WaistonBelt X: A Belt-Type Wearable Device with Sensing and Intervention Toward Health Behavior Change
Open accessAbstract
Changing behavior related to improper lifestyle habits has attracted attention as a solution to prevent lifestyle diseases, such as diabetes, heart disease, arteriosclerosis, and stroke. To drive health behavior changes, wearable devices are needed, and they must not only provide accurate sensing and visualization functions but also effective intervention functions. In this paper, we propose a health support system, WaistonBelt X, that consists of a belt-type wearable device with sensing and intervention functions and a smartphone application. WaistonBelt X can automatically measure a waistline with a magnetometer that detects the movements of a blade installed in the buckle, and monitor the basic activities of daily living with inertial sensors. Furthermore, WaistonBelt X intervenes with the user to correct lifestyle habits by using a built-in vibrator. Through evaluation experiments, we confirmed that our proposed device achieves measurement of the circumference on the belt position (mean absolute error of 0.93 cm) and basic activity recognition (F1 score of 0.95) with high accuracy. In addition, we confirmed that the intervention via belt vibration effectively improves the sitting posture of the user.
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WaistonBelt X received an F1 score of 0.82 for seven activities trailed with 17 participants, with some misclassifications occurring between sitting and standing, walking and walking up and down stairs.
“WaistonBelt X received an F1 score of 0.82, with some misclassifications occurring between sitting and standing, walking and walking up and down stairs [162].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [162]
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Review of Wearable Devices and Data Collection Considerations for Connected Health
Vijayan, V., Connolly, J. P., Condell, J., McKelvey, N., & Gardiner, P. (2021) · Sensors · doi:10.3390/s21165589 · Cited by 435 · see citing works
- Authors
- Nakamura, Y., Matsuda, Y., Arakawa, Y., & Yasumoto, K.
- Affiliations
- Japan Society for the Promotion of Science (JP)
- Nara Institute of Science and Technology (JP)
- Kyushu University (JP)
- Corresponding author
- Nakamura, Yugo
- Matsuda, Yuki
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2019-10-22
- Volume
- 19
- Issue
- 20
- Pages
- 4600
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC6832512
- OpenAlex
- W2981600727
- Cited by
- 24
- References
- 37
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 3 · 2023: 6 · 2022: 4 · 2021: 4 · 2020: 2
- FWCI
- 1.12
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Japan Science and Technology Agency (JPMJPR18UK, JPMJPR1868)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- waist measurement, magnetometer, inertial sensors, activity recognition, health behavior change, sitting posture, mobile application, health support system
- MeSH terms
- Smartphone, Wearable Electronic Devices, Adult, Algorithms, Female, Humans, Male, Posture, Surveys and Questionnaires, Signal Processing, Computer-Assisted, Time Factors, Health Behavior, Young Adult, Accelerometry
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