Functional Principal Component Analysis of Intracranial Pressure Data
نویسندگان
1 Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran.
2 Department of Mathematics and Statistics, Macquarie University, 2109 Sydney, Australia.
3 Department of Neurosurgery, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad 99199‑91766, Iran.
4 Social Determinates of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
5 Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
doi
10.22034/jirss.2025.2021358.1050چکیده
The term "functional data" refers to data where the units of observation are functions defined over a time interval. The fundamental philosophy behind functional data is that the repeated measurements for each individual are considered as a stochastic process over time. One of the commonly used analyses for such data is functional principal component analysis. In this study, since the intracranial pressure is measured over time in patients with subarachnoid hemorrhage due to aneurysm, functional principal component analysis is employed to identify the main factors contributing to increased intracranial pressure. The first four functional principal components account for 87.8 percent of the total variation in the intracranial pressure curve. The first, second, third, and fourth principal components explain approximately 52.3, 21.9, 8, and 5.6 percent of the overall variation, respectively. These four components are linked to the total Glasgow Coma Scale score, diastolic blood pressure, age, and systolic blood pressure, respectively.
