How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough?

Evaluation of Wrist-Worn Photoplethysmography Trackers with an Electrocardiogram in Patients with Ischemic Heart Disease: A Validation Study

PURPOSE

Photoplethysmography measurement of heart rate with wrist-worn trackers has been introduced in healthy individuals. However, additional consideration is necessary for patients with ischemic heart disease, and the available evidence is limited. The study aims to evaluate the validity and reliability of heart rate measures by a wrist-worn photoplethysmography (PPG) tracker compared to an electrocardiogram (ECG) during incremental treadmill exercise among patients with ischemic heart disease.

METHODS

Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers.

RESULTS

At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent.

CONCLUSIONS

Low-cost trackers AMAZFIT Cor and Bip validity and reliability were within acceptable ranges, especially during low-intensity exercise among patients with ischemic heart disease recovering from cardiac procedures. Though using the tracker as part of the diagnosis tool still requires more supporting studies, it can potentially be used as a self-monitoring tool with precautions.

Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study

BACKGROUND

The integration of wearable devices into fitness routines, particularly in military settings, necessitates a rigorous assessment of their accuracy. This study evaluates the precision of heart rate measurements by locally manufactured wristbands, increasingly used in military academies, to inform future device selection for military training activities.

OBJECTIVE

This research aims to assess the reliability of heart rate monitoring in chest straps versus wearable wristbands.

METHODS

Data on heart rate and acceleration were collected using the Q-Band Q-69 smart wristband (Mobile Action Technology Inc) and compared against the Zephyr Bioharness standard measuring device. The Lin concordance correlation coefficient, Pearson product moment correlation coefficient, and intraclass correlation coefficient were used for reliability analysis.

RESULTS

Participants from a Northern Taiwanese medical school were enrolled (January 1-June 31, 2021). The Q-Band Q-69 demonstrated that the mean absolute percentage error (MAPE) of women was observed to be 13.35 (SD 13.47). Comparatively, men exhibited a lower MAPE of 8.54 (SD 10.49). The walking state MAPE was 7.79 for women and 10.65 for men. The wristband's accuracy generally remained below 10% MAPE in other activities. Pearson product moment correlation coefficient analysis indicated gender-based performance differences, with overall coefficients of 0.625 for women and 0.808 for men, varying across walking, running, and cooldown phases.

CONCLUSIONS

This study highlights significant gender and activity-dependent variations in the accuracy of the MobileAction Q-Band Q-69 smart wristband. Reduced accuracy was notably observed during running. Occasional extreme errors point to the necessity of caution in relying on such devices for exercise monitoring. The findings emphasize the limitations and potential inaccuracies of wearable technology, especially in high-intensity physical activities.

Assessing the Validity of Several Heart Rate Monitors in Wearable Technology While Mountain Biking

Purpose

This study sought to assess the validity of several heart rate (HR) monitors in wearable technology during mountain biking (MTB), compared to the Polar H7® HR monitor, used as the criterion device.

Methods

A total of 20 participants completed two MTB trials while wearing six HR monitors (5 test devices, 1 criterion). HR was recorded on a second-by-second basis for all devices analyzed. After data processing, validity measures were calculated, including 1. error analysis: mean absolute percentage errors (MAPE), mean absolute error (MAE), and mean error (ME), and 2. Correlation analysis: Lin's concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r). Thresholds for validity were set at MAPE < 10% and CCC > 0.7.

Results

The only device that was found to be valid during mountain biking was the Suunto Spartan Sport watch with accompanying HR monitor, with a MAPE of 0.66% and a CCC of 0.99 for the overall, combined data.

Conclusion

If a person would like to track their HR during mountain biking, for pacing, training, or other reasons, the devices best able to produce valid results are chest-based, wireless electrocardiogram (ECG) monitors, secured by elastic straps to minimize the movement of the device, such as the Suunto chest-based HR monitor.

Heart rate responses, agreement and accuracy among persons with severe disabilities participating in the indirect movement program: Team Twin-an observational study

Introduction

Heart rate (HR) monitors are rarely used by people living with disabilities (PLWD), and their accuracy is undocumented. Thus, this study aims to describe the HR response during the Team Twin co-running program and, secondly, to assess the agreement and accuracy of using HR monitors among PLWD.

Methods

This 16-week single-arm observational study included 18 people with various disabilities. During the study, the subjects wore a Garmin Vivosmart 4 watch (wrist). To evaluate the agreement and accuracy we applied Garmin's HRM-DUAL™ chest-worn HR monitors for comparison with the Vivosmart 4. The HR response analysis was performed descriptively and with a mixed regression model. The HR agreement and accuracy procedure was conducted on a subsample of five subjects and analyzed using Lin's concordance analysis, Bland and Altman's limits of agreement, and Cohen's kappa analysis of intensity zone agreement. This study was prospectively registered at Clinical Trials.gov (NCT04536779).

Results

The subjects had a mean age of 35 (±12.6), 61% were male, 72% had cerebral palsy were 85% had GMFCS V-IV. HR was monitored for 202:10:33 (HH:MM:SS), with a mean HR of 90 ± 17 bpm during training and race. A total of 19% of the time was spent in intensity zones between light and moderate (30%-59% HR reserve) and 1% in vigorous (60%-84% HR reserve). The remaining 80% were in the very light intensity zone (<29% HR reserve). HR was highest at the start of race and training and steadily decreased. Inter-rater agreement was high (k = 0.75), limits of agreement were between -16 and 13 bpm, and accuracy was acceptable (Rc = 0.86).

Conclusion

Disability type, individual, and contextual factors will likely affect HR responses and the agreement and accuracy for PLWD. The Vivosmart 4, while overall accurate, had low precision due to high variability in the estimation. These findings implicate the methodical and practical difficulties of utilizing HR monitors to measure HR and thus physical activity in adapted sports activities for severely disabled individuals.

Heart rate processing algorithms and exercise duration on reliability and validity decisions in biceps-worn Polar Verity Sense and OH1 wearables

Consumer wearable technology use is widespread and there is a need to validate measures obtained in uncontrolled settings. Because no standard exists for the treatment of heart rate data during exercise, the effect of different approaches on reliability (Coefficient of Variation [CV], Intraclass Correlation Coefficient [ICC]) and validity (Mean Absolute Percent Error [MAPE], Lin's Concordance Correlation Coefficient [CCC)] were determined in the Polar Verity Sense and OH1 during trail running. The Verity Sense met the reliability (CV < 5%, ICC > 0.7) and validity thresholds (MAPE < 5%, CCC > 0.9) in all cases. The OH1 met reliability thresholds in all cases except entire session average (ICC = 0.57). The OH1 met the validity MAPE threshold in all cases (3.3-4.1%), but not CCC (0.6-0.86). Despite various heart rate data processing methods, the approach may not affect reliability and validity interpretation provided adequate data points are obtained. It is also possible that a large volume of data will artificially inflate metrics.

Study protocol for a pilot trial analysing the usability, validity and safety of an interventional health app programme for the structured prehabilitation of patients before major surgical interventions: the PROTEGO MAXIMA trial

INTRODUCTION

Major surgery is associated with a high risk for postoperative complications, leading to an increase in mortality and morbidity, particularly in frail patients with a reduced cardiopulmonary reserve. Prehabilitation, including aerobic exercise training, aims to improve patients' physical fitness before major surgery and reduce postoperative complications, length of hospital stay and costs. The purpose of the study is to assess the usability, validity and safety of an app-based endurance exercise software in accordance with the Medical Device Regulation using wrist-worn wearables to measure heart rate (HR) and distance.

METHODS AND ANALYSIS

The PROTEGO MAXIMA trial is a prospective, interventional study with patients undergoing major elective surgery, comprising three tasks. Tasks I and II aim to assess the usability of the app, using evaluation questionnaires and usability scenarios. In Task IIIa, patients will undergo a structured risk assessment by the Patronus App, which will be correlated with the occurrence of postoperative complications after 90 days (non-interventional). In Task IIIb, healthy students and patients will perform a supervised 6 min walking test and a 37 min interval training on a treadmill based on HR reserve, wearing standard ECG limb leads and two smartwatches, which will be driven by the test software. The aim of this task is to assess the accuracy of HR measurement by the wearables and the safety, using specific alarm settings of the devices and lab testing of the participants (interventional).

ETHICS AND DISSEMINATION

Ethical approval was granted by the Institutional Review Board of the University Hospital of Frankfurt and by the Federal Institute for Pharmaceuticals and Medical Products (BfArM, reference number 94.1.04-5660-13655) on 7 February 2022. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings.

TRIAL REGISTRATION NUMBERS

European Database on Medical Devices (CIV-21-07-037311) and German Clinical Trial Registry (DRKS00026985).

Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?

The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.

Feasibility of Using an Armband Optical Heart Rate Sensor in Naturalistic Environment

Consumer-grade heart rate (HR) sensors including chest straps, wrist-worn watches and rings have become very popular in recent years for tracking individual physiological state, training for sports and even measuring stress levels and emotional changes. While the majority of these consumer sensors are not medical devices, they can still offer insights for consumers and researchers if used correctly taking into account their limitations. Multiple previous studies have been done using a large variety of consumer sensors including Polar® devices, Apple® watches, and Fitbit® wrist bands. The vast majority of prior studies have been done in laboratory settings where collecting data is relatively straightforward. However, using consumer sensors in naturalistic settings that present significant challenges, including noise artefacts and missing data, has not been as extensively investigated. Additionally, the majority of prior studies focused on wrist-worn optical HR sensors. Arm-worn sensors have not been extensively investigated either. In the present study, we validate HR measurements obtained with an arm-worn optical sensor (Polar OH1) against those obtained with a chest-strap electrical sensor (Polar H10) from 16 participants over a 2-week study period in naturalistic settings. We also investigated the impact of physical activity measured with 3-D accelerometers embedded in the H10 chest strap and OH1 armband sensors on the agreement between the two sensors. Overall, we find that the arm-worn optical Polar OH1 sensor provides a good estimate of HR (Pearson r = 0.90, p <0.01). Filtering the signal that corresponds to physical activity further improves the HR estimates but only slightly (Pearson r = 0.91, p <0.01). Based on these preliminary findings, we conclude that the arm-worn Polar OH1 sensor provides usable HR measurements in daily living conditions, with some caveats discussed in the paper.

Wearable-Measured Sleep and Resting Heart Rate Variability as an Outcome of and Predictor for Subjective Stress Measures: A Multiple N-of-1 Observational Study

The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15-55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.

Accuracy of the Apple Watch Series 6 and the Whoop Band 3.0 for assessing heart rate during resistance exercises

This study aimed to determine heart rate accuracy measured by wearable devices during resistance exercises at various intensities. Twenty-nine participants (16 female) aged 19-37 years participated in this cross-sectional study. Participants completed five resistance exercises; Barbell Back Squat, Barbell Deadlift, Dumbbell Curl to Overhead Press, Seated Cable Row, and Burpees. During the exercises, heart rate was concurrently measured using the Polar H10, the Apple Watch Series 6 and the Whoop 3.0. The Apple Watch had high agreement with the Polar H10 during Barbell Back Squats, Barbell Deadlift, and Seated Cable Rows (rho > 0.832) and moderate to low agreement during Dumbbell Curl to Overhead Press and Burpees (rho > 0.364). The Whoop Band 3.0 had high agreement with the Polar H10 during Barbell Back Squats (r > 0.697), moderate agreement during Barbell Deadlift and Dumbbell Curl to Overhead Press (rho > 0.564) and low agreement during Seated Cable Rows and Burpees (rho > 0.383). The results varied across exercises and intensities and indicated the most favourable outcomes for the Apple Watch. In conclusion, our data suggest that the Apple Watch Series 6 is suitable for measuring heart rate during exercise prescription or monitoring resistance exercise performance.

Assessing mental workload with wearable devices - Reliability and applicability of heart rate and motion measurements

Wearable devices are increasingly used for assessing physiological data. Industry 4.0 aims to achieve the real-time assessment of the workers' condition to adapt processes including the current mental workload. Mental workload can be assessed via physiological data. This paper researches the potential of wearable devices for mental workload assessment by utilizing heart rate and motion data collected with a smartwatch. A laboratory study was conducted with four levels of mental workload, ranging from none to high and during sitting and stepping activities. When sitting, a difference in the heart rate and motion data from the smartwatch was only found between no mental workload and any mental workload task. For the stepping condition, differences were found for the movement data. Based on these results, wearable devices could be useful in the future for detecting whether a mental demanding task is currently performed during low levels of physical activity.

The association between sleep deficits and sedentary behavior in people with mild Parkinson disease

Purpose: Sleep deficits are a common nonmotor symptom of Parkinson disease (PD). People with mild PD also achieve less physical activity (PA) than healthy older adults (HOA), but the relationship between sleep and PA in PD is unclear. This study examined associations between sleep and PA in participants with PD and HOA.Materials and Methods: Secondary analysis of a prospective observational study. Participants wore a commercially available activity monitor for two weeks. Wilcoxon Rank-Sum tests compared nighttime sleep, wakenings after sleep onset, number of wakenings, naps, step count, and PA intensity between PD and HOA groups. Age-adjusted regression models calculated associations between nighttime sleep and PA.Results: Per day, participants with PD slept 75 fewer minutes (p < 0.01), took 5,792 fewer steps (p < 0.001), achieved less PA at all intensities, and had 32% more sedentary time (p < 0.001) compared to HOA. Thirty minutes more sleep was associated with 26 fewer sedentary minutes for HOA (p = 0.01) and 25 fewer sedentary minutes for the PD group (p < 0.001).Conclusions: Sleep and PA are reduced in mild PD compared to HOA. Both groups demonstrated similar associations between reduced sleep and increased sedentary behavior. Results may encourage providers to screen for sleep deficits when promoting PA.IMPLICATIONS FOR REHABILITATIONThe use of a wrist-worn commercial activity and sleep monitor was well tolerated by both healthy older adults and people with mild Parkinson Disease in this study.People with mild Parkinson Disease slept less and were less active than a group of healthy older adults.Less sleep was associated with more sedentary behavior in both groups.The relationship between poor sleep and sedentary behavior in mild Parkinson Disease suggests that rehabilitation interventions may be optimized by targeting both physical activity and sleep deficits.

Generating Alerts from Breathing Pattern Outliers

Analysing human physiological data allows access to the health state and the state of mind of the subject individual. Whenever a person is sick, having a panic attack, happy or scared, physiological signals will be different. In terms of physiological signals, we focus, in this manuscript, on monitoring breathing patterns. The scope can be extended to also address heart rate and other variables. We describe an analysis of breathing rate patterns during activities including resting, walking, running and watching a movie. We model normal breathing behaviours by statistically analysing signals, processed to represent quantities of interest. We consider moving maximum/minimum, the amplitude and the Fourier transform of the respiration signal, working with different window sizes. We then learn a statistical model for the basal behaviour, per individual, and detect outliers. When outliers are detected, a system that incorporates our approach would send a visible signal through a smart garment or through other means. We describe alert generation performance in two datasets-one literature dataset and one collected as a field study for this work. In particular, when learning personal rest distributions for the breathing signals of 14 subjects, we see alerts generated more often when the same individual is running than when they are tested in rest conditions.

Re-Visiting Maximal Heart Rate Prediction Using Cross-Validation in Population Aged 7–55 Years

The primary purpose of the present study was to re-visit HR_max prediction by two commonly used equations (i.e., Fox′s and Tanaka′s equation) compared to the direct measured HR_max using the large sample size of Asians. The second aim of the study was to focus on suggesting new equations for the Asian population by separating gender and specific age groups. A total of 672 participants aged from 7 to 55 years were recruited for the study (male: 280 and female: 392), and the maximal graded exercise test with Bruce protocol was used to measure HR_max. All data obtained from the study were analyzed by SPSS 25.0. Additionally, three statistical analysis methods (i.e., Mean Absolute Percent Errors (MAPE), Bland–Altman plots, and equivalence testing) were utilized to confirm the consistency between the measured HR_max and the two prediction equations. The main finding was that two equations showed significant differences in predicting the HR_max of Korean aged from 7 to 55 years. The outcome of children aged from 7 to 14 was a different fit in the agreement compared to other age groups. Fox′s equation had the best fit in the average of the difference closer to zero and completely included within the equivalence zone, but females over 15 years old revealed higher errors than males in the values calculated by the two equations compared to the direct measured HR_max. Consequently, the study demonstrated that both equations tended to overestimate the HR_max for males and females over 15 years old, and the two universal equations were not suitable to predict the HR_max of Koreans except for children aged from 7 to 14 years. The new HR_max prediction equations suggested in this study will more accurately predict the HR_max of Asians, and additional analyses should be examined the cross-validity of the developed HR_max equation by age and gender in the future study.

Wearables in Sports Cardiology

The expanding array and adoption of consumer health wearables is creating a new dynamic to the patient-health-care provider relationship. Providers are increasingly tasked with integrating the biometric data collected from their patients into clinical care. Further, a growing body of evidence is supporting the provider-driven utility of wearables in the screening, diagnosis, and monitoring of cardiovascular disease. Here we highlight existing and emerging wearable health technologies and the potential applications for use within sports cardiology. We additionally highlight how wearables can advance the remote cardiovascular care of patients within the context of the COVID-19 pandemic. Finally, despite these promising advances, we acknowledge some of the significant challenges that remain before wearables can be routinely incorporated into clinical care.

Global Positioning System Watches and Electronic Journals: Are Training-Load Measures Similar in High School Cross-Country Runners?

PURPOSE

Running programs are designed to progress training loads by manipulating the duration, frequency, and/or intensity of running sessions. While some studies use journals to monitor training load, others have used wearable technology. The purpose of this study was to compare the validity of self-reported and global positioning system (GPS)-watch-derived measures of external and internal loads in high school cross-country runners.

METHODS

Twenty-two high school cross-country runners participated in the study during fall 2020. Participants recorded running sessions using a GPS watch and self-reported the running session using an electronic journal. External (distance and duration) and internal loads (session rating of perceived exertion [sRPE], average, and maximum heart rate) were retrieved from the GPS watch and electronic journal. Correlations compared relationships, and Bland-Altman plots compared agreements between GPS-watch-derived and self-reported measures of training loads.

RESULTS

We found moderate relationships between self-reported and GPS-watch-derived measures of external loads (distance: r = .76, moving duration: r = .74, and elapsed duration: r = .70) and poor relationships between internal loads (sRPE vs average heart rate: ρ = .11, sRPE vs maximal heart rate: ρ = .13). We found mean differences of -0.8 km (95% = -6.3 to +4.8 km) for distance, -4.5 minutes (95% = -27.8 to +33.2 min) for moving duration, and 2.7 minutes (95% = -27.8 min to +33.2 min) for elapsed duration.

CONCLUSIONS

High school runners overreported running distance and duration using self-reports, and self-reported and GPS-watch-derived measures of internal loads demonstrated poor agreement. Coaches and clinicians should use caution when comparing results from studies using different methods of monitoring training loads.

Time Synchronization of Multimodal Physiological Signals through Alignment of Common Signal Types and Its Technical Considerations in Digital Health

Background: Despite advancements in digital health, it remains challenging to obtain precise time synchronization of multimodal physiological signals collected through different devices. Existing algorithms mainly rely on specific physiological features that restrict the use cases to certain signal types. The present study aims to complement previous algorithms and solve a niche time alignment problem when a common signal type is available across different devices. Methods: We proposed a simple time alignment approach based on the direct cross-correlation of temporal amplitudes, making it agnostic and thus generalizable to different signal types. The approach was tested on a public electrocardiographic (ECG) dataset to simulate the synchronization of signals collected from an ECG watch and an ECG patch. The algorithm was evaluated considering key practical factors, including sample durations, signal quality index (SQI), resilience to noise, and varying sampling rates. Results: The proposed approach requires a short sample duration (30 s) to operate, and demonstrates stable performance across varying sampling rates and resilience to common noise. The lowest synchronization delay achieved by the algorithm is 0.13 s with the integration of SQI thresholding. Conclusions: Our findings help improve the time alignment of multimodal signals in digital health and advance healthcare toward precise remote monitoring and disease prevention.

Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis

BACKGROUND

Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge.

OBJECTIVE

The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits.

METHODS

We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps.

RESULTS

A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively).

CONCLUSIONS

Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.

Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

Remote monitoring and control of heart function are of primary importance for patient evaluation and management, especially in the modern era of precision medicine and personalized approach. Breaking technological developments have brought to the frontline a variety of smart wearable devices, such as smartwatches, chest patches/straps, or sensors integrated into clothing and footwear, which allow continuous and real-time recording of heart rate, facilitating the detection of cardiac arrhythmias. However, there is great diversity and significant differences in the type and quality of the information they provide, thus impairing their integration into daily clinical practice and the relevant familiarization of practicing physicians. This review will summarize the different types and dominant functions of cardiac smart wearables available in the market. Furthermore, we report the devices certified by official American and/or European authorities and the respective sources of evidence. Finally, we comment pertinent limitations and caveats as well as the potential answers that flow from the latest technological achievements and future perspectives.

Accuracy of heart rate measurements of three smartwatch models in dogs

This study was aimed to evaluate the accuracy of heart rate (HR) measurements using three smartwatch models designed for human use when applied to dogs. A group of 15 mixed breed dogs, ages ranging from 2 to 3 years, weighing between 20 and 30 kg were used. The Garmin Fenix 5X plus (GF5Xp), Samsung Gear S3 (SGS3), and Polygold A-6 (PDA6), were randomly placed on the tibia of dogs to collect the HR recordings every 5 minutes for 1 hour. A veterinary patient monitor (VPM) was used as the reference method. A Bland-Altman plot was applied to determine the difference between smartwatches. The receiver operating characteristic curves were developed analysis for sensitivity and specificity. The HR measured by VPM ranged from 65 to 200 bpm (mean, 149.3 ± 28.1 bpm; median, 154 bpm). Among the smartwatches, the lowest (44 bpm) HR was measured by PDA6, while the highest (201 bpm) was measured by SGS3. Among the smartwatches; GF5Xp and SGS3 had slopes equal to 1 and residual standard deviation closer to 0, in agreement with VPM. At the cut-off HR (160 bpm), SGS3 had the highest sensitivity (97.4%), whereas PDA6 had the lowest sensitivity (68.0%). The specificity of GF5Xp, SGS3, and PDA6 was 97.1%, 98.0%, and 98.0%, respectively. The SGS3 and GF5Xp can be ideal tools for veterinarians to monitor the HR of dogs without requiring an additional device.

Duration of an acute moderate-intensity exercise session affects approach bias toward high-calorie food among individuals with obesity

Obesity is partly driven by unhealthy eating behaviors underpinned by an approach bias toward high-calorie food. Although exercise is a useful strategy for weight loss among individuals with obesity, whether exercise modulates this approach bias is unclear. This study assessed whether the duration of an acute moderate-intensity exercise altered the approach bias toward high-calorie food among individuals with obesity. In total, 24 individuals with obesity were included in this study with a randomized, counterbalanced, crossover design. Participants completed three sessions of 30, 45, or 60 minutes of moderate-intensity exercise (40%-59% of heart rate reserve) on an elliptical trainer or completed a control rest session for 55 minutes. Food approach bias was evaluated using a joystick-based approach-avoidance task immediately before and after each session. Two-way repeated-measures analysis of variance was used to analyze the data. We found that compared with that before exercise, the approach bias score toward high-calorie food was significantly decreased only in the 45-minute exercise session (p = .015) and that this score was also significantly lower than that after both the 60-minute exercise session (p = .002) and the control session (p = .024). These findings suggest a dose-response relationship between exercise duration and approach bias, with 45 minutes of moderate-intensity exercise being an effective strategy for decreasing the approach bias toward high-calorie food among individuals with obesity.

Six-Month Community-Based Brisk Walking and Balance Exercise Alleviates Motor Symptoms and Promotes Functions in People with Parkinson's Disease: A Randomized Controlled Trial

BACKGROUND

In Parkinson's disease (PD), sustained aerobic exercise is a promising therapy in delaying motor disability. Brisk walking is a moderate intensity aerobic training, which could be translated to community practice at low cost, but its effects on motor symptoms remains unclear.

OBJECTIVE

To determine the effectiveness of a six-month brisk walking and balance program in alleviating motor symptoms, and promoting functional, gait, and balance performance in people with PD.

METHODS

Seventy individuals with mild to moderate PD were randomly assigned to a brisk walking (BW) group or an active control (CON) group. BW group received ten 90-minute supervised brisk walking and balance exercise for six months (weeks 1-6: once/week, weeks 7-26: once/month). CON group received upper limb training. Both groups performed 2-3 self-practice sessions weekly. Primary outcome was Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor score. Secondary outcomes were fast gait speed (FGS), timed-up-and-go (TUG) time, six-minute walk distance (6MWD), and Mini-Balance Evaluation Systems Test (Mini-BEST) score.

RESULTS

Sixty-four participants (33 BW/31 CON) completed training. BW group showed greater significant decreases from baseline than CON group in MDS-UPDRS motor score after six weeks (-5.5 vs -1.6, p < 0.001) and 6 months (-6.0 vs -1.4, p < 0.001) of training. BW group also showed greater significant improvement from the baseline than CON group for TUG time, FGS, 6MWD, and mini-BEST score (all p < 0.05).

CONCLUSION

The six-month brisk walking and balance program alleviates motor symptoms, promotes functional and gait performance, walking capacity, and dynamic balance in people with mild to moderate PD.

Accuracy of wrist-worn wearable devices for determining exercise intensity

Objective

As an indicator of exercise intensity, heart rate can be measured in a timely manner using wrist-worn devices. No study has attempted to estimate a target exercise intensity using wearable devices. The objective of the study was to evaluate the validity of prescribing exercise intensity using wrist-worn devices.

Methods

Thirty healthy subjects completed a maximal cardiopulmonary exercise test. Their heart rates were recorded using an electrocardiogram and two devices—Apple Watch Series 6 and Garmin Forerunner 945. Exercise intensity with the target heart rate was defined as resting heart rate + (maximal heart rate − resting heart rate) * n% ( n%: 40–60% for moderate-intensity exercise and 60–89% for vigorous-intensity exercise). Heart rate was analyzed at the lower and upper limits of each exercise intensity (HR40, HR60, and HR89). The mean absolute percentage error and concordance correlation coefficient were calculated, and Bland–Altman plots and scatterplots were constructed.

Results

Both devices showed a low mean absolute error (1.16–1.48 bpm for Apple and 1.35–2.25 for Garmin) and mean absolute percentage error (<1% for Apple and 1.16–1.39% for Garmin) in all intensities. A substantial correlation with electrocardiogram-measured heart rate was observed for moderate to vigorous intensity with concordance correlation coefficient > 0.95 for both devices, except that Garmin showed moderate correlation at the upper limit of vigorous activity with concordance correlation coefficient = 0.936. Moreover, Bland–Altman plots and scatterplots demonstrated a strong correlation without systematic error when the values obtained via the two devices were compared with electrocardiogram measurements.

Conclusions

Our findings indicate the high validity of exercise prescriptions based on the heart rate measured by the two devices. Additional research should explore other populations to confirm these findings.

Evaluating commercially available wireless cardiovascular monitors for measuring and transmitting real-time physiological responses in children with autism

Commercially available wearable biosensors have the potential to enhance psychophysiology research and digital health technologies for autism by enabling stress or arousal monitoring in naturalistic settings. However, such monitors may not be comfortable for children with autism due to sensory sensitivities. To determine the feasibility of wearable technology in children with autism age 8-12 years, we first selected six consumer-grade wireless cardiovascular monitors and tested them during rest and movement conditions in 23 typically developing adults. Subsequently, the best performing monitors (based on data quality robustness statistics), Polar and Mio Fuse, were evaluated in 32 children with autism and 23 typically developing children during a 2-h session, including rest and mild stress-inducing tasks. Cardiovascular data were recorded simultaneously across monitors using custom software. We administered the Comfort Rating Scales to children. Although the Polar monitor was less comfortable for children with autism than typically developing children, absolute scores demonstrated that, on average, all children found each monitor comfortable. For most children, data from the Mio Fuse (96%-100%) and Polar (83%-96%) passed quality thresholds of data robustness. Moreover, in the stress relative to rest condition, heart rate increased for the Polar, F(1,53) = 135.70, p < 0.001, ηp²  = 0.78, and Mio Fuse, F(1,53) = 71.98, p < 0.001, ηp²  = 0.61, respectively, and heart rate variability decreased for the Polar, F(1,53) = 13.41, p = 0.001, ηp²  = 0.26, and Mio Fuse, F(1,53) = 8.89, p = 0.005, ηp²  = 0.16, respectively. This feasibility study suggests that select consumer-grade wearable cardiovascular monitors can be used with children with autism and may be a promising means for tracking physiological stress or arousal responses in community settings. LAY SUMMARY: Commercially available heart rate trackers have the potential to advance stress research with individuals with autism. Due to sensory sensitivities common in autism, their comfort wearing such trackers is vital to gathering robust and valid data. After assessing six trackers with typically developing adults, we tested the best trackers (based on data quality) in typically developing children and children with autism and found that two of them met criteria for comfort, robustness, and validity.

Predicting Chronic Stress among Healthy Females Using Daily-Life Physiological and Lifestyle Features from Wearable Sensors

Background

Chronic stress is a highly prevalent condition that may stem from different sources and can substantially impact physiology and behavior, potentially leading to impaired mental and physical health. Multiple physiological and behavioral lifestyle features can now be recorded unobtrusively in daily-life using wearable sensors. The aim of the current study was to identify a distinct set of physiological and behavioral lifestyle features that are associated with elevated levels of chronic stress across different stress sources.

Methods

For that, 140 healthy female participants completed the Trier inventory for chronic stress (TICS) before wearing the Fitbit Charge3 sensor for seven consecutive days while maintaining their daily routine. Physiological and lifestyle features that were extracted from sensor data, alongside demographic features, were used to predict high versus low chronic stress with support vector machine classifiers, applying out-of-sample model testing.

Results

The model achieved 79% classification accuracy for chronic stress from a social tension source. A mixture of physiological (resting heart-rate, heart-rate circadian characteristics), lifestyle (steps count, sleep onset and sleep regularity) and non-sensor demographic features (smoking status) contributed to this classification.

Conclusion

As wearable technologies continue to rapidly evolve, integration of daily-life indicators could improve our understanding of chronic stress and its impact of physiology and behavior.

Reference Values for Wristband Accelerometry Data in Children Aged 6-11 Years of Age

OBJECTIVES

Wristband activity trackers (accelerometers) could serve as a convenient monitoring tool to continuously quantify physical activity throughout the day. We aim to provide reference values for the use of these devices in healthy children.

METHODS

Children were recruited at a local school and provided with activity trackers (Fitbit Charge 2). Pupils were instructed to wear devices during all normal daytime activities over a period of 11-15 days. Demographic data, total number of daily steps and heart rate were recorded. In addition, all children/parents were asked to complete a questionnaire providing information about daily physical routine (mode of transport to school, sporting activities as well as sport club memberships).

RESULTS

Three hundred two children (54.6% boys; median age 8.7 years) participated in this prospective study. Median wearing time of the device was 12.1 h/day. Overall, the median daily total step count was 12,095. Median step counts/day were significantly higher in boys compared to girls (13,015 vs. 11,305 steps/day; p < 0.0001). In addition, step counts were significantly higher during the week, compared to weekend days. The effect of age on daily step count was found to be non-linear: the total daily step count increased from 6 to 8.5 years of age, while older children (aged >8.5 years) had lower step counts compared to the younger children. Significant predictors of the daily step count were male gender (+1,324.9 steps, p = 0.0008), mode of transportation to school (walking, bicycle, scooter: +865.5 steps p = 0.049), active membership in a sports club (+1,324.9 steps/day, p = 0.0008), and number of structured units of physical exercise performed (+336.5/per 45 min, p < 0.0001). Severe obesity was associated with a significant reduction in total daily step count (-3037.7 steps/day, p = 0.015).

CONCLUSION

Our prospective cohort study of healthy school children provides reference values for wristband accelerometers in normal individuals. In addition, it clarifies the effect of age, body weight and lifestyle on normal daily step counts in school children. This data should be helpful to judge the degree of physical limitation of patients compared to healthy peers.

Step Number and Aerobic Minute Exercise Prescription and Progression in Stroke: A Roadmap

Background

While higher therapeutic intensity improves motor recovery after stroke, translating findings from successful studies is challenging without clear exercise intensity targets. We show in the DOSE trial¹ more than double the steps and aerobic minutes within a session can be achieved compared with usual care and translates to improved long-term walking outcomes.

Objective

We modeled data from this successful higher intensity multi-site RCT to develop targets for prescribing and progressing exercise for varying levels of walking impairment after stroke.

Methods

In twenty-five individuals in inpatient rehabilitation, twenty sessions were monitored for a total of 500 one-hour physical therapy sessions. For the 500 sessions, step number and aerobic minute progression were modeled using linear mixed effects regression. Using formulas from the linear mixed effects regression, targets were calculated.

Results

The model for step number included session number and baseline walking speed, and for aerobic minutes, session number and age. For steps, there was an increase of 73 steps per session. With baseline walking speed, for every 0.1 m/s increase, a corresponding increase of 302 steps was predicted. For aerobic minutes, there was an increase of .56 minutes of aerobic activity (ie, 34 seconds) per session. For every year increase in age, a decrease of .39 minutes (ie, 23 seconds) was predicted.

Conclusions

Using data associated with better walking outcomes, we provide step number and aerobic minute targets that future studies can cross-validate. As walking speed and age are collected at admission, these models allow for uptake of routine measurement of therapeutic intensity.

Registration: www.clinicaltrials.gov; NCT01915368.

Wristbands in Home-Based Rehabilitation-Validation of Heart Rate Measurement

The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.

A Multi-Systems Approach to Human Movement after ACL Reconstruction: The Cardiopulmonary System

The cardiopulmonary system plays a pivotal role in athletic and rehabilitative activities following anterior cruciate ligament reconstruction, along with serving as an important support for the functioning of other physiologic systems including the integumentary, musculoskeletal, and nervous systems. Many competitive sports impose high demands upon the cardiorespiratory system, which requires careful attention and planning from rehabilitation specialists to ensure athletes are adequately prepared to return to sport. Cardiopulmonary function following anterior cruciate ligament reconstruction (ACLR) can be assessed using a variety of methods, depending on stage of healing, training of the clinician, and equipment availability. Reductions in cardiovascular function may influence the selection and dosage of interventions that are not only aimed to address cardiopulmonary impairments, but also deficits experienced in other systems that ultimately work together to achieve goal-directed movement. The purpose of this clinical commentary is to present cardiopulmonary system considerations within a multi-physiologic systems approach to human movement after ACLR, including a clinically relevant review of the cardiopulmonary system, assessment strategies, and modes of cardiopulmonary training to promote effective, efficient movement.

LEVEL OF EVIDENCE

5.

Examining the Accuracy of the Polar A360 Monitor

ABSTRACT

Rider, BC, Conger, SA, Ditzenberger, GL, Besteman, SS, Bouret, CM, and Coughlin, AM. Examining the accuracy of the Polar A360 monitor. J Strength Cond Res 35(8): 2165-2169, 2021-The purpose of this study was to determine the accuracy of the Polar A360 heart rate (HR) monitor during periods of rest, walking/running, and active/passive recovery from exercise. Thirty collegiate athletes (women n = 15 and men n = 15) wore an A360 monitor and a previously validated chest HR monitor (Polar RS400) that served as the criterion measurement across a range of resting and walking/running intensities. First, subjects rested in a supine, seated, and standing position. Next, each subject walked on a treadmill at 1.6 kilometers per hour (kph). Speed was increased by 1.6 kph every 2 minutes until volitional fatigue. Then, subjects walked at 4.8 kph followed by a seated recovery stage. Heart rate was recorded in 30-second increments. Total mean difference in HR readings, percent accuracy, and intraclass correlation coefficient (ICC) analysis established the level of agreement between devices. Bland-Altman plots and a regression were used to examine the agreement between devices. The A360 demonstrated a strong correlation with the RS400 (r2 = 0.98) across time points. The analysis of variance with repeated measures indicated an overall significant difference (p < 0.001) between devices. The A360 significantly underestimated HR during the 6.4-kph speed only (p < 0.05) (effect size 0.26). The greatest percent accuracy occurred during rest (91%) and recovery (90%). An ICC of 0.98 (SEM: 0.35) demonstrates a strong level of agreement between devices. The A360 is accurate at rest and during various walking and running speeds and thus is a device that can be used with confidence by athletes for specific training purposes. Future research should examine accuracy during weight training and other sport-specific activities.

Cross-instrument feasibility, validity, and reproducibility of wireless heart rate monitors: Novel opportunities for extended daily life monitoring

Wired ambulatory monitoring of the electrocardiogram (ECG) is an established method used by researchers and clinicians. Recently, a new generation of wireless, compact, and relatively inexpensive heart rate monitors have become available. However, before these monitors can be used in scientific research and clinical practice, their feasibility, validity, and reproducibility characteristics have to be investigated. Therefore, we tested how two wireless heart rate monitors (i.e., the Ithlete photoplethysmography (PPG) finger sensor and the Cortrium C3 ECG monitor perform against an established wired reference method (the VU-AMS ambulatory ECG monitor). Monitors were tested on cross-instrument and test-retest reproducibility in a controlled laboratory setting, while feasibility was evaluated in protocolled ambulatory settings at home. We found that the Cortrium and the Ithlete monitors showed acceptable agreement with the VU-AMS reference in laboratory setting. In ambulatory settings, assessments were feasible with both wireless devices although more valid data were obtained with the Cortrium than with the Ithlete. We conclude that both monitors have their merits under controlled laboratory settings where motion artefacts are minimized and stationarity of the ECG signal is optimized by design. These findings are promising for long-term ambulatory ECG measurements, although more research is needed to test whether the wireless devices' feasibility, validity, and reproducibility characteristics also hold in unprotocolled daily life settings with natural variations in posture and activities.

Demonstrating the Applicability of Smartwatches in PM2.5 Health Impact Assessment

Smartwatches are being increasingly used in research to monitor heart rate (HR). However, it is debatable whether the data from smartwatches are of high enough quality to be applied in assessing the health impacts of air pollutants. The objective of this study was to assess whether smartwatches are useful complements to certified medical devices for assessing PM_2.5 health impacts. Smartwatches and medical devices were used to measure HR for 7 and 2 days consecutively, respectively, for 49 subjects in 2020 in Taiwan. Their associations with PM_2.5 from low-cost sensing devices were assessed. Good correlations in HR were found between smartwatches and certified medical devices (r_s > 0.6, except for exercise, commuting, and worshipping). The health damage coefficients obtained from smartwatches (0.282% increase per 10 μg/m³ increase in PM_2.5) showed the same direction, with a difference of only 8.74% in magnitude compared to those obtained from certified medical devices. Additionally, with large sample sizes, the health impacts during high-intensity activities were assessed. Our work demonstrates that smartwatches are useful complements to certified medical devices in PM_2.5 health assessment, which can be replicated in developing countries.

Panomics: New Databases for Advancing Cardiology

The multifactorial nature of cardiology makes it challenging to separate noisy signals from confounders and real markers or drivers of disease. Panomics, the combination of various omic methods, provides the deepest insights into the underlying biological mechanisms to develop tools for personalized medicine under a systems biology approach. Questions remain about current findings and anticipated developments of omics. Here, we search for omic databases, investigate the types of data they provide, and give some examples of panomic applications in health care. We identified 104 omic databases, of which 72 met the inclusion criteria: genomic and clinical measurements on a subset of the database population plus one or more omic datasets. Of those, 65 were methylomic, 59 transcriptomic, 41 proteomic, 42 metabolomic, and 22 microbiomic databases. Larger database sample sizes and longer follow-up are often better suited for panomic analyses due to statistical power calculations. They are often more complete, which is important when dealing with large biological variability. Thus, the UK BioBank rises as the most comprehensive panomic resource, at present, but certain study designs may benefit from other databases.

Exercise load and physical activity intensity in relation to dystonia and choreoathetosis during powered wheelchair mobility in children and youth with dyskinetic cerebral palsy

PURPOSE

To explore the relation between exercise load, physical activity intensity, and movement disorders during powered wheelchair (PW) mobility in people with severe dyskinetic cerebral palsy (DCP).

METHODS

Ten participants with DCP, 6-21 years old, users of a head/foot steering system were included. Dystonia and choreoathetosis were assessed using the Dyskinesia Impairment Mobility Scale (DIMS), heart rate (HR) was used to assess the exercise load of the tasks on the participants, and the accelerometry-based activity index (AI) to measure the physical activity intensity and energy expenditure during mobility task performance.

RESULTS

Neck- and distal arm dystonia showed significant correlations with HR (0.64 < r_s < 0.77; 0.009 < p < 0.048), whereas neck- and proximal arm choreoathetosis with AI (0.64 < r_s < 0.76, 0.011 < p < 0.044). Total-body AI was strongly correlated to the AI of the arms (0.66 < r_s < 0.90,  < 0.001 < p < 0.038), but not to the AI of the head.

CONCLUSIONS

During PW mobility tasks, dystonia is associated to exercise load and choreoathetosis to physical activity intensity and energy expenditure. Findings highlight the difficulties in measuring exercise load and activity intensity in PW users with DCP due to the involuntary hypertonic and/or hyperkinetic hallmark of the movement disorders. Nevertheless, a relaxed surrounding with minimal distractions during PW training may increase learning efficiency. Future studies with a bigger sample size are highly recommended to fully establish the relationship between the variables and to allow generalizability of results.Implications for rehabilitationDystonia is positively related to heart rate during powered mobility, which may be explained by the hypertonic hallmark of dystonia causing an increase in exercise load.Choreoathetosis is positively related to the physical activity index during powered mobility where the hyperkinetic hallmark of choreoathetosis may lead to an increase in physical activity intensity and energy expenditure.Arm overflow movements are the component which contribute the most to total-body activity index, thus, minimizing these movements may lower the overall energy expenditure during powered mobility.Mobility training in a relaxed surrounding with minimal distractions and minimized arm overflow movements may lead to a less-demanding powered wheelchair mobility experience and increased learning efficiency.

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

Predicting maximal oxygen uptake from a 3-minute progressive knee-ups and step test

Background

Cardiorespiratory fitness assessment is crucial for diagnosing health risks and assessing interventions. Direct measurement of maximum oxygen uptake (V̇O₂ max) yields more objective and accurate results, but it is practical only in a laboratory setting. We therefore investigated whether a 3-min progressive knee-up and step (3MPKS) test can be used to estimate peak oxygen uptake in these settings.

Method

The data of 166 healthy adult participants were analyzed. We conducted a V̇O₂ max test and a subsequent 3MPKS exercise test, in a balanced order, a week later. In a multivariate regression model, sex; age; relative V̇O₂ max; body mass index (BMI); body fat percentage (BF); resting heart rate (HR0); and heart rates at the beginning as well as at the first, second, third, and fourth minutes (denoted by HR0, HR1, HR2, HR3, and HR4, respectively) during a step test were used as predictors. Moreover, R² and standard error of estimate (SEE) were used to evaluate the accuracy of various body composition models in predicting V̇O₂max.

Results

The predicted and actual V̇O₂ max values were significantly correlated (BF% model: R² = 0.624, SEE = 4.982; BMI model: R² = 0.567, SEE = 5.153). The BF% model yielded more accurate predictions, and the model predictors were sex, age, BF%, HR0, ΔHR3−HR0, and ΔHR3−HR4.

Conclusion

In our study, involving Taiwanese adults, we constructed and verified a model to predict V̇O₂ max, which indicates cardiorespiratory fitness. This model had the predictors sex, age, body composition, and heart rate changes during a step test. Our 3MPKS test has the potential to be widely used in epidemiological research to measure V̇O₂ max and other health-related parameters.

Data from Digital Health Devices Informs Ideal Cardiovascular Health

Ideal cardiovascular health is associated with a decrease in adverse cardiovascular events. The My Research Legacy study examined ideal cardiovascular health using the Life's Simple 7 survey and data from digital health devices. We hypothesized that digital devices provide a more objective view of overall cardiovascular health status than self-reported measures. Therefore, we analyzed weight and activity data recorded by digital devices to recalculate the Life's Simple 7 Health Score. All study participants (n = 1561) answered the survey, while a subgroup (n = 390) provided data from digital devices. Individuals with digital devices had a lower body mass index (BMI) and higher weekly minutes of vigorous exercise than participants without digital devices (p < 0.01). Baseline Health Scores were higher in individuals with digital devices compared to those without (7.0 ± 1.6 vs. 6.6 ± 1.6, p < 0.01). Data from digital devices reveal both increases and decreases in measured vs. self-reported BMI (p < 0.04) and weekly minutes of moderate and vigorous exercise activity (p < 0.01). Using these data, a significant difference was found between the recalculated and the self-reported Life's Simple 7 Health Score (p < 0.05). These findings suggest that incorporation of digital health devices should be considered as part of a precision medicinal approach to assessing ideal cardiovascular health.

Intensity of usual care physical therapy during inpatient rehabilitation for people with neurologic diagnoses

BACKGROUND

Early, intense rehabilitation is essential to promote recovery after stroke, spinal cord injury (SCI), and traumatic brain injury (TBI). However, intensity of usual care rehabilitation interventions during inpatient rehabilitation are poorly characterized.

OBJECTIVE

To describe the intensity of usual care rehabilitation interventions completed during the subacute phase of recovery from neurologic injury.

DESIGN

Observational.

SETTING

Inpatient rehabilitation facility.

INTERVENTIONS

Twenty-two usual care physical therapy interventions were grouped into six categories: gait (four activities), functional (two), strengthening (four), aerobic (six), balance (four), and wheelchair (two).

PATIENTS

Patients admitted to inpatient rehabilitation with a primary diagnosis of stroke, SCI or TBI within 6 months of injury.

MAIN OUTCOME MEASURE(S)

Cardiovascular intensity (physiological and perceived) was recorded during rehabilitation activity sessions. Physiological intensity was assessed by heart rate reserve (HRR) via a Polar A370 Fitness Watch and characterized as very light (<30%), light (30-39%), moderate (40-59%), vigorous (60-89%), and near maximal (≥90%). Perceived intensity was assessed using the Rating of Perceived Exertion scale.

RESULTS

Patients (stroke n = 16 [number of activity sessions = 388/average session duration = 15.1 min]; SCI n = 15 [299/27.3 min]; TBI n = 15 [340/13.4 min]) participated. For patients with stroke, moderate-to-vigorous HRR was attained between 42% (aerobic exercise) to 55% (wheelchair propulsion) of activity sessions. For patients with SCI, moderate-to-vigorous HRR was attained between 29% (strength training) to 46% (gait training) of activity sessions. For patients with TBI, moderate-to-vigorous HRR was attained between 29% (balance activities) to 47% (gait training) of activity sessions. Associations between HRR and rate of perceived exertion were very weak across stroke (r = 0.12), SCI (r = 0.18), and TBI (r = 0.27).

CONCLUSIONS

Patients with stroke, SCI, and TBI undergoing inpatient rehabilitation achieve moderate-to-vigorous intensity during some usual care activities such as gait training. Patient perception of intensity was dissimilar to physiological response.

Validity of the Polar Vantage M watch when measuring heart rate at different exercise intensities

Background

The use of wrist worn wearable fitness trackers has been growing rapidly over the last decade. The growing popularity can be partly attributed to the improvements in technology, making activity trackers more affordable, comfortable and convenient for use in different fitness and environmental applications. Fitness trackers typically monitor activity level, track steps, distance, heart rate (HR), sleep, peripheral capillary oxygen saturation and more, as the technology continuously is advancing. In terms of measuring HR, photoplethysmography (PPG) is a relatively new technology utilised in wearables. PPG estimates HR through an optical technique that monitors changes in blood volume beneath the skin. With these new products becoming available it is important that the validity of these devices be evaluated. Therefore, the aim of this study was to assess the validity of the Polar Vantage M (PVM) watch to measure HR compared to medical grade ECG on a healthy population during a range of treadmill exercise intensities.

Methods

A total of 30 healthy participants (n = 17 males, n = 13 females) were recruited for this study. The validity of the PVM watch to measure HR was compared against the gold standard 5-lead ECG. The study was conducted on 2 separate testing days with 24–48 h between sessions. Participants completed the Bruce Treadmill Protocol, and HR was measured every 30 s. Validation of the PVM watch in comparison to the ECG was measured with an Intraclass Correlation Coefficient (ICC) and associated 95% confidence intervals (CI) and levels of agreement were identified with Bland–Altman plots with 90% limits of agreement. Linear regression analysis was performed to calculate the value of r² computing the variation of HR obtained by the PVM watch and ECG.

Results

In total, 30 participants completed the protocol, with data from 28 participants utilised for statistical analysis (16 males, 14 females, 26.10 ± 3.39 years, height 52.36 m ± 7.40 cm, mass 73.59 ± 11.90 kg). A strong and significant correlation was found between the PVM watch and ECG, demonstrating good criterion validity (p < 0.05, r² = 0.87). Good validity was seen for day 1 and day 2 for stage 0 (ICC = 0.83; 95% CI [0.63–0.92], ICC = 0.74; 95% CI [0.37–0.88]), stage 1 (ICC = 0.78; 95% CI [0.52–0.90], ICC = 0.88; 95% CI [0.74–0.95]), and stage 2 (ICC = 0.88; 95% CI [0.73–0.94], ICC = 0.80; 95% CI [0.40–0.92]). Poor validity was demonstrated on day 1 and day 2 for stages 3–5 (ICC < 0.50).

Conclusion

This study revealed that the PVM watch had a strong correlation with the ECG throughout the entire Bruce Protocol, however the level of agreement (LoA) becomes widely dispersed as exercise intensities increased. Due to the large LoA between the ECG and PVM watch, it is not advisable to use this device in clinical populations in which accurate HR measures are essential for patient safety; however, the watch maybe used in settings where less accurate HR is not critical to an individual’s safety while exercising.

ESC working group on e-cardiology position paper: use of commercially available wearable technology for heart rate and activity tracking in primary and secondary cardiovascular prevention-in collaboration with the European Heart Rhythm Association, European Association of Preventive Cardiology, Association of Cardiovascular Nursing and Allied Professionals, Patient Forum, and the Digital Health Committee

Commercially available health technologies such as smartphones and smartwatches, activity trackers and eHealth applications, commonly referred to as wearables, are increasingly available and used both in the leisure and healthcare sector for pulse and fitness/activity tracking. The aim of the Position Paper is to identify specific barriers and knowledge gaps for the use of wearables, in particular for heart rate (HR) and activity tracking, in clinical cardiovascular healthcare to support their implementation into clinical care. The widespread use of HR and fitness tracking technologies provides unparalleled opportunities for capturing physiological information from large populations in the community, which has previously only been available in patient populations in the setting of healthcare provision. The availability of low-cost and high-volume physiological data from the community also provides unique challenges. While the number of patients meeting healthcare providers with data from wearables is rapidly growing, there are at present no clinical guidelines on how and when to use data from wearables in primary and secondary prevention. Technical aspects of HR tracking especially during activity need to be further validated. How to analyse, translate, and interpret large datasets of information into clinically applicable recommendations needs further consideration. While the current users of wearable technologies tend to be young, healthy and in the higher sociodemographic strata, wearables could potentially have a greater utility in the elderly and higher-risk population. Wearables may also provide a benefit through increased health awareness, democratization of health data and patient engagement. Use of continuous monitoring may provide opportunities for detection of risk factors and disease development earlier in the causal pathway, which may provide novel applications in both prevention and clinical research. However, wearables may also have potential adverse consequences due to unintended modification of behaviour, uncertain use and interpretation of large physiological data, a possible increase in social inequality due to differential access and technological literacy, challenges with regulatory bodies and privacy issues. In the present position paper, current applications as well as specific barriers and gaps in knowledge are identified and discussed in order to support the implementation of wearable technologies from gadget-ology into clinical cardiology.

Accuracy of wrist-worn heart rate monitors during physical therapy sessions among hemiparetic inpatients with stroke

[Purpose] We aimed to examine the accuracy of heart rate monitors worn on the wrist by patients with stroke. The wrist worn heart rate monitor could improve the quality of rehabilitation by monitoring exercise intensity during physical therapy. [Participants and Methods] Thirty inpatients with subacute hemiparetic stroke wore heart rate monitors on both (non-paretic and paretic) wrists, as well as a chest heart rate monitor. We recorded the heart rate values measured at the wrist and chest every minute during physical therapy sessions. The wrist monitors were an optical heart rate measurement device based on photoplethysmography, and the chest monitor was a traditional chest device based on electrocardiography. The relative and absolute reliabilities between the heart rate measurements from the wrist and chest monitors were calculated. [Results] The intraclass correlation coefficients for model 2.1 ranged from 0.75 to 0.79. Bland-Altman analysis revealed a very slight fixed bias; however, no significant proportional bias was observed. For the non-paretic and paretic sides, the lower and upper limits of agreement ranged from −21.8 to 23.8 beats/min and from −20.8 to 21.6 beats/min, and the mean absolute percentage errors were 6.7% and 5.9%, respectively. The Cohen’s d value was small. [Conclusion] The relative reliability of the wrist heart rate monitors was substantial. The absolute reliability as bias in wrist heart rate and chest heart rate was small, but heart rates estimated from wrist monitors were not particularly accurate.

Development and piloting of a perturbation stationary bicycle robotic system that provides unexpected lateral perturbations during bicycling (the PerStBiRo system)

Background

Balance control, and specifically balance reactive responses that contribute to maintaining balance when balance is lost unexpectedly, is impaired in older people. This leads to an increased fall risk and injurious falls. Improving balance reactive responses is one of the goals in fall-prevention training programs. Perturbation training during standing or treadmill walking that specifically challenges the balance reactive responses has shown very promising results; however, only older people who are able to perform treadmill walking can participate in these training regimes. Thus, we aimed to develop, build, and pilot a mechatronic Perturbation Stationary Bicycle Robotic system (i.e., PerStBiRo) that can challenge balance while sitting on a stationary bicycle, with the aim of improving balance proactive and reactive control.

Methods

This paper describes the development, and building of the PerStBiRo using stationary bicycles. In addition, we conducted a pilot randomized control trial (RCT) with 13 older people who were allocated to PerStBiRo training (N = 7) versus a control group, riding stationary bicycles (N = 6). The Postural Sway Test, Berg Balance Test (BBS), and 6-min Walk Test were measured before and after 3 months i.e., 20 training sessions.

Results

The PerStBiRo System provides programmed controlled unannounced lateral balance perturbations during stationary bicycling. Its software is able to identify a trainee’s proactive and reactive balance responses using the Microsoft Kinect™ system. After a perturbation, when identifying a trainee’s trunk and arm reactive balance response, the software controls the motor of the PerStBiRo system to stop the perturbation. The pilot RCT shows that, older people who participated in the PerStBiRo training significantly improved the BBS (54 to 56, p = 0.026) and Postural Sway velocity (20.3 m/s to 18.3 m/s, p = 0.018), while control group subject did not (51.0 vs. 50.5, p = 0.581 and 15 m/s vs. 13.8 m/s, p = 0.893, respectively), 6MWT tended to improve in both groups.

Conclusions

Our participants were able to perform correct balance proactive and reactive responses, indicating that older people are able to learn balance trunk and arm reactive responses during stationary bicycling. The pilot study shows that these improvements in balance proactive and reactive responses are generalized to performance-based measures of balance (BBS and Postural Sway measures).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02015-1.

Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables assessing HR by PPG. The recommendations were developed through the following multi-stage process: (1) a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, (2) an unstructured review of the wider literature pertaining to factors that may introduce bias during the validation of these devices and (3) evidence-informed expert opinions of the INTERLIVE Network. A total of 44 articles were deemed eligible and retrieved through our systematic literature review. Based on these studies, a wider literature review and our evidence-informed expert opinions, we propose a validation framework with standardised recommendations using six domains: considerations for the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. As such, this paper presents recommendations to standardise the validity testing and reporting of PPG-based HR wearables used by consumers. Moreover, checklists are provided to guide the validation protocol development and reporting. This will ensure that manufacturers, consumers, healthcare providers and researchers use wearables safely and to its full potential.

"I shy away from them because they are very identifiable": A qualitative study exploring user and non-user's perceptions of wearable activity trackers

OBJECTIVE

Wearable activity trackers hold potential as a research tool to increase physical activity. However, long-term wearable adherence is low among users, which may be due to the limited understanding of the factors related to use and relation to health behavior theory. The purpose of this study was to qualitatively explore the perceptions of wearables among active adult users and non-users. Findings will inform potential barriers and facilitators for the adherence and adoption of wearables through the application of the Self-Determination Theory.

METHODS

Six focus groups were conducted and equally stratified to wearable users (n = 10) and non-users (n = 10). Data were audio recorded, transcribed, and analyzed using an iterative approach creating first-level codes. This was followed by developing second-level codes that allowed for generating themes.

RESULTS

For users, the wearables' feedback provided them with validation, a sense of achievement, and other-determined motivation. Users appreciated the functionality of wearables, particularly with simpler and newer models. They also reported improvements in health behaviors. While both users and non-users had a general positive feeling towards wearables, they held similar concerns about cost, guilt, dependency, and accuracy. Non-users were unique in their concerns for materialism and functionality (i.e. ease of use and charge) associated with wearables. They also seemed to be more intrinsically motivated to be physically active by relying less on external sources of motivation as potentially provided by wearables.

CONCLUSIONS

Findings show that while both adult users and non-users held positive perceptions of wearables and concerns for feelings of guilt and dependency, widespread adoption and adherence may be prevented by differences in motivation for physical activity and concerns for cost, materialism, and functionality.

Verification of the Propagation Range of Respiratory Strain Using Signal Waveform Measured by FBG Sensors

The FBG (Fiber Bragg grating) sensor is an optical fiber type strain sensor. When a person breathes, strain occurs in the lungs and diaphragm. This was verified using an FBG sensor to which part of the living body this respiratory strain propagates. When measured in the abdomen, the signal waveforms were significantly different between breathing and apnea. The respiratory cycle measured by the temperature sensor attached to the mask and the strain cycle measured by the FBG sensor almost matched. Respiratory strain was measured in the abdomen, chest, and shoulder, and the signal amplitude decreased with distance from the abdomen. In addition, the respiratory rate could be calculated from the measured strain signal. On the other hand, respiratory strain did not propagate to the elbows and wrists, which were off the trunk, and the respiratory time, based on the signal period, could not be calculated at these parts. Therefore, it was shown that respiratory strain propagated in the trunk from the abdomen to the shoulder, but not in the peripheral parts of the elbow and wrist.

Biosensors Based on Mechanical and Electrical Detection Techniques

Biosensors are powerful analytical tools for biology and biomedicine, with applications ranging from drug discovery to medical diagnostics, food safety, and agricultural and environmental monitoring. Typically, biological recognition receptors, such as enzymes, antibodies, and nucleic acids, are immobilized on a surface, and used to interact with one or more specific analytes to produce a physical or chemical change, which can be captured and converted to an optical or electrical signal by a transducer. However, many existing biosensing methods rely on chemical, electrochemical and optical methods of identification and detection of specific targets, and are often: complex, expensive, time consuming, suffer from a lack of portability, or may require centralised testing by qualified personnel. Given the general dependence of most optical and electrochemical techniques on labelling molecules, this review will instead focus on mechanical and electrical detection techniques that can provide information on a broad range of species without the requirement of labelling. These techniques are often able to provide data in real time, with good temporal sensitivity. This review will cover the advances in the development of mechanical and electrical biosensors, highlighting the challenges and opportunities therein.

Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review

Background

Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.

Objective

The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.

Methods

We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.

Results

We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.

Conclusions

Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.

A Study on the Effect of Contact Pressure during Physical Activity on Photoplethysmographic Heart Rate Measurements

Heart rate (HR) as an important physiological indicator could properly describe global subject's physical status. Photoplethysmographic (PPG) sensors are catching on in field of wearable sensors, combining the advantages in costs, weight and size. Nevertheless, accuracy in HR readings is unreliable specifically during physical activity. Among several identified sources that affect PPG recording, contact pressure (CP) between the PPG sensor and skin greatly influences the signals.

METHODS

In this study, the accuracy of HR measurements of a PPG sensor at different CP was investigated when compared with a commercial ECG-based chest strap used as a test control, with the aim of determining the optimal CP to produce a reliable signal during physical activity. Seventeen subjects were enrolled for the study to perform a physical activity at three different rates repeated at three different contact pressures of the PPG-based wristband.

RESULTS

The results show that the CP of 54 mmHg provides the most accurate outcome with a Pearson correlation coefficient ranging from 0.81 to 0.95 and a mean average percentage error ranging from 3.8% to 2.4%, based on the physical activity rate.

CONCLUSION

Authors found that changes in the CP have greater effects on PPG-HR signal quality than those deriving from the intensity of the physical activity and specifically, the individual best CP for each subject provided reliable HR measurements even for a high intensity of physical exercise with a Bland-Altman plot within ±11 bpm. Although future studies on a larger cohort of subjects are still needed, this study could contribute a profitable indication to enhance accuracy of PPG-based wearable devices.