Validity of the Polar H7 Heart Rate Sensor for Heart Rate Variability Analysis during Exercise in Different Age, Body Composition and Fitness Level Groups

Abstract

This work aims to validate the Polar H7 heart rate (HR) sensor for heart rate variability (HRV) analysis at rest and during various exercise intensities in a cohort of male volunteers with different age, body composition and fitness level. Cluster analysis was carried out to evaluate how these phenotypic characteristics influenced HR and HRV measurements. For this purpose, sixty-seven volunteers performed a test consisting of the following consecutive segments: sitting rest, three submaximal exercise intensities in cycle-ergometer and sitting recovery. The agreement between HRV indices derived from Polar H7 and a simultaneous electrocardiogram (ECG) was assessed using concordance correlation coefficient (CCC). The percentage of subjects not reaching excellent agreement (CCC > 0.90) was higher for high-frequency power (PHF) than for low-frequency power (PLF) of HRV and increased with exercise intensity. A cluster of unfit and not young volunteers with high trunk fat percentage showed the highest error in HRV indices. This study indicates that Polar H7 and ECG were interchangeable at rest. During exercise, HR and PLF showed excellent agreement between devices. However, during the highest exercise intensity, CCC for PHF was lower than 0.90 in as many as 60% of the volunteers. During recovery, HR but not HRV measurements were accurate. As a conclusion, phenotypic differences between subjects can represent one of the causes for disagreement between HR sensors and ECG devices, which should be considered specifically when using Polar H7 and, generally, in the validation of any HR sensor for HRV analysis.

Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review

“…Chest-strap devices use sensors to measure the electric activity of the heart and have been often used as a simple and less costly alternative to traditional ECG. A number of studies that used chest-strap heart-rate devices found that in general, they show excellent agreement during resting and exercise at light to moderate intensities, but some decreased their accuracy during higher exercise intensities, while others maintained an excellent performance even during high-intensity exercise [ 65 , 66 ]. Nonetheless, the overall level of agreement varied among participants, level of exercise, and indices of HRV [ 65 ].…”

Multimodal Assessment of the Pulse Rate Variability Analysis Module of a Photoplethysmography-Based Telemedicine System

“…However, in the literature, it is controversial whether HRV parameters calculated from time series of RR intervals obtained from ECG recordings and from pulse durations obtained from PPG signals or continuous non-invasive blood pressure monitoring (e.g., Finapress) can be used alternatively [ 54 ]. Nowadays, the number of wearable and telemedical devices that are equipped with either ECG or PPG detectors dynamically increases [ 55 , 56 ]. This may open new prospects for scientists and physicians to exploit the opportunities offered by HRV/PRV analysis in patient evaluation.…”

Analysis of Gender Differences in HRV of Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Mobile-Health Technology

“…More studies have been published recently combining HRV and mHealth technologies [ 63 , 64 , 65 , 66 ]. However, one of the main limitations of those studies is the high sensitivity to the body movement and the presence of artifacts as that most of them rely on a photoplethysmography sensor for detecting the heartbeats or the inter-beat cardiac intervals [ 67 , 68 ]. The gold standard for HRV analysis is based on the lab-ECG signal.…”

“…However, this recording method requires the use of electrodes and leads, so it is expensive, uncomfortable for the patient, and requires some training. As an alternative to the lab-ECG, they are recently appearing portable user devices based on mHealth technology, detecting ECG signals deriving the RR interval values for HRV analysis [ 38 , 68 , 69 ].…”