Abstract
The number of occupational injury claims and certifications for mental disorders increases every year. Therefore, the Ministry of Health, Labour and Welfare of Japan (MHLW) has mandated annual stress checks as a countermeasure. This gives rise to the having a daily health measurement using IoT devices. However, it has been found that managing multiple devices and active measurement behavior decreases users’ motivation. This paper proposes a health measurement system that can be integrated with traditional brushing tools enabling a smooth gauging of health measures. This is done while people are performing their daily teeth brushing activity without any extra overhead. The proposed method estimates the recovery index for fatigue based on halitosis collecting by a smart toothbrush with a halitosis sensor. To evaluate the proposed method, we collected halitosis data and questionnaires about recovery index from 12 subjects every day for approximately two months and constructed a model to estimate each item of the questionnaires by Random Forest based on the halitosis data. As a result, we found a significant difference between the halitosis data and two measures of the recovery experience (MA and PD); furthermore, we achieved MA with an f-score of 0.60, PD with an F-score of 0.58 for three value classification, and sleep quality with an F-score of 0.71 with binary classification.
This research is partially supported by Initiative for Life Design Innovation (iLDi) Platform for Society 5.0.
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References
Bandura, A., Freeman, W., Lightsey, R.: Self-efficacy: the exercise of control. Br. J. Clin. Psychol. (1999)
Binnewies, C., Sonnentag, S., Mojza, E.J.: Daily performance at work: feeling recovered in the morning as a predictor of day-level job performance. J. Organ. Behav.: Int. J. Ind. Occup. Organ. Psychol. Behav. 30(1), 67–93 (2009)
Brosschot, J.F., Pieper, S., Thayer, J.F.: Expanding stress theory: prolonged activation and perseverative cognition. Psychoneuroendocrinology 30(10), 1043–1049 (2005)
Bui, A.L., Fonarow, G.C.: Home monitoring for heart failure management. J. Am. Coll. Cardiol. 59(2), 97–104 (2015). https://doi.org/10.1016/j.jacc.2011.09.044
De Croon, E.M., Sluiter, J.K., Blonk, R.W., Broersen, J.P., Frings-Dresen, M.H.: Stressful work, psychological job strain, and turnover: a 2-year prospective cohort study of truck drivers. J. Appl. Psychol. 89(3), 442 (2004)
Doi, Y., et al.: Psychometric assessment of subjective sleep quality using the Japanese version of the pittsburgh sleep quality index (PSQI-J) in psychiatric disordered and control subjects. J. Organ. Behav.: Int. J. Ind. Occup. Organ. Psychol. Behav. 97, 165–172 (2000)
Etzion, D., Eden, D., Lapidot, Y.: Relief from job stressors and burnout: reserve service as a respite. J. Appl. Psychol. 83(4), 577 (1998)
Inan, O.T., et al.: Novel wearable seismocardiography and machine learning algorithms can assess clinical status of heart failure patients. Circ. Heart Fail. 11(1), e004313 (2018). https://doi.org/10.1161/CIRCHEARTFAILURE.117.004313
Ingram, S.S., et al.: The association between oral health and general health and quality of life in older male cancer patients. J. Am. Geriatr. Soc. 53(9), 1504–1509 (2005)
Islam, S., Kim, A., Hwang, G., Song, S.H.: Smart tooth system for in-situ wireless PH monitoring. In: 2021 21st International Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), pp. 755–758 (2021). https://doi.org/10.1109/Transducers50396.2021.9495706
Kim, S.Y., Sim, S., Kim, S.G., Park, B., Choi, H.G.: Prevalence and associated factors of subjective halitosis in Korean adolescents. PLoS ONE 10(10), 14–21 (2015)
Kwon, H.J., Yoon, M.S.: Relationship of depression, stress, and self-esteem with oral health-related quality of life of middle-aged women. J. Dent. Hyg. Sci. 15(6), 825–835 (2015)
Leng, L.B., Giin, L.B., Chung, W.Y.: Wearable driver drowsiness detection system based on biomedical and motion sensors. In: 2015 IEEE SENSORS, pp. 1–4 (2015). https://doi.org/10.1109/ICSENS.2015.7370355
Lim, H.R., Jeon, S.Y.: Relationship between stress, oral health, and quality of life in university students. J. Dent. Hyg. Sci. 16(4), 310–316 (2016)
MarketsandMarkets Research Private Ltd: Wearable fitness technology market report. https://www.marketsandmarkets.com/Market-Reports/wearable-fitness-technology-market-139869705.html. Accessed 08 Sept 2021
Ministry of Health, Labour and Welfare: Compensation status for industrial accidents and public affairs accidents related to death from overwork. https://www.mhlw.go.jp/stf/newpage_04738.html. Accessed 08 June 2021
Ministry of Health, Labour and Welfare: Mental health measures and overwork measures in the workplace such as stress checks. https://www.mhlw.go.jp/bunya/roudoukijun/anzeneisei12/index.html. Accessed 08 Sept 2021
Ministry of Health, Labour and Welfare: Workmen’s accident compensation status such as death from overwork. https://www.mhlw.go.jp/content/11402000/000796022.pdf. Accessed 08 Sept 2021
Ryotaro Bonai: Verification of blood glucose improvement effect through behavior change of IoT in type 2 diabetes: PRISM-J. https://www.amed.go.jp/content/000059276.pdf. Accessed 08 Sept 2021
Shetty, V., Morrison, D., Belin, T., Hnat, T., Kumar, S., et al.: A scalable system for passively monitoring oral health behaviors using electronic toothbrushes in the home setting: development and feasibility study. JMIR Mhealth Uhealth 8(6), e17347 (2020)
Shimazu, A., Sonnentag, S., Kubota, K., Kawakami, N.: Validation of the Japanese version of the recovery experience questionnaire. J. Occup. Health 54(3), 196–205 (2012)
Sonnentag, S., Fritz, C.: The recovery experience questionnaire: development and validation of a measure for assessing recuperation and unwinding from work. J. Occup. Health Psychol. 12(3), 204 (2007)
Zhang, S., et al.: Necksense: a multi-sensor necklace for detecting eating activities in free-living conditions. CoRR abs/1911.07179 (2019). http://arxiv.org/abs/1911.07179
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Yoshimura, S., Mizumoto, T., Matsuda, Y., Ueda, K., Takeyama, A. (2022). Daily Health Condition Estimation Using a Smart Toothbrush with Halitosis Sensor. In: Hara, T., Yamaguchi, H. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-030-94822-1_43
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