| Project/Area Number |
06670810
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Pediatrics
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| Research Institution | Oita Medical University |
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Principal Investigator |
OGAWA Teruyuki Oita Medical University, Department of Pediatrics, Professor, 医学部, 教授 (10039810)
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| Co-Investigator(Kenkyū-buntansha) |
FUKUSHIMA Naoki Oita Medical University, Dept of Pediatrics, Assistant, 医学部, 助手 (60218914)
KOJO Masanobu Oita Medical University, Dept of Pediatrics, Assistant Professor, 医学部, 講師 (10215262)
GOTO Kazuya Oita Medical University, Dept of Pediatrics, Assistant Professor, 医学部, 講師 (90178442)
石黒 真木夫 文部省統計数理研究所, 予測制御系, 教授 (10000217)
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| Project Period (FY) |
1994 – 1995
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| Project Status |
Completed (Fiscal Year 1995)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1995: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 1994: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | preterm-, newborn infant / long-term non-invasive signals / autoregressive model / Akaike information criterion / EEG activity / general movement / posture and movement / cardio-respiratory interaction / 赤池情報量規準(AIC) / General movement / 呼吸 / 自己回帰解析 / 脳波 / 呼吸変動 / RR間隔 / general movement |
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| Research Abstract |
Perinatal death and brain damage are conditions which can often be prevented as a result of the use of continous physiological monitoring techniques in labor. The computers were programd to automatically obtain the measurement on EEGs, heart rate, TcPO_2 and blood pressure from monitoring system, display and store the current values, retrieve post data with the using an autoregressive (AR) spectral analysis method (1992). By using the system, the following results were obtained.
1.Computer analysis of 24-hour EEG on using Akaike information criterion (AIC) in preterm infants : The results showed that the fluctations in minimum AIC and AIC-moving avarage might reflect the periodic change of QS state.
2.Autoregressive analysis of heart rate variability from prenatal to postnatal life : progressive and significant increases in the power density of the high-frequency component (0.28-0.45c/b : HF) from gestational week 36 to postnatal day 4 provided a quantitative index of the influence of respiration on the EEG signal and may be related to vagal activity.
3.Relationship between AR-powerspectrum and sleep stage : From 35 wk gestational age onward, respiratory frequency was higher in QS,compared to AS,and significantly from that of QS and AS.
4.AR-analysis of the 24-h EMG from preterm infants : AR-power spectral analysis can help defferentiate the duration measure in QS and AS.Assesment of the quality of general movements in preterm infants was automaticaly obtained.
5.Central pattern generators of general movement and autonomic nervous system.
In conclusion, the periodicity findings of this study suggest that biological signals in very young infants may be functionally linked to the emergent state properties of active sleep. The relationship between motility bursts and state in infants between 26 and 36 weeks conceptional age deserves further study.
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