Optimal Tracking Periods for Behavior in Risk Assessment

Long-term sedentary behavior, which involves spending extended periods sitting or being inactive, increases the risk of obesity, cardiovascular disease, and other health problems. These risks are often overlooked due to low levels of physical activity. This study promotes the use of You Only Look Once (YOLO) pose estimation for dwell-time analysis to monitor sedentary behavior. Our study was conducted with 20-8-2 cycle strategy, which encourages individuals to sit for 20 minutes, stand for 8 minutes, and move for 2 minutes. This approach is based on guidelines recommended by an international group of experts, invited by Public Health England and Active Working CIC (UK community interest company), to promote the reduction of prolonged sedentary behavior. This paper attempted to offer a workable approach for promoting physical activity and reducing the health hazards associated with sedentary behavior by utilizing YOLO object detection. Our model achieved a mAP@50 score of 96.9%, demonstrating high accuracy in object detection.

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Published
2025-05-20
DOI
https://doi.org/10.1109/ecti-con64996.2025.11101620
Primary Topic
Decision-Making and Behavioral Economics
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article
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article

Optimal Tracking Periods for Behavior in Risk Assessment

Suree Pumrin, Phengou Chea
Decision-Making and Behavioral Economics
article

Optimal Tracking Periods for Behavior in Risk Assessment

Suree Pumrin, Phengou Chea
article en

Abstract

Long-term sedentary behavior, which involves spending extended periods sitting or being inactive, increases the risk of obesity, cardiovascular disease, and other health problems. These risks are often overlooked due to low levels of physical activity. This study promotes the use of You Only Look Once (YOLO) pose estimation for dwell-time analysis to monitor sedentary behavior. Our study was conducted with 20-8-2 cycle strategy, which encourages individuals to sit for 20 minutes, stand for 8 minutes, and move for 2 minutes. This approach is based on guidelines recommended by an international group of experts, invited by Public Health England and Active Working CIC (UK community interest company), to promote the reduction of prolonged sedentary behavior. This paper attempted to offer a workable approach for promoting physical activity and reducing the health hazards associated with sedentary behavior by utilizing YOLO object detection. Our model achieved a mAP@50 score of 96.9%, demonstrating high accuracy in object detection.

Chulalongkorn University (TH)
Climate action
Openalex Percentile: Top 75%
Decision-Making and Behavioral Economics
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