Yuma SHISHIKURA’s research while affiliated with Azabu University and other places

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Publications (1)


Results of raw data points obtained by Random Tree prediction
Results of raw data points by comparison between activiy classes and sleep meter determination
Predictive Values of activit y classes Sleep stage Precision Recall Accuracy F1 score
Beacon-based sleep-wake monitoring in dogs
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  • Full-text available

April 2024

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38 Reads

Journal of Veterinary Medical Science

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Mizuho YAGISAWA

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Kahori KOYAMA

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[...]

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Miho NAGASAWA

The sleep-wake cycle represents a crucial physiological process essential for maintaining homeostasis and promoting individual growth. In dogs, alterations in sleep patterns associated with age and dog’s correlation with temperament factors, such as nervousness, have been reported, and there is an increasing demand for precise monitoring of sleep and physical activity in dogs. The present study aims to develop an analysis method for measuring sleep-wake patterns and physical activity in dogs by utilizing an accelerometer and a smartphone. By analyzing time series data collected from the accelerometer attached to the dog's collar, a comprehensive sleep and activity analysis model was constructed. This model classified the activity level into seven classes and effectively highlighted the variations in sleep-activity patterns. Two classes with lower activity levels were considered as sleep, while other five levels were regarded as wake based on the rate of occurrence. This protocol of data acquisition and analysis provides a methodology that enables accurate and extended evaluation of both sleep and physical activity in dogs.

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