The Zephyr BioHarness was tested to determine the accuracy of heart rate (HR) and respiratory rate (RR) measurements during 2 exercise protocols in conjunction with either a laboratory metabolic cart (Vmax) or a previously validated portable metabolic system (K4b2). In one protocol, HR and RR were measured using the BioHarness and Vmax during a graded exercise up to V˙O2max (n=12). In another protocol, HR and RR were measured using the BH and K4b2 during sustained exercise (30% and 50% V˙O2max for 20 min each) in a hot environment (30 °C, 50% relative humidity) (n=6). During the graded exercise, HR but not RR, obtained from the BioHarness was higher compared to the Vmax at baseline and 30% V˙O2max (p<0.05), but showed no significant difference at other stages with high correlation coefficients for both HR (r=0.87-0.96) and RR (r=0.90-0.99 above 30% V˙O2max). During the exercise in the heat, there were no significant differences between the BioHarness and K4b2 system. Correlation coefficients between the methods were low for HR but moderately to highly correlated (0.49-0.99) for RR. In conclusion, the BioHarness is comparable to Vmax and K4b2 over a wide range of V˙O2 during graded exercise and sustained exercise in the heat.

Measurement Accuracy of Heart Rate and Respiratory Rate during Graded Exercise and Sustained Exercise in the Heat Using the Zephyr BioHarness

Objective To determine the accuracy of wrist and arm-worn activity monitors’ estimates of energy expenditure (EE) Data sources SportDISCUS (EBSCOHost), PubMed, MEDLINE (Ovid), PsycINFO (EBSCOHost), Embase (Ovid) and CINAHL (EBSCOHost) Design A random effects meta-analysis was performed to evaluate the difference in EE estimates between activity monitors and criterion measurements Moderator analyses were conducted to determine the benefit of additional sensors and to compare the accuracy of devices used for research purposes with commercially available devices Eligibility criteria We included studies validating EE estimates from wrist-worn or arm-worn activity monitors against criterion measures (indirect calorimetry, room calorimeters and doubly labelled water) in healthy adult populations Results 60 studies (104 effect sizes) were included in the meta-analysis Devices showed variable accuracy depending on activity type Large and significant heterogeneity was observed for many devices (I2 >75%) Combining heart rate or heat sensing technology with accelerometry decreased the error in most activity types Research-grade devices were statistically more accurate for comparisons of total EE but less accurate than commercial devices during ambulatory activity and sedentary tasks Conclusions EE estimates from wrist and arm-worn devices differ in accuracy depending on activity type Addition of physiological sensors improves estimates of EE, and research-grade devices are superior for total EE These data highlight the need to improve estimates of EE from wearable devices, and one way this can be achieved is with the addition of heart rate to accelerometry PROSPEROregistration number CRD42018085016

https://bjsm.bmj.com/content/bjsports/54/6/332.full.pdf

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

Physiological condition monitoring of construction workers

Wristband-type wearable health devices to measure construction workers' physical demands

Feasibility analysis of heart rate monitoring of construction workers using a photoplethysmography (PPG) sensor embedded in a wristband-type activity tracker

The purpose of this investigation was to examine the relationships between aerobic fitness, volume of physical activity (PA), heart rate variability (HRV), and heart rate recovery (HRR) in a group of well-trained endurance athletes. Nineteen endurance athletes participated in this study and had aerobic capacities that placed them above the 99th percentile based on normative values (VO(2max): 67.1 ± 2 ml kg(-1) min(-1)). HRV was obtained via an EKG collected during supine rest and reported as high-frequency (HF), low-frequency (LF), and total power (TP). Natural log (ln) transformation was applied when variables violated assumptions of normality. HRR recovery was reported as the reduction in heart rate from peak exercise to the heart rate 1 min after cessation of exercise and PA was estimated from a questionnaire. HRR was significantly correlated with PA and VO(2max) (r = 0.67, P = 0.003 and 0.51, P = 0.039, respectively), but not with any index of HRV. Age was significantly correlated with lnHF (r = -0.49, P = 0.033), lnLF/lnHF (r = 0.48, P = 0.037), and normalized units (NU) of LF (r = 0.47, P = 0.042) and HF (r = -0.47, P = 0.042). Stepwise regression revealed that the strongest predictor of HRR was PA (R (2) = 0.45) and that VO(2max) did not add significant predictive value to the model. The relationship between HRV and age is evident in well-trained endurance athletes, whereas the relationship between HRV and PA/aerobic fitness is not. The maintained relationship between HRR and PA/aerobic fitness suggests that HRR may be a better marker of fitness-related differences in autonomic control in this population.

Dissociation of heart rate variability and heart rate recovery in well-trained athletes

The purpose of this study was to examine the accuracy of the ePulse Personal Fitness Assistant, a forearm-worn device that provides measures of heart rate and estimates energy expenditure. Forty-six participants engaged in 4-minute periods of standing, 2.0 mph walking, 3.5 mph walking, 4.5 mph jogging, and 6.0 mph running. Heart rate and energy expenditure were simultaneously recorded at 60-second intervals using the ePulse, an electrocardiogram (EKG), and indirect calorimetry. The heart rates obtained from the ePulse were highly correlated (intraclass correlation coefficients [ICCs] ≥0.85) with those from the EKG during all conditions. The typical errors progressively increased with increasing exercise intensity but were <5 bpm only during rest and 2.0 mph. Energy expenditure from the ePulse was poorly correlated with indirect calorimetry (ICCs: 0.01–0.36) and the typical errors for energy expenditure ranged from 0.69–2.97 kcal · min−1, progressively increasing with exercise intensity. These dat...

Accuracy of an infrared LED device to measure heart rate and energy expenditure during rest and exercise.

The purpose of this study was to examine the validity of treadmill handgrip sensors that provide real-time estimates of heart rate. Twenty-five individuals participated in 3-minute periods of standing, 2.0 mph walking, 3.5 mph walking, 4.5 mph jogging, and 6.0 mph running. Heart rate was simultaneously measured and recorded at 60-second intervals using the handgrip sensors and an electrocardiograph (EKG) which served as the criterion method. The heart rates obtained from the handgrip sensors were highly correlated with those from the EKG ( r ≥ 0.97) and the typical error was below 4 bpm for all measurements. Bland-Altman plots also revealed consistency between the handgrip sensors and EKG as the bias for heart rate ranged from -0.84 to 0.66 bpm and the 95% limits of agreement ranged from -7.15 to 6.87 bpm. However, the handgrip sensors exhibited a reduced ability to detect a heart rate during the 4.5 and 6.0 mph conditions as only 84% and 65.6% of heart rates were detected during these conditions, respectively. In conclusion, the handgrip sensors appear to be a valid device for monitoring heart rate while standing and during treadmill exercise involving walking and jogging in a healthy, young adult sample, although it may not be able to consistently detect a heart rate when body motion is excessive.

Accuracy of Handgrip Sensors to Measure Heart Rate during Rest and Exer-cise

/pdf/a-comparison-of-wrist-and-hip-accelerometer-output-at-lmjr91yc86.pdf

Albert Mendoza

Papers

Dissociation of heart rate variability and heart rate recovery in well-trained athletes

Accuracy of an infrared LED device to measure heart rate and energy expenditure during rest and exercise.

Accuracy of Handgrip Sensors to Measure Heart Rate during Rest and Exer-cise

A Comparison of Wrist and Hip Accelerometer Output at Different Walking Speeds: 2680 May 30, 2

The Relationship Between Intensity And Accelerometer Output From The Sqord, Zamzee, And Movband Activity Trackers: 1621 May 28, 2