穿戴式裝置之睡眠品質偵測演算法分析與評估

Analysis and Assessment of Sleep Quality Detection Algorithm based on Wearable Device

林秤毅(Pin-Yi Lin)

指導教授 ： 李仁貴

國立臺北科技大學/電資學院/電腦與通訊研究所/碩士(2014年)

https://doi.org/10.6841/NTUT.2014.00230

摘要

睡眠在人的生活中扮演非常重要的角色，對於生理及心理的狀態恢復有一定的作用，因此自身的睡眠品質已被漸漸的重視。然而一般的穿戴式睡眠裝置礙於硬體限制，演算法設計無法太過複雜，進而影響評估睡眠品質的準確性。因此本論文提出一套新的系統，主要應用於穿戴式裝置，其中包含了收集心率參數的前端裝置，在受測者睡眠期間紀錄資料。此外論文與安卓系統結合，以簡單的介面幫助受測者自身的睡眠階段變化情況。考慮到穿戴式裝置硬體的限制，演算法設計參考心跳變異率的時域分析，參考SDNN(Standard Deviation of all Normal to Normal Intervals)時域分析作為主要判斷準則，最後再根據三軸加速度值的變化，綜合整理出完整的睡眠品質分析。
最後系統與MIT-BIH(Polysomnographic Database)睡眠資料庫驗證，整體睡眠階段命中率達70%以上；評估結果與其他系統比較下，MAPE(Mean Absolute Percentage Error)的結果分別為0.082%及0.1365%。相較其他穿戴式睡眠裝置，能提供更準確的睡眠資訊。

關鍵字

睡眠品質 ； 心跳變異率 ； 安卓系統 ； 穿戴式裝置。

並列摘要

Sleeping is important in people’s life, which is occupy one-third of life. People have to go to the hospital to detect the sleep disorder when something bad during sleep. Due to the complex procedure, we expect to develop a new system to detect sleep quality, which used few physiological parameters. Considering the limitations of wearable devices, the algorithms using relatively simple time-domain analysis.
In addition, the system will combine with android environment to help people to understand self-condition easily. The overall hit rate was above 70% of sleep stage detection which was compared to MIT-BIH sleep database. And the MAPE of sleep efficiency verification with other system were 0.082% and 0.1365%. Compared to other systems, it can offer more accurate information.

並列關鍵字

Sleep Quality ； HRV ； Android System ； Wearable Device

參考文獻

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