This paper is devoted to the problem of regulating the heart rate response along a predetermined reference profile, for cycle-ergometer exercises designed for training or cardio-respiratory rehabilitation. The controller designed in this study is a non-conventional, non-model-based, proportional, integral and derivative (PID) controller. The PID controller commands can be transmitted as biofeedback auditory commands, which can be heard and interpreted by the exercising subject to increase or reduce exercise intensity. However, in such a case, for the purposes of effectively communicating to the exercising subject a change in the required exercise intensity, the timing of this feedback signal relative to the position of the pedals becomes critical. A feedback signal delivered when the pedals are not in a suitable position to efficiently exert force may be ineffective and this may, in turn, lead to the cognitive disengagement of the user from the feedback controller. This note examines a novel form of control system which has been expressly designed for this project. The system is called an “actuator-based event-driven control system”. The proposed control system was experimentally verified using 24 healthy male subjects who were randomly divided into two separate groups, along with cross-validation scheme. A statistical analysis was employed to test the generalisation of the PID tunes, derived based on the average transfer functions of the two groups, and it revealed that there were no significant differences between the mean values of root mean square of the tracking error of two groups (3.9 vs. 3.7 bpm, \(p = 0.65\)). Furthermore, the results of a second statistical hypothesis test showed that the proposed PID controller with novel synchronised biofeedback mechanism has better performance compared to a conventional PID controller with a fixed-rate biofeedback mechanism (Group 1: 3.9 vs. 5.0 bpm, Group 2: 3.7 vs. 4.4 bpm, \(p <0.05\)).
['Ahmadreza Argha', 'Steven W. Su', 'Branko G. Celler']
Heart rate regulation during cycle-ergometer exercise via event-driven biofeedback