Clinical Implications of Fluctuations and Rhythms in Biological Signals

生物在不同的时间尺度上表现出波动和节奏，这些时间尺度与产生、发育、成熟和衰老等非平稳过程有关。在医学治疗中，必须考虑生物信号的非平稳、节律性和波动性。在这项研究中，试图在长期记录和分析技术的基础上实现准确的诊断和有效的治疗。结果总结如下。(1)正常人心率变异性在10^<-3> ~ 10^<-2>Hz范围内出现1/f谱曲线偏差，反映慢波睡眠时心血管动态变化。(2)原发性高血压患者48小时血压记录显示，夜间“不斗”组与左室肥厚有显著相关性。(3)心绞痛患者的心理出汗测量有助于观察胸痛患者对心理应激的反应过程。(4)胃电图（EGG）显示位于胃上部的起搏器的电活动（3次/min）。糖尿病自主神经系统疾病患者的EGG表现为湍流型。(5)复杂解调技术对于分析非平稳信号的频谱分量波动是有用的。这里获得的结果阐明了生物信号波动和节律的临床意义。此外，新提出的分析技术有助于从生物信号中提取有用的信息。

Living things exhibit fluctuations and rhythms with various time scales associated with nonstationary processes such as generation, developing, maturing, and aging. In a medical treatment, it should be essential to consider nonstationary, rhythmic, and fluctuating aspects of biological signals. In this research, a precise diagnosis and an efficient medical treatment were attempted to be achieved based on a long-term recording and analysis techniques. Results are summarized as follows.(1) In the heart rate variabilities of normal human subjects, deviations from the 1/f spectral profile were observed in the frequency range from 10^<-3> to 10^<-2>Hz, which was supposed to reflact the cardiovascular dynamics during slow wave sleep.(2) The 48hr recording of blood pressure of essential hypertensive patients showed the significant correlation between the "Non-dipper" group during night and left ventricular hypertrophy.(3) The measurement of psychologic sweating for angina patients was shown to be useful to observe the responsive process to the psychological stress associated with the thoracic pain.(4) Electrogastrograph (EGG) was shown to reflect the electrical activity (3 times/min) of pacemakers located on the upper side of the stomach. The patients with diabetic autonomic nervous system disease were found to show a turbulant pattern of EGG.(5) The complex demodulation technique was shown to be useful for analysing fluctuations in spectral components of nonstationary signals.The results obtained here clarify the clinical implications of fluctuations and rhythms in biological signals. Besides, the newly proposed analysis techniques could contribute to extracting useful information from biological signals.