Furutani Naoki, Takahashi Tetsuya, Naito Nobushige, Maruishi Takafumi, Yoshimura Yuko, Hasegawa Chiaki, Hirosawa Tetsu, Kikuchi Mitsuru
Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa 920-8640, Japan.
Research Center for Child Mental Development, Kanazawa University, Kanazawa 920-8640, Japan.
Entropy (Basel). 2021 Mar 31;23(4):418. doi: 10.3390/e23040418.
Recently, measuring the complexity of body movements during sleep has been proven as an objective biomarker of various psychiatric disorders. Although sleep problems are common in children with autism spectrum disorder (ASD) and might exacerbate ASD symptoms, their objectivity as a biomarker remains to be established. Therefore, details of body movement complexity during sleep as estimated by actigraphy were investigated in typically developing (TD) children and in children with ASD. Several complexity analyses were applied to raw and thresholded data of actigraphy from 17 TD children and 17 children with ASD. Determinism, irregularity and unpredictability, and long-range temporal correlation were examined respectively using the false nearest neighbor (FNN) algorithm, information-theoretic analyses, and detrended fluctuation analysis (DFA). Although the FNN algorithm did not reveal determinism in body movements, surrogate analyses identified the influence of nonlinear processes on the irregularity and long-range temporal correlation of body movements. Additionally, the irregularity and unpredictability of body movements measured by expanded sample entropy were significantly lower in ASD than in TD children up to two hours after sleep onset and at approximately six hours after sleep onset. This difference was found especially for the high-irregularity period. Through this study, we characterized details of the complexity of body movements during sleep and demonstrated the group difference of body movement complexity across TD children and children with ASD. Complexity analyses of body movements during sleep have provided valuable insights into sleep profiles. Body movement complexity might be useful as a biomarker for ASD.
最近，测量睡眠期间身体运动的复杂性已被证明是各种精神疾病的客观生物标志物。虽然睡眠问题在自闭症谱系障碍（ASD）儿童中很常见，并且可能会加剧ASD症状，但它们作为生物标志物的客观性仍有待确定。因此，我们研究了通过活动记录仪估计的典型发育（TD）儿童和ASD儿童睡眠期间身体运动复杂性的细节。对17名TD儿童和17名ASD儿童的活动记录仪原始数据和阈值化数据进行了几种复杂性分析。分别使用伪最近邻（FNN）算法、信息论分析和去趋势波动分析（DFA）来检验确定性、不规则性和不可预测性以及长程时间相关性。虽然FNN算法未揭示身体运动中的确定性，但替代分析确定了非线性过程对身体运动的不规则性和长程时间相关性的影响。此外，在睡眠开始后两小时内以及睡眠开始后约六小时，ASD儿童通过扩展样本熵测量的身体运动的不规则性和不可预测性明显低于TD儿童。这种差异在高不规则期尤为明显。通过这项研究，我们描述了睡眠期间身体运动复杂性的细节，并证明了TD儿童和ASD儿童之间身体运动复杂性的组间差异。睡眠期间身体运动的复杂性分析为睡眠概况提供了有价值的见解。身体运动复杂性可能作为ASD的生物标志物有用。
