Ikhtedar Husain Rizvi
Department of Mechanical Engineering, Indian Institute of Technology Bhilai, Chhattisgarh-492015, India
Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi-110016, India; Department of Mechanical Engineering, Indian Institute of Technology Bhilai, Chhattisgarh-492015, India
Elevated core temperature is the primary indicator of heat injury for people working in a hot environment. High core body temperature (core temperature greater than 40°C) for a prolonged period leads to the state of heatstroke. Untreated heatstroke conditions cause damage to the heart, brain, and kidney. Longer delays in treatment lead to more serious complications. This can be prevented by monitoring the body core temperature during the work session. We have compared the performance of the simple Kalman filter (KF) and extended Kalman filter (EKF) models for estimating the core temperature using heart rate measurements for different personal cooling intervention systems. Measured data of core temperature and heart rate were used for the development and validation of the Kalman filter models. It is found that the EKF model performance was better for all cases since it has an overall RMSE equal to 0.30 °C which is lesser than the RMSE (0.52 °C) value for the KF model. Kalman filter models performed similarly for different cooling intervention systems and these models are easily implementable as heart rate is the only measured parameter required.