A nonlinear dynamic model for heart rate response to treadmill walking exercise

A nonlinear dynamic model for heart rate response to treadmill walking exercise, Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 22-26 Aug. 2007]. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Technology, Sydney's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it A nonlinear dynamic model for heart rate response to treadmill walking exercise Teddy M. Cheng, Andrey V. Savkin, Branko G. Celler, Lu Wang, Steven W. Su Abstract-A dynamic model of the heart rate response to treadmill walking exercise is presented. The model is a feedback interconnected system; the subsystem in the forward path represents the neural response to exercise, while the subsystem in the feedback path describes the peripheral local response. The parameters of the model were estimated from 5 healthy adult male subjects, each undertaking 3 sets of walking exercise at different speeds. Simulated responses from the model closely match the experimental data both in the exercise and the recovery phases. The model will be useful in explaining the cardiovascular response to exercise and in the design of exercise protocols for individuals

Self biofeedback control of oxygen consumption (Vo2) during cycling exercise : based on its real time estimate

The aim of this paper is to develop the self biofeedback (SBF) control of oxygen consumption (Vo2) during cycling exercise. The developed system uses an estimator that can predict Vo2 in real time by using the measurements of heart rate (HR), respiratory rate (RespR) and frequency of exercising activity, this terms is known as Exercise Rate (ER). The biofeedback command is given to the exercising subject in terms of the desired action required by the subject to achieve the targeted Vo2 (Vo 2target) profile. The desired action is determined by the SBF system based on the current estimates of Vo2 and is communicated to the exercising subject by flashing an indicator on the computer screen. The results obtained in this study demonstrate that the estimator developed for cycling exercise is capable of estimating Vo2 in real time. The developed system is tested on six healthy male subjects. The obtained results show that the SBF system performs well with the average steady state error in terms of Root Mean Square Error (RMSE) of 1 ml/min/Kg during low intensity exercise and with RMSE of 1.6426 ml/min/Kg during high intensity exercise

Estimation of Walking Energy Expenditure by Using Support Vector Regression

Abstract-This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed