Experimental heart rate regulation in cycle-ergometer exercises.

Area of Science:

• Physiology
• Control Systems Engineering
• Exercise Science

Background:

• Heart rate (HR) is a key indicator of exercise intensity, crucial for targeted training and rehabilitation.
• Precise HR control is vital for athletes and individuals with cardiovascular or obesity-related conditions.
• Existing HR regulation methods may lack precision during prolonged ergometer exercises.

Purpose of the Study:

• To adapt a recently proposed nonlinear control strategy for HR regulation from treadmill to cycle-ergometer exercises.
• To validate a nonlinear HR dynamics model for cycle-ergometer use.
• To demonstrate the effectiveness of generalized proportional-integral control in this context.

Main Methods:

• Mathematical modeling of HR dynamics during cycle-ergometer exercise, inspired by treadmill models.
• Application of nonlocal and nonswitching nonlinear control techniques.
• Experimental validation using a cycle-ergometer at constant cycling speed and varying workloads.
• Generalization of classical proportional-integral control to a nonlinear framework.

Main Results:

• Experimental validation of the proposed nonlinear HR dynamics model for cycle-ergometer exercises.
• Demonstration of precise HR regulation using the adapted nonlinear control approach.
• Confirmation that workload in cycling is analogous to treadmill speed in HR dynamics models.
• Successful generalization of proportional-integral control within a nonlinear framework.

Conclusions:

• The nonlocal, nonswitching nonlinear control strategy is effective for HR regulation in cycle-ergometer exercises.
• The study validates a nonlinear HR dynamics model applicable to cycling.
• The findings support the potential for precise HR control in exercise physiology and clinical settings.
• Online HR reference modification using heart rate variability (HRV) is a promising avenue for future research.