TY - JOUR
T1 - Learning Hemodynamic Effect of Transcranial Infrared Laser Stimulation Using Longitudinal Data Analysis
AU - Wu, Qian
AU - Wang, Xinlong
AU - Liu, Hanli
AU - Zeng, Li
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - Brain hemodynamics
KW - functional mixed-effect model
KW - longitudinal data analysis
KW - photobiomodulation
UR - http://www.scopus.com/inward/record.url?scp=85086051256&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85086051256&origin=recordpage
U2 - 10.1109/JBHI.2019.2951772
DO - 10.1109/JBHI.2019.2951772
M3 - RGC 21 - Publication in refereed journal
C2 - 31714245
SN - 2168-2194
VL - 24
SP - 1772
EP - 1779
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 6
M1 - 8892501
ER -