| Project/Area Number |
18K11531
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62010:Life, health and medical informatics-related
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| Research Institution | University of Miyazaki |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
淡野 公一 宮崎大学, 工学部, 教授 (50260740)
永田 順子 宮崎大学, 医学部, 講師 (50264429)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2019: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 呼吸・心拍計測 / 圧電素子 / 睡眠時無呼吸症候群判定 / ファジィ化 / 心拍・呼吸計測技術 / 生体信号解析 / 睡眠時無呼吸症候群判断 / 呼吸数計測 / 心拍数計測 / 睡眠時無呼吸状態判定 / 生体信号計測 / 睡眠時無呼吸症候群 |
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| Outline of Final Research Achievements |
Incorporating real time health monitoring systems in a non-restrictive way, can significantly improve an individual’s quality of life in the treatment of sleep disorders. This research suggests a novel system for non-wearable, cost effective measurement of breathing and heart-beat during sleep state. The measurement system is composed of flexible multi-piezoelectric elements to acquire the pressure fluctuations persuade by respiratory movement and heart-beat when the subject is lying on it. Further, in the evaluation of non-breathing time intervals, the amplitude changes in the extracted breathing waveforms were considered over its sleep event. Several experiments were conducted in order to evaluate the performance of the system on above criteria, along with a commercially available system. The experimental results suggest that the proposed method can measure and extract the related waveforms of breathing and heart-beat successfully.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で開発したシステムは、睡眠中の呼吸、心拍の情報を収集し、呼吸波形の変化からわかりえる睡眠状態を判定することが可能になると期待される。現在のコロナ禍で、在宅治療等が注目されているが、本システムは在宅で自身の睡眠時の状態を把握し、本人が無自覚な睡眠障害を含めて睡眠状態でわかる病気等を予防することができるヘルスケアの機器になりえる。将来的には、在宅だけでなく、介護施設、病院、育児施設等での活用が想定され、無意識に見守られ、見える化できることで、多くの人の生活の質の向上に貢献できるものと考える。
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