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Journal Articles Bulletin of the Polish Academy of Sciences : Technical Sciences Year : 2020

Missing-data imputation using wearable sensors in heart rate variability

Amira Tlija
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Katarzyna Wegrzyn-Wolska
Dan Istrate

Abstract

The objective of this work is to set up a methodology that considers missing data from a connected heartbeat sensor in order to propose a good replacement methodology in the context of heart rate variability (HRV) computation. The framework is a research project, which aims to build a system that can measure stress and other factors influencing the onset and development of heart disease. The research encompasses studying existing methods, and improving them by use of experimental data from case study that describe the participant’s everyday life. We conduct a study to modelize stress from the HRV signal, which is extracted from a heart rate monitor belt connected to a smart watch. This paper describes data recording procedure and data imputation methodology. Missing data is a topic that has been discussed by several authors. The manuscript explains why we choose spline interpolation for data values imputation. We implement a random suppression data procedure and simulate removed data. After that, we implement several algorithms and choose the best one for our case study based on the mean square error.

Dates and versions

hal-03553710 , version 1 (02-02-2022)

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Amira Tlija, Katarzyna Wegrzyn-Wolska, Dan Istrate. Missing-data imputation using wearable sensors in heart rate variability. Bulletin of the Polish Academy of Sciences : Technical Sciences, 2020, 68 (2), ⟨10.24425/bpasts.2020.133118⟩. ⟨hal-03553710⟩
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