1996 Fiscal Year Final Research Report Summary
Quantitative Analysis of 24-Hour Sleep Awake Architecture by Autoregressive Analysis in Preterm Infants
| Project/Area Number |
07670878
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Pediatrics
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| Research Institution | Oita Medical University |
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Principal Investigator |
GOTO Kazuya Oita Medical University・Pediatrics・Assistant Professor, 医学部, 講師 (90178442)
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| Co-Investigator(Kenkyū-buntansha) |
MAEDA Tomoki Oita Medical University・Pediatrics・Research Assistant, 医学部, 助手 (80264349)
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| Project Period (FY) |
1995 – 1996
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| Keywords | newborn / sleep / autoregressive analysis. / automated classification / electroencephalogram / respiration / eye movement / piezoelectric transducer |
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| Research Abstract |
The purpose of this study is to quantify the sleep architecture in preterm infants. We analyzed 1) 24-hour electroencephalogram (EEG) 2) 24-hour respiratory wave and 3) eye movements recorded by piezoelectric transducer.
We could have developed computerized, automated system which analyze EEG discontinuity. This system provides the degree of EEG discontinuity and its maximum value through 24-hour record. We also developed an autoregressive analysis and evaluate EEG parameters including moving average of minimum AIC (Akaike Information Criteria), total power, and delta power. The results showed that these EEG parameters were well organized both during quiet sleep and active sleep in preterm infants from 30 weeks of conceptional age. With the autoregressive analysis, quiet sleep states could be separated from non quiet sleep states automatically basing on these EEG parameters. 24-hour respiratory wave form were also quantified by an autoregressive analysis. Comparing with active sleep, si
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gnificantly longer damping time was observed in quiet sleep. With damping time and AIC,quiet sleep could be automatically detected with both sufficient sensitivity and specificity. Moreover, normal distribution AIC (n-AIC) has great advantage to quantify the regularity of respiratory wave form more exactly. With n-AIC,24-hour respiratory wave form becomes more regular with increasing conceptional ages. The findings which less AIC variability of 24-hour respiratory wave form was observed in infants with perinatal brain damage suggested that there exits sleep stage abnormality in those infants. We use piezoelectric film PVDF to detect eye movement. This is the first report to use this equipment. Comparing with electrooculogram, piezoelectric film could detect eye movements with sufficient sensitivity. Although this equipment was only applied to shot-term polygraphic recording, artifact could be excluded with simultaneous recording of cheek electromyogram and automated detection of eye movement became possible. Automated detection of body movement is the important problem in order to develop the system of automated sleep state classification. Less
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