Development of a rule-based automatic five-sleep-stage scoring method for rats

Ting Ying Wei, Chung Ping Young, Yu Ting Liu, Jia Hao Xu, Sheng Fu Liang, Fu Zen Shaw, Chin En Kuo

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)


Background: Sleep problem or disturbance often exists in pain or neurological/psychiatric diseases. However, sleep scoring is a time-consuming tedious labor. Very few studies discuss the 5-stage (wake/NREM1/NREM2/transition sleep/REM) automatic fine analysis of wake-sleep stages in rodent models. The present study aimed to develop and validate an automatic rule-based classification of 5-stage wake-sleep pattern in acid-induced widespread hyperalgesia model of the rat. Results: The overall agreement between two experts' consensus and automatic scoring in the 5-stage and 3-stage analyses were 92.32% (κ = 0.88) and 94.97% (κ = 0.91), respectively. Standard deviation of the accuracy among all rats was only 2.93%. Both frontal-occipital EEG and parietal EEG data showed comparable accuracies. The results demonstrated the performance of the proposed method with high accuracy and reliability. Subtle changes exhibited in the 5-stage wake-sleep analysis but not in the 3-stage analysis during hyperalgesia development of the acid-induced pain model. Compared with existing methods, our method can automatically classify vigilance states into 5-stage or 3-stage wake-sleep pattern with a promising high agreement with sleep experts. Conclusions: In this study, we have performed and validated a reliable automated sleep scoring system in rats. The classification algorithm is less computation power, a high robustness, and consistency of results. The algorithm can be implanted into a versatile wireless portable monitoring system for real-Time analysis in the future.

期刊Biomedical engineering online
出版狀態Published - 2019 9月 4

All Science Journal Classification (ASJC) codes

  • 放射與超音波技術
  • 生物材料
  • 生物醫學工程
  • 放射學、核子醫學和影像學


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