Estimating Core Body Temperature Using Electrocardiogram Signals

Abstract

Purpose: Core body temperature is one of the diagnostic criteria for heatstroke. This study proposed an algorithm that estimates core body temperature based on electrocardiogram signals that are received by a wearable sensor.Methods: A total of 12 healthy males aged 21–64 years performed an ergometric exercise load test in an environmental chamber adjusted to a temperature of 35°C and humidity of 50% under two exercise conditions. Physical data were obtained from participants pre- and post-experiment, while electrocardiograms, core body temperatures, and body surface temperatures were continuously measured. Amount of change in core body temperature was estimated by multiple regression analysis wherein indexes derived from electrocardiograms was treated as the dependent variables.Results: Findings showed that continuous core body temperature can be estimated using electrocardiogram signals regardless of individual characteristics such as age and physique. Conclusions: In this study, we developed a core body temperature estimation model using the Poincaré plot method. Changes in heartrate were related to heat production and yielded valid results. As the basic estimation model is positioned for use under limited conditions, we also plan to enhance estimation accuracy and further verify efficacy in consideration of clothing and environmental conditions.