Validity Of An Algorithm To Estimate Core Temperature During Prolonged Walking In Hot Ambient Conditions

PURPOSE: Climate change exposes people more often to environmental heat stress, which increases the risk to develop heat-related illnesses. Non-invasive methods are needed to reliably monitor core temperature (TC) responses during exercise. The ECTempTM algorithm estimates TC based on sequential heart rate (HR) measurements. We examined the validity of ECTempTM to estimate TC during real-world prolonged walking exercise in hot ambient conditions, and compared the validity on group level data and individual participant level data. METHODS: Participants walked 30 (n = 3), 40 (n = 13) or 50 (n = 2) km on a self-selected pace during which TC was continuously measured using an ingestible telemetric temperature capsule. HR was measured at 1-sec intervals and estimated core temperature (Test) was computed based on the HR observations using the ECTempTM algorithm. Bland Altman analyses were performed to assess agreement between TC and Test, and Pearson’s correlation coefficients were calculated. A systematic bias <0.1 °C was considered acceptable. The data was analyzed both on group and individual level. RESULTS: 18 participants (56 ± 16 years, 61% male) walked for 549 min (range 418-645 min), while ambient temperature increased from 22 °C to 29 °C throughout the day. Average HR was 108 ± 13 bpm and TC ranged from 36.9 °C to 39.2 °C, whereas Test ranged from 36.8 °C to 38.9 °C. A total of 8,572 observations were available to compare TC and Test. Group level data revealed an acceptable systematic bias of -0.09 °C (p < 0.01), indicating that average Test values were slightly larger than TC values. The limits of agreements were, however, large ±0.76 °C and a weak correlation was found between TC and Test (r = 0.28; p < 0.01). Individual participant level data revealed different outcomes as the systematic bias ranged from -0.62 °C to 0.45 °C and correlation coefficients ranged from -0.09 to 0.95. Three out of 18 participants (17%) had an acceptable systemic bias. CONCLUSION: On group level, the ECTempTM algorithm provides a low and acceptable systematic bias during prolonged walking exercise in hot ambient conditions, but individual participant level data showed that only 3 out of 18 participants had a bias <0.1 °C. Future studies are needed to improve the accuracy of the algorithm to the individual level, so it can be used during exercise in the heat.