Comparative Analysis of the Equivital EQ02 Lifemonitor with Holter Ambulatory ECG Device for Continuous Measurement of ECG, Heart Rate, and Heart Rate Variability: A Validation Study for Precision and Accuracy

Day-to-day reliability of basal heart rate and short-term and ultra short-term heart rate variability assessment by the Equivital eq02+ LifeMonitor in US Army soldiers

INTRODUCTION

The present study determined the (1) day-to-day reliability of basal heart rate (HR) and HR variability (HRV) measured by the Equivital eq02+ LifeMonitor and (2) agreement of ultra short-term HRV compared with short-term HRV.

METHODS

Twenty-three active-duty US Army Soldiers (5 females, 18 males) completed two experimental visits separated by >48 hours with restrictions consistent with basal monitoring (eg, exercise, dietary), with measurements after supine rest at minutes 20-21 (ultra short-term) and minutes 20-25 (short-term). HRV was assessed as the SD of R-R intervals (SDNN) and the square root of the mean squared differences between consecutive R-R intervals (RMSSD).

RESULTS

The day-to-day reliability (intraclass correlation coefficient (ICC)) using linear-mixed model approach was good for HR (0.849, 95% CI: 0.689 to 0.933) and RMSSD (ICC: 0.823, 95% CI: 0.623 to 0.920). SDNN had moderate day-to-day reliability with greater variation (ICC: 0.689, 95% CI: 0.428 to 0.858). The reliability of RMSSD was slightly improved when considering the effect of respiration (ICC: 0.821, 95% CI: 0.672 to 0.944). There was no bias for HR measured for 1 min versus 5 min (p=0.511). For 1 min measurements versus 5 min, there was a very modest mean bias of -4 ms for SDNN and -1 ms for RMSSD (p≤0.023).

CONCLUSION

When preceded by a 20 min stabilisation period using restrictions consistent with basal monitoring and measuring respiration, military personnel can rely on the eq02+ for basal HR and RMSSD monitoring but should be more cautious using SDNN. These data also support using ultra short-term measurements when following these procedures.

E-Textiles for Sports and Fitness Sensing: Current State, Challenges, and Future Opportunities

E-textiles have emerged as a fast-growing area in wearable technology for sports and fitness due to the soft and comfortable nature of textile materials and the capability for smart functionality to be integrated into familiar sports clothing. This review paper presents the roles of wearable technologies in sport and fitness in monitoring movement and biosignals used to assess performance, reduce injury risk, and motivate training/exercise. The drivers of research in e-textiles are discussed after reviewing existing non-textile and textile-based commercial wearable products. Different sensing components/materials (e.g., inertial measurement units, electrodes for biosignals, piezoresistive sensors), manufacturing processes, and their applications in sports and fitness published in the literature were reviewed and discussed. Finally, the paper presents the current challenges of e-textiles to achieve practical applications at scale and future perspectives in e-textiles research and development.

Characterizing Heart Rate Variability Response to Maximal Exercise Testing in People with Huntington's Disease

Background

Huntington's disease (HD) is an autosomal dominant, neurodegenerative disease that involves dysfunction in the autonomic nervous system (ANS). Heart rate variability (HRV) is a valid and noninvasive measure for ANS dysfunction, yet no study has characterized HRV response to exercise in people with HD.

Objective

Characterize HRV response to exercise in individuals with HD and explore its implications for exercise prescription and cardiac dysautonomia mechanisms.

Methods

19 participants with HD were recruited as part of a cohort of individuals enrolled in the Physical Activity and Exercise Outcomes in Huntington's Disease (PACE-HD) study at Teachers College, Columbia University (TC). 13 non-HD age- and gender-matched control participants were also recruited from TC. HRV was recorded with a Polar H10 heart rate (HR) monitor before, during, and after a ramp cycle-ergometer exercise test.

Results

Participants with HD showed reduced HR peak (p < 0.01) and HR reserve (p < 0.001) compared with controls. Participants with HD demonstrated reduced root mean square of successive differences between normal-to-normal intervals (RMSSD) and successive differences of normal-to-normal intervals (SDSD) at rest (p < 0.001). Participants with HD also showed differences for low frequency (LF) power (p < 0.01), high frequency (HF) normalized units (nu) (p < 0.05), LF (nu) (p < 0.001), and HF/LF ratio (p < 0.05) compared with controls.

Conclusions

We found reduced aerobic exercise capacity and sympathovagal dysautonomia both at rest and during post-exercise recovery in people with HD, suggesting modified exercise prescription may be required for people with HD. Further investigations focusing on cardiac dysautonomia and underlying mechanisms of sympathovagal dysautonomia in people with HD are warranted.

Validity of heart rate derived core temperature estimation during simulated firefighting tasks

Rectal core temperature monitoring can help fire services mitigate heat injury but can be invasive and impractical. EQ02 + LifeMonitor provides a non-invasive estimation of core temperature. Therefore, the primary purpose of this study was to determine the validity of the EQ02 + LifeMonitor compared to the gold standard rectal thermometer core temperature assessment, as well as the potential influence of turnout gear on the estimated and physiological strain experienced during these activities. Thirteen participants completed simulated firefighting tasks with and without turnout gear, involving four rounds of a 5-min walk on a treadmill at 2.8 mph/2.5% grade and 20 deadlifts over 5 min in an environmental chamber set to 40.6 °C; 50% humidity. During each trial participants wore both an EQ02 + LifeMonitor and DataTherm II rectal thermometer. The results from the devices were statistically equivalent (p < 0.001), yet there was a statistically significant difference in the value (~ 0.1 °C; p < 0.001). There was a significant effect of devices [p < 0.001] and time [p < 0.001], but no interaction effect [p = 0.70] on core temperature drift. Estimated core temperature was marginally different from that measured via the DataTherm II. The EQ02 on average overestimated core temperature. Heart rate, rating of perceived exertion, and area under the curve of core temperature were significantly elevated due to turnout gear [ps < 0.025], but not core temperature skin temperature, or ventilatory rate [ps > 0.372]. These results suggest the EQ02 + LifeMonitor may be a viable, non-invasive alternative for assessing core temperature compared to rectal temperature monitoring, especially during rigorous, intermittent activities. Turnout gear does however increase heart rate, cumulative core temperature, and perceived exertion. Additionally, the validity of the estimated core temperature is not impacted by the use turnout gear. This is likely due to significant changes in heart rate, which allowed the heart-rate derived estimate of core temperature to remain consistent with changes in DataTherm II rectal temperatures.

Accuracy of heart rate measured by military-grade wearable ECG monitor compared with reference and commercial monitors

INTRODUCTION

Physiological monitoring of soldiers can indicate combat readiness and performance. Despite demonstrated use of wearable devices for HR monitoring, commercial options lack desired military features. A newly developed OMNI monitor includes desired features such as long-range secure data transmission. This study investigated the accuracy of the OMNI to measure HR via accuracy of R-R interval duration relative to research-grade ECG and commercial products.

METHODS

54 healthy individuals (male/female=37/17, age=22.2±3.6 years, height=173.0±9.1 cm, weight=70.1±11.2 kg) completed a submaximal exercise test while wearing a reference ECG (Biopac) and a randomly assigned chest-based monitor (OMNI, Polar H10, Equivital EQ-02, Zephyr Bioharness 3). All participants also wore two wrist-based photoplethysmography (PPG) devices, Garmin fēnix 6 and Empatica E4. Bland-Altman analyses of agreement, concordance correlation coefficient (CCC) and root-mean-squared error (RMSE) were used to determine accuracy of the OMNI and commercial devices relative to Biopac. Additionally, a linear mixed-effects model evaluated the effects of device and exercise intensity on agreement.

RESULTS

Chest-based devices showed superior agreement with Biopac for measuring R-R interval compared with wrist-based ones in terms of mean bias, CCC and RMSE, with OMNI demonstrating the best scores on all metrics. Linear mixed-effects model showed no significant main or interaction effects for the chest-based devices. However, significant effects were found for Garmin and Empatica devices (p<0.001) as well as the interaction effects between both Garmin and Empatica and exercise intensity (p<0.001).

CONCLUSIONS

Chest-based ECG devices are preferred to wrist-based PPG devices due to superior HR accuracy over a range of exercise intensities, with the OMNI device demonstrating equal, if not superior, performance to other commercial ECG monitors. Additionally, wrist-based PPG devices are significantly affected by exercise intensity as they underestimate HR at low intensities and overestimate HR at high intensities.

PreEpiSeizures: description and outcomes of physiological data acquisition using wearable devices during video-EEG monitoring in people with epilepsy

The PreEpiSeizures project was created to better understand epilepsy and seizures through wearable technologies. The motivation was to capture physiological information related to epileptic seizures, besides Electroencephalography (EEG) during video-EEG monitorings. If other physiological signals have reliable information of epileptic seizures, unobtrusive wearable technology could be used to monitor epilepsy in daily life. The development of wearable solutions for epilepsy is limited by the nonexistence of datasets which could validate these solutions. Three different form factors were developed and deployed, and the signal quality was assessed for all acquired biosignals. The wearable data acquisition was performed during the video-EEG of patients with epilepsy. The results achieved so far include 59 patients from 2 hospitals totaling 2,721 h of wearable data and 348 seizures. Besides the wearable data, the Electrocardiogram of the hospital is also useable, totalling 5,838 h of hospital data. The quality ECG signals collected with the proposed wearable is equated with the hospital system, and all other biosignals also achieved state-of-the-art quality. During the data acquisition, 18 challenges were identified, and are presented alongside their possible solutions. Though this is an ongoing work, there were many lessons learned which could help to predict possible problems in wearable data collections and also contribute to the epilepsy community with new physiological information. This work contributes with original wearable data and results relevant to epilepsy research, and discusses relevant challenges that impact wearable health monitoring.

Heart Rate Variability Assessment of Land Navigation and Load Carriage Activities in Specialist Police Selection

Police tactical group (PTG) personnel are exposed to physical, mental, and emotional stressors. Consequently, PTG selection courses (SCs) impart similar challenges, often resulting in candidate attrition. Holistic assessment may provide additional support to stakeholders given these risks. Heart Rate Variability (HRV) is an objective holistic stress measure that may be applicable in PTG SCs but has not been thoroughly researched. Therefore, this study aimed to report HRV data in an end-user accessible format and determine the relationship between HRV and attrition. A total of 18 qualified Australian State law enforcement officers completed a 1-day physical readiness assessment. Of those, six males progressed to an additional two-day course, on which this study is focused. This two-day selection consisted of additional physical challenges and occupational assessments. HRV was obtained from 2-lead ECGs and defined as the percentage of R-R intervals that varied by ≥50 ms (pRR50). Data were summarized in a heat map of consecutive short-term analyses. Three candidates withdrew. A logistic regression based on heat map data found high HRV was significant for predicting attrition, χ2 (6) = 8.318, p = 0.004. HRV may provide insight for PTG stakeholders monitoring attrition. While the sample size was limited and replication is needed, this study tentatively establishes value for HRV monitoring in PTG SCs.

A Multifunctional Network with Uncertainty Estimation and Attention-Based Knowledge Distillation to Address Practical Challenges in Respiration Rate Estimation

Respiration rate is a vital parameter to indicate good health, wellbeing, and performance. As the estimation through classical measurement modes are limited only to rest or during slow movements, respiration rate is commonly estimated through physiological signals such as electrocardiogram and photoplethysmography due to the unobtrusive nature of wearable devices. Deep learning methodologies have gained much traction in the recent past to enhance accuracy during activities involving a lot of movement. However, these methods pose challenges, including model interpretability, uncertainty estimation in the context of respiration rate estimation, and model compactness in terms of deployment in wearable platforms. In this direction, we propose a multifunctional framework, which includes the combination of an attention mechanism, an uncertainty estimation functionality, and a knowledge distillation framework. We evaluated the performance of our framework on two datasets containing ambulatory movement. The attention mechanism visually and quantitatively improved instantaneous respiration rate estimation. Using Monte Carlo dropouts to embed the network with inferential uncertainty estimation resulted in the rejection of 3.7% of windows with high uncertainty, which consequently resulted in an overall reduction of 7.99% in the mean absolute error. The attention-aware knowledge distillation mechanism reduced the model's parameter count and inference time by 49.5% and 38.09%, respectively, without any increase in error rates. Through experimentation, ablation, and visualization, we demonstrated the efficacy of the proposed framework in addressing practical challenges, thus taking a step towards deployment in wearable edge devices.

Design and Validation of a Multimodal Wearable Device for Simultaneous Collection of Electrocardiogram, Electromyogram, and Electrodermal Activity

Bio-signals are being increasingly used for the assessment of pathophysiological conditions including pain, stress, fatigue, and anxiety. For some approaches, a single signal is not sufficient to provide a comprehensive diagnosis; however, there is a growing consensus that multimodal approaches allow higher sensitivity and specificity. For instance, in visceral pain subjects, the autonomic activation can be inferred using electrodermal activity (EDA) and heart rate variability derived from the electrocardiogram (ECG), but including the muscle activation detected from the surface electromyogram (sEMG) can better differentiate the disease that causes the pain. There is no wearable device commercially capable of collecting these three signals simultaneously. This paper presents the validation of a novel multimodal low profile wearable data acquisition device for the simultaneous collection of EDA, ECG, and sEMG signals. The device was validated by comparing its performance to laboratory-scale reference devices. N = 20 healthy subjects were recruited to participate in a four-stage study that exposed them to an array of cognitive, orthostatic, and muscular stimuli, ensuring the device is sensitive to a range of stressors. Time and frequency domain analyses for all three signals showed significant similarities between our device and the reference devices. Correlation of sEMG metrics ranged from 0.81 to 0.95 and EDA/ECG metrics showed few instances of significant difference in trends between our device and the references. With only minor observed differences, we demonstrated the ability of our device to collect EDA, sEMG, and ECG signals. This device will enable future practical and impactful advances in the field of chronic pain and stress measurement and can confidently be implemented in related studies.

The Role of Age, Sex, Body Mass Index, and Sport Type on the Dynamic Exertion Test in Healthy Athletes: A Cross-Sectional Study

BACKGROUND

The dynamic exertion test (EXiT) was developed to help inform return to play after sport-related concussion, but some factors may threaten the internal validity of EXiT and affect clinical interpretation.

OBJECTIVE

To compare age, sex, BMI, and sport types across EXiT physiological [pre-EXiT and post-EXiT percentage of maximum heart rate (HR %max) and blood pressure (BP)], performance (change-of-direction task completion time and committed errors), and clinical [symptoms and rating of perceived exertion (RPE)] outcomes among healthy adolescents and adults.

STUDY DESIGN

Cross-sectional.

METHODS

Eighty-seven participants ( F = 55, 37.4%) reported symptoms and RPE during the EXiT, which consists of a 12-minute treadmill running protocol, and the dynamic circuit, ball toss, box shuffle (SHUF) and carioca (CAR), zig zag (ZZ), proagility (PA), and arrow agility (AA) tasks. Independent samples t tests were conducted for pre-EXiT and post-EXiT HR %max and BP and change-of-direction task completion time and Mann-Whitney U tests for errors, symptoms, and RPE. A series of 1-way analysis of variance (ANOVAs) and Kruskal-Wallis H tests were conducted to compare collision, contact, and noncontact sport types.

RESULTS

Adolescents had lower completion time across AA ( P = 0.01) and male athletes lower than female athletes on CAR, ZZ, PA, and AA ( P < 0.04). Male athletes reported greater RPE after the SHUF, CAR, and AA ( P < 0.03). HR %max , errors, and symptoms were equivocal across all subgroups ( P > 0.05).

CONCLUSION

Age and sex should be considered in the interpretation of performance and clinical, but not physiological, EXiT outcomes. The EXiT is a standardized exercise assessment and generalizable to healthy athletes.

The association between continuous ambulatory heart rate, heart rate variability, and 24-h rhythms of heart rate with familial longevity and aging

Aging is associated with changes in heart rate (HR), heart rate variability (HRV), and 24-h rhythms in HR. Longevity has been linked to lower resting HR, while a higher resting HR and a decreased HRV were linked to cardiovascular events and increased mortality risk. HR and HRV are often investigated during a short electrocardiogram (ECG) measurement at a hospital. In this study, we aim to investigate the relationship between HR parameters with familial longevity and chronological age derived from continuous ambulatory ECG measurements collected over a period of 24 to 90 hours. We included 73 middle-aged participants (mean (SD) age: 67.0 (6.16) years), comprising 37 offspring of long-lived families, 36 of their partners, and 35 young participants (22.8 (3.96) years). We found no association with familial longevity, but middle-aged participants had lower 24-h HR (average and maximum HR, not minimum HR), lower amplitudes, and earlier trough and peak times than young participants. Associations in HR with chronological age could be caused by the aging process or by differences in environmental factors. Interestingly, middle-aged participants had a less optimal HRV during long-term recordings in both the sleep and awake periods, which might indicate that their heart is less adaptable than that of young participants. This could be a first indication of deteriorated cardiovascular health in middle-aged individuals.

Wearables for Engagement Detection in Learning Environments: A Review

Appropriate teaching-learning strategies lead to student engagement during learning activities. Scientific progress and modern technology have made it possible to measure engagement in educational settings by reading and analyzing student physiological signals through sensors attached to wearables. This work is a review of current student engagement detection initiatives in the educational domain. The review highlights existing commercial and non-commercial wearables for student engagement monitoring and identifies key physiological signals involved in engagement detection. Our findings reveal that common physiological signals used to measure student engagement include heart rate, skin temperature, respiratory rate, oxygen saturation, blood pressure, and electrocardiogram (ECG) data. Similarly, stress and surprise are key features of student engagement.

Dry textile electrode for ambulatory monitoring after catheter ablation of atrial fibrillation: A pilot study of simultaneous comparison to the Holter electrocardiogram

Background: Holter electrocardiogram (ECG) is the gold standard for ambulatory monitoring of atrial fibrillation (AF) but it is insufficient because of its limited recording time. Although several consumer ECG devices provide longer recording time, they generally do not undergo the regulatory process for medical use. Furthermore, current medical-grade devices for longer ECG monitoring are not continuous or too invasive for AF monitoring. A wearable ECG with a medical-grade dry textile electrode is a promising technology to remedy this limitation. This pilot study aimed to simultaneously compare the wearable and Holter ECGs for ambulatory monitoring in a clinical setting.

Methods: This prospective observational study enrolled 18 patients who underwent AF ablation. One day after AF ablation, ambulatory ECG was obtained for three hours simultaneously using both the wearable and Holter ECG devices. Automatic ECG interpretations between devices were compared with correlation and agreement analyses.

Results: Simultaneous ECG monitoring demonstrated a comparable analysis time and total heart beats between the two devices. Almost complete correlation and agreement were also demonstrated in all clinically relevant testing aspects except in R-wave amplitude (r = 0.743, p < .001). AF was detected in three patients. AF duration was the same in both ECG devices in two patients with continuous AF. In the remaining patient with intermittent AF, AF duration was shortened by 0.6% with the wearable ECG as compared to that with the Holter ECG.

Conclusions: Simultaneous ECG comparison revealed a high consistency between the wearable and Holter ECG devices. The results of this study warrant further clinical studies for long-term monitoring of ambulatory ECG after AF ablation.

Test-Retest, Interrater Reliability, and Minimal Detectable Change of the Dynamic Exertion Test (EXiT) for Concussion

BACKGROUND

The Dynamic Exertion Test (EXiT) was developed to inform return-to-play (RTP) decision-making following clinical recovery from sport-related concussion (SRC). The purpose of the current study was to document intrarater and test-retest reliability and minimal detectable change (MDC) scores for physiological [heart rate (HR) and blood pressure], performance (change-of-direction task completion time and errors), and clinical outcomes (endorsed symptoms, perceived exertion) of EXiT, and interrater reliability of performance outcomes.

HYPOTHESIS

Healthy athletes would exhibit stable physiological responses to the EXiT across visits, demonstrate consistent change-of-direction task completion time between consecutive trials at each visit, and the fastest time (of 2 trials) across visits, and endorse equivocal symptoms and effort across visits.

STUDY DESIGN

Cross-sectional, test-retest.

LEVEL OF EVIDENCE

Level 3.

METHODS

Seventy-nine (female: 34 [43%], 19.6 ± 5.0 years) athletes completed the EXiT at 2 study visits (8.7 ± 4.7 days between visits). Two-way, mixed, intraclass correlation coefficients (ICCs) were used to evaluate intrarater and test-retest reliability. Cronbach's alpha was used to document the internal consistency of symptoms at each visit, and MDC scores were calculated on the physiological, performance, and clinical outcomes.

RESULTS

Measured and percentage of age-estimated maximum HR were reliable following EXiT (ICC = 0.579-0.618). Change-of-direction task completion time (MDC range = 0.75-8.70 s) had good-to-excellent test-retest (ICC = 0.703-0.948) and interrater (ICC = 0.932-0.965) reliability. Symptoms had a high internal consistency at visits 1 (α = 0.894) and 2 (α = 0.805) and were reliable across visits (ICC = 0.588).

CONCLUSION

The current investigation established test-retest reliability in addition to MDC scores of an objective dynamic exercise assessment among healthy adolescent and adult athletes. The EXiT may be an objective approach to inform RTP decision-making following SRC recovery.

CLINICAL RELEVANCE

The EXiT is a clinically feasible exertion-based assessment that can be readily administered in a variety of outpatient clinical settings.

Sympathovagal Balance Is a Strong Predictor of Post High-Volume Endurance Exercise Cardiac Arrhythmia

Regular physical activity is important for cardiovascular health. However, high-volume endurance exercise has been associated with increased number of electrocardiogram (ECG) abnormalities, including disturbances in cardiac rhythm (arrhythmias) and abnormalities in ECG pattern. The aim of this study was to assess if heart rate variability (HRV) is associated with ECG abnormalities. Fifteen participants with previous cycling experience completed a 21-day high-volume endurance exercise cycle over 3,515 km. Participants wore a 5-lead Holter monitor for 24 h pre- and post-exercise, which was used to quantify ECG abnormalities and export sinus R-to-R intervals (NN) used to calculate HRV characteristics. As noise is prevalent in 24-h HRV recordings, both 24-h and heart rate collected during stable periods of time (i.e., deep sleep) were examined. Participants experienced significantly more arrhythmias post high-volume endurance exercise (median = 35) compared to pre (median = 12; p = 0.041). All 24-h and deep sleep HRV outcomes were not different pre-to-post high-volume endurance exercise (p &gt; 0.05). Strong and significant associations with arrhythmia number post-exercise were found for total arrhythmia (total arrhythmia number pre-exercise, ρ = 0.79; age, ρ = 0.73), supraventricular arrhythmia (supraventricular arrhythmia number pre-exercise: ρ = 0.74; age: ρ = 0.66), and ventricular arrhythmia (age: ρ = 0.54). As a result, age and arrhythmia number pre-exercise were controlled for in hierarchical regression, which revealed that only deep sleep derived low frequency to high frequency (LF/HF) ratio post high-volume endurance exercise predicted post total arrhythmia number (B = 0.63, R2Δ = 34%, p = 0.013) and supraventricular arrhythmia number (B = 0.77, R2Δ = 69%, p &lt; 0.001). In this study of recreationally active people, only deep sleep derived LF/HF ratio was associated with more total and supraventricular arrhythmias after high-volume endurance exercise. This finding suggests that measurement of sympathovagal balance during deep sleep might be useful to monitor arrhythmia risk after prolonged high-volume endurance exercise performance.

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.

Validation of a smart shirt for heart rate variability measurements at rest and during exercise

Heart rate variability (HRV) monitoring is a promising option to estimate the autonomic nervous system regulation responding to exercise. Textiles with embedded sensors recording heartbeat intervals are a simple tool for data collection. So-called smart shirts offer comfort for a daily use and are managed easily. Their measurement accuracy for HRV calculation at rest is promising but remains questionable during exercise. Therefore, the present study validated the Ambiotex smart shirt using HRV indices (RMSSD, rel. HF power and rel. LF power) during exercise. Eighty-three healthy participants (31 ± 6 years; 39 females, 44 males) completed an incremental exercise test on a bicycle ergometer wearing the smart shirt and an electrocardiogram simultaneously. We compared HRV indices of segments at rest (5 min), at warm-up (3 min) and twice at the exercise test (each 5 min). At rest and at warm-up, we observed excellent linear relationship (r > 0.96; R² > 0.94), excellent relative reliability (ICC ≥ 0.98; α ≥ 0.98) and acceptable agreement (bias < 10%). During the exercise test, measurement accuracy declined with increasing intensity but remained high (> 0.8), although results for partial HRV indices were insufficient. In addition, percentage bias was unacceptable during exercise test. However, the findings support the validity of the smart shirt for measuring HRV especially at rest and at warm-up. We suggest using the smart shirt for monitoring HRV indices on a daily basis but caution should be taken in the interpretation of HRV indices obtained during moderate to vigorous exercise intensities. This article is protected by copyright. All rights reserved.

Remote Healthcare for Elderly People Using Wearables: A Review

The growth of health care spending on older adults with chronic diseases faces major concerns that require effective measures to be adopted worldwide. Among the main concerns is whether recent technological advances now offer the possibility of providing remote health care for the aging population. The benefits of suitable prevention and adequate monitoring of chronic diseases by using emerging technological paradigms such as wearable devices and the Internet of Things (IoT) can increase the detection rates of health risks to raise the quality of life for the elderly. Specifically, on the subject of remote health monitoring in older adults, a first approach is required to review devices, sensors, and wearables that serve as tools for obtaining and measuring physiological parameters in order to identify progress, limitations, and areas of opportunity in the development of health monitoring schemes. For these reasons, a review of articles on wearable devices was presented in the first instance to identify whether the selected articles addressed the needs of aged adults. Subsequently, the direct review of commercial and prototype wearable devices with the capability to read physiological parameters was presented to identify whether they are optimal or usable for health monitoring in older adults.

Validation of ambulatory monitoring devices to measure energy expenditure and heart rate in a military setting

Objectives.To investigate the validity of different devices and algorithms used in military organizations worldwide to assess physical activity energy expenditure (PAEE) and heart rate (HR) among soldiers.Design.Device validation study.Methods. Twenty-three male participants serving their mandatory military service accomplished, firstly, nine different military specific activities indoors, and secondly, a normal military routine outdoors. Participants wore simultaneously an ActiHeart, Everion, MetaMax 3B, Garmin Fenix 3, Hidalgo EQ02, and PADIS 2.0 system. The PAEE and HR data of each system were compared to the criterion measures MetaMax 3B and Hidalgo EQ02, respectively.Results. Overall, the recorded systematic errors in PAEE estimation ranged from 0.1 (±1.8) kcal.min^-1to -1.7 (±1.8) kcal.min^-1for the systems PADIS 2.0 and Hidalgo EQ02 running the Royal Dutch Army algorithm, respectively, and in the HR assessment ranged from -0.1 (±2.1) b.min^-1to 0.8 (±3.0) b.min^-1for the PADIS 2.0 and ActiHeart systems, respectively. The mean absolute percentage error (MAPE) in PAEE estimation ranged from 29.9% to 75.1%, with only the Everion system showing an overall MAPE <30%, but all investigated devices reported overall MAPE <1.4% in the HR assessment.Conclusions. The present study demonstrated poor to moderate validity in terms of PAEE estimation, but excellent validity in all investigated devices in terms of HR assessment. Overall, the Everion performed among the best in both parameters and with a device placement on the upper arm, the Everion system is particularly useful during military service, as it does not interfere with other relevant equipment.

Non-Invasive Physiological Monitoring for Physical Exertion and Fatigue Assessment in Military Personnel: A Systematic Review

During operational activities, military personnel face extremely demanding circumstances, which when combined lead to severe fatigue, influencing both their well-being and performance. Physical exertion is the main condition leading to fatigue, and its continuous tracking would help prevent its effects. This review aimed to investigate the up-to-date progress on non-invasive physiological monitoring to evaluate situations of physical exertion as a pre-condition to fatigue in military populations, and determine the potential associations between physiological responses and fatigue, which can later result in decision-making indicators to prevent health-related consequences. Adhering to the PRISMA Statement, four databases (Scopus, Science Direct, Web of Science and PubMed) were used for a literature search based on combinations of keywords. The eligibility criteria focused on studies monitoring physiological variables through non-invasive objective measurements, with these measurements being developed in military field, combat, or training conditions. The review process led to the inclusion of 20 studies. The findings established the importance of multivariable assessments in a real-life context to accurately characterise the effects of military practices. A tendency for examining heart rate variables, thermal responses, and actigraphy measurements was also identified. The objectives and experimental protocols were diverse, but the effectiveness of non-invasive measurements in identifying the most fatigue-inducing periods was demonstrated. Nevertheless, no assessment system for standardised application was presented. Future work may include the development of assessment methods to translate physiological recordings into actionable information in real-time and mitigate the effects of fatigue on soldiers’ performance accurately.

Effects of Dynamic Resilience on the Reactivity of Vagally Mediated Heart Rate Variability

Dynamic resilience is a novel concept that aims to quantify how individuals are coping while operating in dynamic and complex task environments. A recently developed dynamic resilience measure, derived through autoregressive modeling, offers an avenue toward dynamic resilience classification that may yield valuable information about working personnel for industries such as defense and elite sport. However, this measure classifies dynamic resilience based upon in-task performance rather than self-regulating cognitive structures; thereby, lacking any supported self-regulating cognitive links to the dynamic resilience framework. Vagally mediated heart rate variability (vmHRV) parameters are potential physiological measures that may offer an opportunity to link self-regulating cognitive structures to dynamic resilience given their supported connection to the self-regulation of stress. This study examines if dynamic resilience classifications reveal significant differences in vagal reactivity between higher, moderate and lower dynamic resilience groups, as participants engage in a dynamic, decision-making task. An amended Three Rs paradigm was implemented that examined vagal reactivity across six concurrent vmHRV reactivity segments consisting of lower and higher task load. Overall, the results supported significant differences between higher and moderate dynamic resilience groups' vagal reactivity but rejected significant differences between the lower dynamic resilience group. Additionally, differences in vagal reactivity across vmHRV reactivity segments within an amended Three Rs paradigm were partially supported. Together, these findings offer support toward linking dynamic resilience to temporal self-regulating cognitive structures that play a role in mediating physiological adaptations during task engagement.

Wearable Devices Suitable for Monitoring Twenty Four Hour Heart Rate Variability in Military Populations

Heart rate variability (HRV) measurements provide information on the autonomic nervous system and the balance between parasympathetic and sympathetic activity. A high HRV can be advantageous, reflecting the ability of the autonomic nervous system to adapt, whereas a low HRV can be indicative of fatigue, overtraining or health issues. There has been a surge in wearable devices that claim to measure HRV. Some of these include spot measurements, whilst others only record during periods of rest and/or sleep. Few are capable of continuously measuring HRV (≥24 h). We undertook a narrative review of the literature with the aim to determine which currently available wearable devices are capable of measuring continuous, precise HRV measures. The review also aims to evaluate which devices would be suitable in a field setting specific to military populations. The Polar H10 appears to be the most accurate wearable device when compared to criterion measures and even appears to supersede traditional methods during exercise. However, currently, the H10 must be paired with a watch to enable the raw data to be extracted for HRV analysis if users need to avoid using an app (for security or data ownership reasons) which incurs additional cost.

Monitoring heat strain: the effect of sensor type and location on single-site and mean skin temperature during work in the heat

PURPOSE

Elevations in skin temperature and heat strain reduce tolerance to work in the heat. This study assessed agreement between mean (eight sites) and single-site skin temperature, measured by a conductive or infrared sensor, during exercise in the heat.

METHODS

Twelve males (age: 24.2 ± 3.7 years; height: 180 ± 6.5 cm; body mass: 82.9 ± 9.5 kg; body fat: 16.0 ± 6.5%) volunteered to participate in two trials. Thirty minutes of seated rest was followed by 60 min of treadmill walking (4.5 km·h^-1, 1%) inside an environmental chamber (35.5 ± 0.2 °C dry bulb, 50.7 ± 2.5% relative humidity) wearing either an athletic (ATH: t-shirt, shorts, shoes) or a chemical protective ensemble (CPE: ATH plus coverall and respirator). Skin temperature was measured on the axilla with a conductive sensor (T_sk-C) and an infrared sensor (T_sk-I) and compared to mean skin temperature ([Formula: see text] 8-site conductive sensors). Rectal temperature and heart rate were measured and used to calculate the adaptive physiological strain index (aPSI).

RESULTS

Skin temperature on the chest, scapula, and thigh showed acceptable agreement with [Formula: see text] (mean difference < 0.5 °C and limits of agreement ± 1.0 °C) in both ATH and CPE. Skin temperature on the axilla overestimated [Formula: see text] in ATH (T_sk-C: 1.5 ± 0.8 °C; T_sk-I: 2.2 ± 1.2 °C) and CPE (T_sk-C: 1.1 ± 0.9 °C; T_sk-I: 1.8 ± 1.1 °C). Significant differences (p < 0.001) were observed in aPSI using T_sk-I (ATH: 5.7 ± 1.0, CPE: 8.3 ± 1.1) and T_sk-C (ATH: 5.4 ± 1.0, CPE 7.8 ± 1.0) compared to [Formula: see text] (ATH: 5.2 ± 1.0, CPE: 7.4 ± 1.0).

CONCLUSION

The overestimate of mean skin temperature had a significant influence on the aPSI, which has important implications for real-time monitoring and risk management of personnel working in hot environments.

The Role of Heart Rate Variability in the Future of Remote Digital Biomarkers

Heart rate variability (HRV) offers insights into humoral, neural and neurovisceral processes in health and disorders of brain, body and behavior but has yet to be fully potentiated in the digital age. Remote measurement technologies (RMTs), such as, smartphones, wearable sensors or home-based devices, can passively capture HRV as a nested parameter of neurovisceral integration and health during everyday life, providing insights across different contexts, such as activities of daily living, therapeutic interventions and behavioral tasks, to compliment ongoing clinical care. Many RMTs measure HRV, even consumer wearables and smartphones, which can be deployed as wearable sensors or digital cameras using photoplethysmography. RMTs that measure HRV provide the opportunity to identify digital biomarkers indicative of changes in health or disease status in disorders where neurovisceral processes are compromised. RMT-based HRV therefore has potential as an adjunct digital biomarker in neurovisceral digital phenotyping that can add continuously updated, objective and relevant data to existing clinical methodologies, aiding the evolution of current "diagnose and treat" care models to a more proactive and holistic approach that pairs established markers with advances in remote digital technology.

Continuous physiological monitoring using wearable technology to inform individual management of infectious diseases, public health and outbreak responses

Optimal management of infectious diseases is guided by up-to-date information at the individual and public health levels. For infections of global importance, including emerging pandemics such as COVID-19 or prevalent endemic diseases such as dengue, identifying patients at risk of severe disease and clinical deterioration can be challenging, considering that the majority present with a mild illness. In our article, we describe the use of wearable technology for continuous physiological monitoring in healthcare settings. Deployment of wearables in hospital settings for the management of infectious diseases, or in the community to support syndromic surveillance during outbreaks, could provide significant, cost-effective advantages and improve healthcare delivery. We highlight a range of promising technologies employed by wearable devices and discuss the technical and ethical issues relating to implementation in the clinic, focusing on low- and middle- income countries. Finally, we propose a set of essential criteria for the rollout of wearable technology for clinical use.

A protocol for an observational cohort study of heat strain and its effect on fetal wellbeing in pregnant farmers in The Gambia

Introduction: Climate change predictions indicate that global temperatures are likely to exceed those seen in the last 200,000 years, rising by around 4°C above pre-industrial levels by 2100 (without effective mitigation of current emission rates). In regions of the world set to experience extreme temperatures, women often work outside in agriculture even during pregnancy. The implications of heat strain in pregnancy on maternal health and pregnancy outcome are not well understood. This protocol describes a study to assess the physiological response of pregnant women to environmental heat stress and the immediate effect this has on fetal wellbeing.

Methods and analysis: The study will be performed in West Kiang district, The Gambia; a semi-arid zone in West Africa with daily maximum temperatures ranging from approximately 32 to 40°C. We will recruit 125 pregnant women of all ages who perform agricultural work during their pregnancy. Participants will be followed every two months until delivery. At each study visit fetal growth will be measured by ultrasound scan. During the course of their working day we will take the following measurements: continuous maternal physiological measurements (heart rate, respiratory rate, chest skin temperature and tri-axis accelerometer data); intermittent maternal tympanic core temperature, four point skin temperature, blood pressure; intermittent fetal heart rate and, if eligible, umbilical artery doppler; intermittent environmental measurements of air temperature, humidity, solar radiation and wind speed. Venous blood and urine will be collected at beginning and end of day for biomarkers of heat strain or fetal distress and hydration status.

A protocol for an observational cohort study of heat strain and its effect on fetal wellbeing in pregnant farmers in The Gambia

Introduction: Climate change predictions indicate that global temperatures are likely to exceed those seen in the last 200,000 years, rising by around 4°C above pre-industrial levels by 2100 (without effective mitigation of current emission rates). In regions of the world set to experience extreme temperatures, women often work outside in agriculture even during pregnancy. The implications of heat strain in pregnancy on maternal health and pregnancy outcome are not well understood. This protocol describes a study to assess the physiological response of pregnant women to environmental heat stress and the immediate effect this has on fetal wellbeing. Methods and analysis: The study will be performed in West Kiang district, The Gambia; a semi-arid zone in West Africa with daily maximum temperatures ranging from approximately 32 to 40°C. We will recruit 125 pregnant women of all ages who perform agricultural work during their pregnancy. Participants will be followed every two months until delivery. At each study visit fetal growth will be measured by ultrasound scan. During the course of their working day we will take the following measurements: continuous maternal physiological measurements (heart rate, respiratory rate, chest skin temperature and tri-axis accelerometer data); intermittent maternal tympanic core temperature, four point skin temperature, blood pressure; intermittent fetal heart rate and, if eligible, umbilical artery doppler; intermittent environmental measurements of air temperature, humidity, solar radiation and wind speed. Venous blood and urine will be collected at beginning and end of day for biomarkers of heat strain or fetal distress and hydration status.

Wearable Sensor System to Monitor Physical Activity and the Physiological Effects of Heat Exposure

Mobile health monitoring via non-invasive wearable sensors is poised to advance telehealth for older adults and other vulnerable populations. Extreme heat and other environmental conditions raise serious health challenges that warrant monitoring of real-time physiological data as people go about their normal activities. Mobile systems could be beneficial for many communities, including elite athletes, military special forces, and at-home geriatric monitoring. While some commercial monitors exist, they are bulky, require reconfiguration, and do not fit seamlessly as a simple wearable device. We designed, prototyped and tested an integrated sensor platform that records heart rate, oxygen saturation, physical activity levels, skin temperature, and galvanic skin response. The device uses a small microcontroller to integrate the measurements and store data directly on the device for up to 48+ h. continuously. The device was compared to clinical standards for calibration and performance benchmarking. We found that our system compared favorably with clinical measures, such as fingertip pulse oximetry and infrared thermometry, with high accuracy and correlation. Our novel platform would facilitate an individualized approach to care, particularly those whose access to healthcare facilities is limited. The platform also can be used as a research tool to study physiological responses to a variety of environmental conditions, such as extreme heat, and can be customized to incorporate new sensors to explore other lines of inquiry.

Wearable Vital Signs Monitoring for Patients With Asthma: A Review

Worldwide,an estimated 461 000 people die from asthma attacks each year. While there remain treatments to alleviate asthma symptoms and reduce deaths, patient deterioration needs to be identified in sufficient time. To prevent asthma deterioration, patients need to be aware of personal and environmental triggers and monitor their asthma symptoms. The aim of this article is to provide a comprehensive review of the current state-of-the-art wearable sensors and devices that use vital signs for asthma patient monitoring and management. Among all vital signs, breathing rate and airflow sound are key indicators of asthmatic patients' health that can be measured directly using wearable sensors to provide continuous and constant patient monitoring or indirectly by estimations based on proven algorithms using electrocardiogram (ECG), photoplethysmogram (PPG), and chest movements. ECG and PPG signals are widely used in smart watches and chest bands, enabling easy integration of a more extensive body sensor framework for asthmatic exacerbation prediction. Other vital signs used in asthma patient monitoring include blood oxygen saturation, temperature, blood pressure, verbal sound, and pain responses. The use of wearable vital signs enabled a broad range of wearable sensor application scenarios for asthma monitoring and management.

Wearable devices for remote vital signs monitoring in the outpatient setting: an overview of the field

Early detection of physiological deterioration has been shown to improve patient outcomes. Due to recent improvements in technology, comprehensive outpatient vital signs monitoring is now possible. This is the first review to collate information on all wearable devices on the market for outpatient physiological monitoring.

A scoping review was undertaken. The monitors reviewed were limited to those that can function in the outpatient setting with minimal restrictions on the patient’s normal lifestyle, while measuring any or all of the vital signs: heart rate, ECG, oxygen saturation, respiration rate, blood pressure and temperature.

A total of 270 papers were included in the review. Thirty wearable monitors were examined: 6 patches, 3 clothing-based monitors, 4 chest straps, 2 upper arm bands and 15 wristbands. The monitoring of vital signs in the outpatient setting is a developing field with differing levels of evidence for each monitor. The most common clinical application was heart rate monitoring. Blood pressure and oxygen saturation measurements were the least common applications. There is a need for clinical validation studies in the outpatient setting to prove the potential of many of the monitors identified.

Research in this area is in its infancy. Future research should look at aggregating the results of validity and reliability and patient outcome studies for each monitor and between different devices. This would provide a more holistic overview of the potential for the clinical use of each device.

Neuroscience in service research: an overview and discussion of its possibilities

Purpose

The purpose of this paper is to discuss recent developments in neuroscientific methods and demonstrate its potential for the service field. This work is a call to action for more service researchers to adopt promising and increasingly accessible neuro-tools that allow the service field to benefit from neuroscience theories and insights.

Design/methodology/approach

The paper synthesizes key literature from a variety of domains (e.g. neuroscience, consumer neuroscience and organizational neuroscience) to provide an in-depth background to start applying neuro-tools. Specifically, this paper outlines the most important neuro-tools today and discusses their theoretical and empirical value.

Findings

To date, the use of neuro-tools in the service field is limited. This is surprising given the great potential they hold to advance service research. To stimulate the use of neuro-tools in the service area, the authors provide a roadmap to enable neuroscientific service studies and conclude with a discussion on promising areas (e.g. service experience and servicescape) ripe for neuroscientific input.

Originality/value

The paper offers service researchers a starting point to understand the potential benefits of adopting the neuroscientific method and shows their complementarity with traditional service research methods like surveys, experiments and qualitative research. In addition, this paper may also help reviewers and editors to better assess the quality of neuro-studies in service.

Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources

Investigations in preventive and occupational medicine are often based on the acquisition of data in the customer's daily routine. This requires convenient measurement solutions including physiological, psychological, physical, and sometimes emotional parameters. In this paper, the introduction of a decentralized multi-sensor-fusion approach for a preventive health-management system is described. The aim is the provision of a flexible mobile data-collection platform, which can be used in many different health-care related applications. Different heterogeneous data sources can be integrated and measured data are prepared and transferred to a superordinated data-science-oriented cloud-solution. The presented novel approach focuses on the integration and fusion of different mobile data sources on a mobile data collection system (mDCS). This includes directly coupled wireless sensor devices, indirectly coupled devices offering the datasets via vendor-specific cloud solutions (as e.g., Fitbit, San Francisco, USA and Nokia, Espoo, Finland) and questionnaires to acquire subjective and objective parameters. The mDCS functions as a user-specific interface adapter and data concentrator decentralized from a data-science-oriented processing cloud. A low-level data fusion in the mDCS includes the synchronization of the data sources, the individual selection of required data sets and the execution of pre-processing procedures. Thus, the mDCS increases the availability of the processing cloud and in consequence also of the higher level data-fusion procedures. The developed system can be easily adapted to changing health-care applications by using different sensor combinations. The complex processing for data analysis can be supported and intervention measures can be provided.

Moving beyond self-report data collection in the natural environment: A review of the past and future directions for ambulatory assessment in eating disorders

OBJECTIVE

In recent years, ecological momentary assessment (EMA) has been used to repeatedly assess eating disorder (ED) symptoms in naturalistic settings, which has allowed for increased understanding of temporal processes that potentiate ED behaviors. However, there remain notable limitations of self-report EMA, and with the rapid proliferation of technology there are ever-increasing possibilities to improve ambulatory assessment methods to further the understanding and treatment of EDs. Therefore, the purpose of this review was to (a) systematically review the studies in EDs that have utilized ambulatory assessment methods other than self-report, and (b) provide directions for future research and clinical applications.

METHOD

A systematic literature search of electronic databases was conducted, and data regarding study characteristics and methodological quality were extracted.

RESULTS

The search identified 17 studies that used ambulatory assessment methods to gather objective data, and focused primarily on autonomic functioning, physical activity, and cognitive processes in ED and control groups.

DISCUSSION

Together the literature demonstrates the promise of using a range of ecologically valid ambulatory assessment approaches in EDs, though there remains limited research that has utilized methods other than self-report (e.g., wearable sensors), particularly in recent years. Going forward, there are several technology-enhanced momentary assessment methods that have potential to improve the understanding and treatment of EDs.

Clinical Applicability of a Textile 1-Lead ECG Device for Overnight Monitoring

Even for 1-lead electrocardiography (ECG), single-use gel conductive electrodes are employed in a clinical setting. However, gel electrodes show limited applicability for long-term monitoring due to skin irritation and detachment. In the present study, we investigated the validity of a textile ECG-belt suitable for long-term measurements in clinical use. In order to assess the signal quality and validity of the ECG-belt during sleep, 242 patients (186 males and 56 females, age 52 (interquartile range 42-60) years, body mass index 29 (interquartile range 26-33) kg·m-2) with suspected sleep apnoea underwent overnight polysomnography including standard 1-lead ECG recording. The single intervals between R-peaks (RR-intervals) were calculated from the ECG-signals. We found a mean difference for average RR-intervals of -2.9 ms, a standard error of estimate of 0.39%, as well as a Pearson r of 0.91. Furthermore, we found that the validity of the ECG-belt decreases when lying on the side, which was potentially due to the fitting of the belt. In conclusion, the validity of RR-interval measurements using the ECG-belt is high and it may be further improved for future applications by optimizing wear fitting.

Secondary outcomes of a behavioral sleep intervention: A randomized clinical trial

OBJECTIVE

Nearly 80% of cancer patients struggle with insomnia, which is associated with decreased heart rate variability (HRV) and quality of life (QOL). The aim of this secondary analysis was to evaluate the possible effects of Brief Behavioral Therapy for Cancer-Related Insomnia (BBT-CI), delivered during chemotherapy visits, on QOL and HRV in patients with breast cancer (BC).

METHOD

QOL and HRV data were obtained during a pilot clinical trial assessing the feasibility and effects of BBT-CI on insomnia. A total of 71 BC patients (mean age = 52.5 years) were randomly assigned to either BBT-CI or a healthy-eating control intervention (HEAL). BBT-CI and HEAL were delivered over 6 weeks (2 face-to-face sessions plus 4 phone calls) by trained staff at 4 National Cancer Institute-funded Community Oncology Research Program clinics. QOL was measured with the Functional Assessment of Cancer Therapy (FACT-G) and HRV with the Firstbeat device at baseline and after intervention.

RESULTS

There were significant improvements in QOL after intervention for BBT-CI (FACT-G, p = .009; FACT-B, p = .016; ANCOVA) and 5-min supine HRV measures (SDNN, p = .005; rMSSD, p = .004; HF, p = .009; ANCOVA) compared with HEAL.

CONCLUSIONS

Patients randomized to BBT-CI showed improvements in QOL and HRV, providing support for BBT-CI's possible benefit when delivered in the community oncology setting by trained staff. A more definitive efficacy trial of BBT-CI is currently being planned with sufficient statistical power to evaluate the intervention's clinical utility. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Self-powered smart patch for sweat conductivity monitoring

A self-powered skin patch for the measurement of sweat conductivity is presented. The key component of the patch consists of a paper battery that is activated upon absorption of sweat. This body fluid acts as the battery electrolyte, the conductivity of which has a direct impact on the battery-generated output power and voltage. This particular behaviour enables the operation of a very simple and robust conductivity sensor in direct current mode without needing an external power source. The device presented in this paper takes advantage of this new measurement method to develop a sweat patch for screening cystic fibrosis that operates with an extremely simple electronic circuit that minimizes its cost and environmental impact. The patch provides an unambiguous digital result that can be read in an electrochromic display and yields 95% sensitivity and 100% specificity when tested with artificial eccrine perspiration samples.

A Review of Wearable Solutions for Physiological and Emotional Monitoring for Use by People with Autism Spectrum Disorder and Their Caregivers

The goal of real-time feedback on physiological changes, stress monitoring and even emotion detection is becoming a technological reality. People in their daily life experience varying emotional states, some of which are negative and which can lead to decreased attention, decreased productivity and ultimately, reduced quality of life. Therefore, having a solution that continuously monitors the physiological signals of the person and assesses his or her emotional well-being could be a very valuable tool. This paper aims to review existing physiological and motional monitoring devices, highlight their features and compare their sensing capabilities. Such technology would be particularly useful for certain populations who experience rapidly changing emotional states such as people with autism spectrum disorder and people with intellectual disabilities. Wearable sensing devices present a potential solution that can support and complement existing behavioral interventions. This paper presents a review of existing and emerging products in the market. It reviews the literature on state-of-the-art prototypes and analyzes their usefulness, clinical validity, and discusses clinical perspectives. A small number of products offer reliable physiological internal state monitoring and may be suitable for people with Autism Spectrum Disorder (ASD). It is likely that more promising solutions will be available in the near future. Therefore, caregivers should be careful in their selection of devices that meet the care-receiver's personal needs and have strong research support for reliability and validity.

Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk

With the recent advancement in wearable computing, sensor technologies, and data processing approaches, it is possible to develop smart clothing that integrates sensors into garments. The main objective of this study was to develop the method of automatic recognition of sedentary behavior related to cardiovascular risk based on quantitative measurement of physical activity. The solution is based on the designed prototype of the smart shirt equipped with a processor, wearable sensors, power supply and telemedical interface. The data derived from wearable sensors were used to create feature vector that consisted of the estimation of the user-specific relative intensity and the variance of filtered accelerometer data. The method was validated using an experimental protocol which was designed to be safe for the elderly and was based on clinically validated short physical performance battery (SPPB) test tasks. To obtain the recognition model six classifiers were examined and compared including Linear Discriminant Analysis, Support Vector Machines, K-Nearest Neighbors, Naive Bayes, Binary Decision Trees and Artificial Neural Networks. The classification models were able to identify the sedentary behavior with an accuracy of 95.00% ± 2.11%. Experimental results suggested that high accuracy can be obtained by estimating sedentary behavior pattern using the smart shirt and machine learning approach. The main advantage of the developed method to continuously monitor patient activities in a free-living environment and could potentially be used for early detection of increased cardiovascular risk.

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

The current paper investigates the value and application of a range of physiological and neuroscientific techniques in applied marketing research and consumer science, highlighting new insights from research in social psychology and neuroscience. We review measures of sweat secretion, heart rate, facial muscle activity, eye movements, and electrical brain activity, using techniques including skin conductance, pupillometry, eyetracking, and magnetic brain imaging. For each measure, after a brief explanation of the underlying technique, we illustrate concepts and mechanisms that the measure allows researchers in marketing and consumer science to investigate, with a focus on consumer attitudes and behavior. By providing reviews on recent research that applied these methods in consumer science and relevant related fields, we also highlight methodological and theoretical strengths and limitations, with an emphasis on ecological validity. We argue that the inclusion of physiological and neuroscientific techniques can advance consumer research by providing insights into the often unconscious mechanisms underlying consumer behavior. Therefore, such technologies can help researchers and marketing practitioners understand the mechanisms of consumer behavior and improve predictions of consumer behavior.

Does the Temporal Asymmetry of Short-Term Heart Rate Variability Change during Regular Walking? A Pilot Study of Healthy Young Subjects

The acceleration and deceleration patterns in heartbeat fluctuations distribute asymmetrically, which is known as heart rate asymmetry (HRA). It is hypothesized that HRA reflects the balancing regulation of the sympathetic and parasympathetic nervous systems. This study was designed to examine whether altered autonomic balance during exercise can lead to HRA changes. Sixteen healthy college students were enrolled, and each student undertook two 5-min ECG measurements: one in a resting seated position and another while walking on a treadmill at a regular speed of 5 km/h. The two measurements were conducted in a randomized order, and a 30-min rest was required between them. RR interval time series were extracted from the 5-min ECG data, and HRA (short-term) was estimated using four established metrics, that is, Porta's index (PI), Guzik's index (GI), slope index (SI), and area index (AI), from both raw RR interval time series and the time series after wavelet detrending that removes the low-frequency component of <~0.03 Hz. Our pilot data showed a reduced PI but unchanged GI, SI, and AI during walking compared to resting seated position based on the raw data. Based on the wavelet-detrended data, reduced PI, SI, and AI were observed while GI still showed no significant changes. The reduced PI during walking based on both raw and detrended data which suggests less short-term HRA may underline the belief that vagal tone is withdrawn during low-intensity exercise. GI may not be sensitive to short-term HRA. The reduced SI and AI based on detrended data suggest that they may capture both short- and long-term HRA features and that the expected change in short-term HRA is amplified after removing the trend that is supposed to link to long-term component. Further studies with more subjects and longer measurements are warranted to validate our observations and to examine these additional hypotheses.