Functional data analysis for wearable sensor data: a systematic review

Nihan Acar-Denizli () and Pedro Delicado ()
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Nihan Acar-Denizli: Universitat Politècnica de Catalunya
Pedro Delicado: Universitat Politècnica de Catalunya

AStA Advances in Statistical Analysis, 2025, vol. 109, issue 3, No 9, 631 pages

Abstract: Abstract Wearable devices and sensors have recently become a popular way to collect data, especially in the health sciences. The use of sensors allows patients to be monitored over a period of time with a high observation frequency. Due to the continuous-on-time structure of the data, novel statistical methods are recommended for the analysis of sensor data. One of the popular approaches in the analysis of wearable sensor data is functional data analysis. The main objective of this paper is to review functional data analysis methods applied to wearable device data according to the type of sensor. In addition, we introduce several freely available software packages and open databases of wearable device data to facilitate access to sensor data in different fields.

Keywords: Accelerometer; Glucometer; Functional principal component analysis; Functional regression; Open data; Wearable devices (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10182-025-00531-8

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