IEEE J Biomed Health Inform. 2020 Jun;24(6):1772-1779. doi: 10.1109/JBHI.2019.2951772. Epub 2019 Nov 6.
Transcranial infrared laser stimulation (TILS) is a promising noninvasive intervention for neurological diseases. Though some experimental work has been done to understand the mechanism of TILS, the reported statistical analysis of data is quite simple and could not provide a comprehensive picture on the effect of TILS. This study learns the effect of TILS on hemodynamics of the human brain from experimental data using longitudinal data analysis methods. Specifically, repeated measures analysis of variance (ANOVA) is first applied to confirm the significance of the TILS effect and its characteristics. Based on that, two parametric mixed-effect models and non-parametric functional mixed-effect model are proposed to model the population-level performance and individual variation of this effect. Interpretations on the fitted models are provided, and comparison of the three proposed models in terms of fitting and prediction performance is made to select the best model. According to the selected model, TILS increases the concentration of oxygenated hemoglobin in the brain and this effect sustains even after the treatment stops. Also, there is considerable variation among individual responses to TILS.
经颅红外激光刺激(TILS)是一种有前途的神经疾病的非侵入性干预方法。虽然已经进行了一些实验工作来了解 TILS 的机制,但报告的数据统计分析相当简单,无法全面反映 TILS 的效果。本研究使用纵向数据分析方法,从实验数据中学习 TILS 对人脑血液动力学的影响。具体来说,首先应用重复测量方差分析(ANOVA)来确认 TILS 效应及其特征的显著性。在此基础上,提出了两种参数混合效应模型和非参数功能混合效应模型,以对该效应的群体水平性能和个体变异性进行建模。对拟合模型进行了解释,并就拟合和预测性能方面对这三个提出的模型进行了比较,以选择最佳模型。根据所选模型,TILS 会增加大脑中含氧血红蛋白的浓度,并且这种效应即使在治疗停止后仍会持续。此外,个体对 TILS 的反应存在相当大的差异。