A unified heart rate control approach for cycle ergometer and treadmill exercise. (September 2019)

• Record Type: Journal Article
• Authors: Hunt, Kenneth J.; Zahnd, Andreas; Grunder, Reto
• Is Part Of: Biomedical signal processing and control. Volume 54(2019)
• Publication Date: 2019-09
• Subjects: Heart rate dynamics -- System identification -- Heart rate control -- Physiological control -- Treadmills -- Cycle ergometers; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.101601
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Very-low-frequency heart rate variability is a challenge for feedback control of HR. We derive a unified control approach for cycle ergometers and treadmills. Novel control design approach using shaping of the input sensitivity function. Highly accurate tracking of target heart rate with mean RMS error around 3 bpm. Robustness despite substantial plant variability and simple plant model. Abstract: Objective: To develop a unified heart rate (HR) control approach for cycle ergometer (CE) and treadmill (TM) exercise, and to empirically compare the common controller's performance between the CE and TM. Methods: The control method used frequency-domain shaping of the input-sensitivity function to address rejection of disturbances arising from broad-spectrum heart rate variability (HRV). A single controller was calculated using an approximate, nominal linear plant model and an input-sensitivity bandwidth specification. Fifty HR control tests were executed using the single controller: 25 healthy male participants each did one test on the CE and one on the TM. Results: There was no significant difference in mean root-mean-square HR tracking error: 3.10 bpm ± 0.68 bpm and 2.85 bpm ± 0.75 bpm (mean ± standard deviation, bpm = beats/min); CE vs. TM; p = 0.13. But mean normalised average control signal power was significantly different: 1.59 bpm 2 ± 0.27 bpm 2 vs. 1.36 bpm 2 ± 0.28 bpm 2 ; CE vs. TM; p = 3.5 × 10 −4 . Conclusion and significance: The lower values for RMS tracking error and control signal power for the TM point to decreasing HRV intensity with increasing HR, because, in order to match perceived exertion for the two modalities, mean HR for the TM was set 20 bpm higher than for the CE. These HR-intensity-dependent differences in HRV are consistent with previous observations in the literature. The unified HR control approach for CE and TM exercise gave accurate, stable and robust performance in all tests, thus lending support to the concept that HRV disturbance rejection is the main issue in HR control design.