H.
AU - Schultz T.
PY - 2022
SP - 680
EP - 688
DO - 10.5220/0010896400003123