「世大智科/天才家居」-我們創業囉
Contact Professor: Yeh-Liang Hsu (徐業良)

102學年度元智大學機械工程研究所陳澤蔚碩士論文

Master thesis by Tsu-Wei Chen, Mechanical Engineering Department, Yuan Ze University, 2013

102碩士論文:適用於居家環境之活動感知床墊 商品化開發及應用

  「床」是每天睡眠與休息的場所,長期的臥床睡眠資訊常常可以表現出個人的健康狀況,而對於一些無法自主行動的人,或是需長期照護的高齡者而言,床的角色更為重要。睡眠多項生理檢查儀器(polysomnography, PSG)是臨床睡眠監測標準設備,許多研究著重在開發非侵入式、非察覺性臥床活動感知技術,適用於居家長期監測。
  本研究開發適用於居家長期監測的臥床活動感知床墊WhizPad,更進一步與床墊製造商世大化成股份有限公司合作進行商品化,考量公司的材料及相關製程來進行感知床墊的設計,使床墊在不同壓力下有不同的電阻值。在保有高度舒適性的前提下,本研究中所開發的WhizPad活動感知床墊提供臥/離床、姿態辨識與活動力感測的功能,並針對此三項感測的功能做了靈敏度與陽性預測值的分析;本研究並評估開發呼吸偵測功能的可行性,實驗結果驗證活動感知床墊在判斷臥/離床的靈敏度與準確率是100%;判斷臥床姿態的靈敏度為正躺79%、側躺92%,準確率為正躺86%、側躺84%;判斷活動力的靈敏度為83%,準確率為95%;呼吸實驗以PSG波形人工數出的呼吸頻率與演算法所偵測到的呼吸頻率對照,平均差異為0.73次,最大差異為-2.0次。

關鍵字:睡眠監測、活動感知、臥床姿態、呼吸頻率

Development and Commercialization of a Motion-Sensing Mattress Applied in Home Environment

The bed is an indispensable part of our daily lives. Bed activity monitoring provides valuable information of the health status. This is especially true for older adults with disabilities who stay in bed most of the time. While polysomnography (PSG) is the standard clinical equipment for sleep monitoring, various sensors have been developed for long term sleep monitoring in the home environment in an unobtrusive way.

The objective of this study is to develop a motion sensing mattress WhizPad. Collaborating with a mattress manufacturer, the material and manufacturing process are considered for commercialization. WhizPad has the ability to provide information about on/off bed, sleep posture, and motion-sensing. The sensitivity and Positive Predictive Value (PPV) of WhizPad were also accessed. Moreover, the feasibility of breath detection using WhizPad was studied as well. Based on the experimental results, WhizPad yields the sensitivity of 100% and the PPV of 100% for on/off bed detection. The sensitivity for posture recognition is 79% while lying on the back and 92% while lying on one side. Further, the PPV is 86% and 84% for each posture, respectively. As for sleep motion-sensing, the sensitivity is 83%, while the PPV is 95%. Finally, the respiration rate is compared with the data obtained by using PSG. The average difference is 0.73 times per minute, and the maximal difference is -2.0 times per minute.

Keyword: sleep monitoring; motion sensing; sleep posture; respiration rate

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Last Updated:2014/1/2