RR interval signal quality of a heart rate monitor and an ECG Holter at rest and during exercise.

This study was designed to examine the RR interval signal qualities of a Holter device and a heart rate chest belt monitor at rest and during exercise. Ten healthy individuals completed five low- to high-intensity activities while simultaneously using the medilog® AR12plus Holter monitor and the Polar H10 heart rate monitor. The RR interval signal quality was based on the quantification of the missing RR intervals and RR interval detection errors. Therefore, both measurement systems were compared against visual inspection of the raw electrocardiography signal. The missing and wrong R-wave peak detections were counted manually for both measurement systems. RR interval signal quality was defined as the relative number of correctly detected RR intervals. Overall, RR interval signal qualities of 94.6% and 99.6% were demonstrated for the medilog® AR12plus and the Polar H10. During the high-intensity activities, the RR interval signal quality of the medilog® AR12plus dropped to 89.8%, whereas the Polar H10 maintained a signal quality of 99.4%. The correlation between both systems was high (r = 0.997, p > 0.001). The excellent RR interval signal quality during low- to moderate-intensity activities in the medilog® AR12plus and during low- to high-intensity activities in the Polar H10 demonstrates both measurement systems' validity for the detection of RR intervals throughout a wide range of activities. A simple chest strap such as the Polar H10 might be recommended as the gold standard for RR interval assessments if intense activities with strong body movements are investigated.

Spectral fusion-based breathing frequency estimation; experiment on activities of daily living.

BACKGROUND: We study the estimation of breathing frequency (BF) derived from wearable single-channel ECG signal in the context of mobile daily life activities. Although respiration effects on heart rate variability and ECG morphology have been well established, studies on ECG-derived respiration in daily living settings are scarce; possibly due to considerable amount of disturbances in such data. Yet, unobtrusive BF estimation during everyday activities can provide vital information for both disease management and athletic performance optimization. METHOD AND DATA: For robust ECG-derived BF estimation, we combine the respiratory information derived from R-R interval (RRI) variability and morphological scale variation of QRS complexes (MSV), acquired from ECG signals. Two different fusion techniques are applied on MSV and RRI signals: cross-power spectral density (CPSD) estimation and power spectrum multiplication (PSM). The algorithms were tested on large sets of data collected from 67 participants during office, household and sport activities, simulating daily living activities. We use spirometer reference BF to evaluate and compare our estimations made by different models. RESULTS AND CONCLUSION: PSM acquires the least average error of BF estimation, [Formula: see text] and [Formula: see text], compared to the reference spirometer values. PSM offers approximately 25 and 75% less error in comparison with the CPSD fusion estimation and the estimation by those two exclusive sources, respectively. Our results demonstrate the superiority of both of the fusion approaches, compared to the estimation derived from either of RRI or MSV signals exclusively.

Accuracy of PARTwear Inertial Sensor and Optojump Optical Measurement System for Measuring Ground Contact Time During Running.

Ammann, R, Taube, W, and Wyss, T. Accuracy of PARTwear inertial sensor and Optojump optical measurement system for measuring ground contact time during running. J Strength Cond Res 30(7): 2057-2063, 2016-The aim of this study was to validate the detection of ground contact time (GCT) during running in 2 differently working systems: a small inertial measurement sensor, PARTwear (PW), worn on the shoe laces, and the optical measurement system, Optojump (OJ), placed on the track. Twelve well-trained subjects performed 12 runs each on an indoor track at speeds ranging from 3.0 to 9.0 m·s. GCT of one step per run (total 144) was simultaneously obtained by the PW, the OJ, and a high-speed video camera (HSC), whereby the latter served as reference system. The sampling rate was 1,000 Hz for all methods. Compared with the HSC, the PW and the OJ systems underestimated GCT by -1.3 ± 6.1% and -16.5 ± 6.7% (p-values ≤ 0.05), respectively. The intraclass correlation coefficients between PW and HSC and between OJ and HSC were 0.984 and 0.853 (p-values < 0.001), respectively. Despite the constant systematic underestimation of GCT, analyses indicated that PW successfully recorded GCT over a wide range of speeds. However, results showed only moderate validity for the OJ system, with increasing errors when speed decreased. In conclusion, the PW proved to be a highly useful and valid application, and its use can be recommended not only for laboratory settings but also for field applications. In contrast, data on GCT obtained by OJ during running must be treated with caution, specifically when running speed changes or when comparisons are made with GCT data collected by other measurement systems.

Detecting Soldiers' Fatigue Using Eye-Tracking Glasses: Practical Field Applications and Research Opportunities.

INTRODUCTION: Objectively determining soldiers' fatigue levels could help prevent injuries or accidents resulting from inattention or decreased alertness. Eye-tracking technologies, such as optical eye tracking (OET) and electrooculography (EOG), are often used to monitor fatigue. Eyeblinks-especially blink frequency and blink duration-are known as easily observable and valid biomarkers of fatigue. Currently, various eye trackers (i.e., eye-tracking glasses) are available on the market using either OET or EOG technologies. These wearable eye trackers offer several advantages, including unobtrusive functionality, practicality, and low costs. However, several challenges and limitations must be considered when implementing these technologies in the field to monitor fatigue levels. This review investigates the feasibility of eye tracking in the field focusing on the practical applications in military operational environments. MATERIALS AND METHOD: This paper summarizes the existing literature about eyeblink dynamics and available wearable eye-tracking technologies, exposing challenges and limitations, as well as discussing practical recommendations on how to improve the feasibility of eye tracking in the field. RESULTS: So far, no eye-tracking glasses can be recommended for use in a demanding work environment. First, eyeblink dynamics are influenced by multiple factors; therefore, environments, situations, and individual behavior must be taken into account. Second, the glasses' placement, sunlight, facial or body movements, vibrations, and sweat can drastically decrease measurement accuracy. The placement of the eye cameras for the OET and the placement of the electrodes for the EOG must be chosen consciously, the sampling rate must be minimal 200 Hz, and software and hardware must be robust to resist any factors influencing eye tracking. CONCLUSION: Monitoring physiological and psychological readiness of soldiers, as well as other civil professionals that face higher risks when their attention is impaired or reduced, is necessary. However, improvements to eye-tracking devices' hardware, calibration method, sampling rate, and algorithm are needed in order to accurately monitor fatigue levels in the field.

Eyeblink Detection in the Field: A Proof of Concept Study of Two Mobile Optical Eye-Trackers.

INTRODUCTION: High physical and cognitive strain, high pressure, and sleep deficit are part of daily life for military professionals and civilians working in physiologically demanding environments. As a result, cognitive and physical capacities decline and the risk of illness, injury, or accidents increases. Such unfortunate outcomes could be prevented by tracking real-time physiological information, revealing individuals' objective fatigue levels. Oculometrics, and especially eyeblinks, have been shown to be promising biomarkers that reflect fatigue development. Head-mounted optical eye-trackers are a common method to monitor these oculometrics. However, studies measuring eyeblink detection in real-life settings have been lacking in the literature. Therefore, this study aims to validate two current mobile optical eye-trackers in an unrestrained military training environment. MATERIALS AND METHOD: Three male participants (age 20.0 ± 1.0) of the Swiss Armed Forces participated in this study by wearing three optical eye-trackers, two VPS16s (Viewpointsystem GmbH, Vienna, Austria) and one Pupil Core (Pupil Labs GmbH, Berlin, Germany), during four military training events: Healthcare education, orienteering, shooting, and military marching. Software outputs were analyzed against a visual inspection (VI) of the video recordings of participants' eyes via the respective software. Absolute and relative blink numbers were provided. Each blink detected by the software was classified as a "true blink" (TB) when it occurred in the software output and the VI at the same time, as a "false blink" (FB) when it occurred in the software but not in the VI, and as a "missed blink" (MB) when the software failed to detect a blink that occurred in the VI. The FBs were further examined for causes of the incorrect recordings, and they were divided into four categories: "sunlight," "movements," "lost pupil," and "double-counted". Blink frequency (i.e., blinks per minute) was also analyzed. RESULTS: Overall, 49.3% and 72.5% of registered eyeblinks were classified as TBs for the VPS16 and Pupil Core, respectively. The VPS16 recorded 50.7% of FBs and accounted for 8.5% of MBs, while the Pupil Core recorded 27.5% of FBs and accounted for 55.5% of MBs. The majority of FBs-45.5% and 73.9% for the VPS16 and Pupil Core, respectively-were erroneously recorded due to participants' eye movements while looking up, down, or to one side. For blink frequency analysis, systematic biases (±limits of agreement) stood at 23.3 (±43.5) and -4.87 (±14.1) blinks per minute for the VPS16 and Pupil Core, respectively. Significant differences in systematic bias between devices and the respective VIs were found for nearly all activities (P < .05). CONCLUSION: An objective physiological monitoring of fatigue is necessary for soldiers as well as civil professionals who are exposed to higher risks when their cognitive or physical capacities weaken. However, optical eye-trackers' accuracy has not been specified under field conditions-especially not in monitoring fatigue. The significant overestimation and underestimation of the VPS16 and Pupil Core, respectively, demonstrate the general difficulty of blink detection in the field.

Influence of Soldiers' Cardiorespiratory Fitness on Physiological Responses and Dropouts During a Loaded Long-distance March.

INTRODUCTION: In military service, marching is an important, common, and physically demanding task. Minimizing dropouts, maintaining operational readiness during the march, and achieving a fast recovery are desirable because the soldiers have to be ready for duty, sometimes shortly after an exhausting task. The present field study investigated the influence of the soldiers' cardiorespiratory fitness on physiological responses during a long-lasting and challenging 34 km march. MATERIALS AND METHODS: Heart rate (HR), body core temperature (BCT), total energy expenditure (TEE), energy intake, motivation, and pain sensation were investigated in 44 soldiers (20.3 ± 1.3 years, 178.5 ± 7.0 cm, 74.8 ± 9.8 kg, body mass index: 23.4 ± 2.7 kg × m-2, peak oxygen uptake ($\dot{\rm{V}}$O2peak): 54.2 ± 7.9 mL × kg-1 × min-1) during almost 8 hours of marching. All soldiers were equipped with a portable electrocardiogram to record HR and an accelerometer on the hip, all swallowed a telemetry pill to record BCT, and all filled out a pre- and post-march questionnaire. The influence of aerobic capacity on the physiological responses during the march was examined by dividing the soldiers into three fitness groups according to their $\dot{\rm{V}}$O2peak. RESULTS: The group with the lowest aerobic capacity ($\dot{\rm{V}}$O2peak: 44.9 ± 4.8 mL × kg-1 × min-1) compared to the group with the highest aerobic capacity ($\dot{\rm{V}}$O2peak: 61.7 ± 2.2 mL × kg-1 × min-1) showed a significantly higher (P < .05) mean HR (133 ± 9 bpm and 125 ± 8 bpm, respectively) as well as peak BCT (38.6 ± 0.3 and 38.4 ± 0.2 °C, respectively) during the march. In terms of recovery ability during the break, no significant differences could be identified between the three groups in either HR or BCT. The energy deficit during the march was remarkably high, as the soldiers could only replace 22%, 26%, and 36% of the total energy expenditure in the lower, middle, and higher fitness group, respectively. The cardiorespiratory fittest soldiers showed a significantly higher motivation to perform when compared to the least cardiorespiratory fit soldiers (P = .002; scale from 1 [not at all] to 10 [extremely]; scale difference of 2.3). A total of nine soldiers (16%) had to end marching early: four soldiers (21%) in the group with the lowest aerobic capacity, five (28%) in the middle group, and none in the highest group. CONCLUSION: Soldiers with a high $\dot{\rm{V}}$O2peak showed a lower mean HR and peak BCT throughout the long-distance march, as well as higher performance motivation, no dropouts, and lower energy deficit. All soldiers showed an enormous energy deficit; therefore, corresponding nutritional strategies are recommended.

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.

Accuracy of Distance Recordings in Eight Positioning-Enabled Sport Watches: Instrument Validation Study.

BACKGROUND: Elite athletes and recreational runners rely on the accuracy of global navigation satellite system (GNSS)-enabled sport watches to monitor and regulate training activities. However, there is a lack of scientific evidence regarding the accuracy of such sport watches. OBJECTIVE: The aim was to investigate the accuracy of the recorded distances obtained by eight commercially available sport watches by Apple, Coros, Garmin, Polar, and Suunto when assessed in different areas and at different speeds. Furthermore, potential parameters that affect the measurement quality were evaluated. METHODS: Altogether, 3 × 12 measurements in urban, forest, and track and field areas were obtained while walking, running, and cycling under various outdoor conditions. RESULTS: The selected reference distances ranged from 404.0 m to 4296.9 m. For all the measurement areas combined, the recorded systematic errors (±limits of agreements) ranged between 3.7 (±195.6) m and -101.0 (±231.3) m, and the mean absolute percentage errors ranged from 3.2% to 6.1%. Only the GNSS receivers from Polar showed overall errors <5%. Generally, the recorded distances were significantly underestimated (all P values <.04) and less accurate in the urban and forest areas, whereas they were overestimated but with good accuracy in 75% (6/8) of the sport watches in the track and field area. Furthermore, the data assessed during running showed significantly higher error rates in most devices compared with the walking and cycling activities. CONCLUSIONS: The recorded distances might be underestimated by up to 9%. However, the use of all investigated sport watches can be recommended, especially for distance recordings in open areas.

Accuracy of the Multisensory Wristwatch Polar Vantage's Estimation of Energy Expenditure in Various Activities: Instrument Validation Study.

BACKGROUND: Sport watches and fitness trackers provide a feasible way of obtaining energy expenditure (EE) estimations in daily life as well as during exercise. However, today's popular wrist-worn technologies show only poor-to-moderate EE accuracy. Recently, the invention of optical heart rate measurement and the further development of accelerometers in wrist units have opened up the possibility of measuring EE. OBJECTIVE: This study aimed to validate the new multisensory wristwatch Polar Vantage and its EE estimation in healthy individuals during low-to-high-intensity activities against indirect calorimetry. METHODS: Overall, 30 volunteers (15 females; mean age 29.5 [SD 5.1] years; mean height 1.7 [SD 0.8] m; mean weight 67.5 [SD 8.7] kg; mean maximal oxygen uptake 53.4 [SD 6.8] mL/min·kg) performed 7 activities-ranging in intensity from sitting to playing floorball-in a semistructured indoor environment for 10 min each, with 2-min breaks in between. These activities were performed while wearing the Polar Vantage M wristwatch and the MetaMax 3B spirometer. RESULTS: After EE estimation, a mean (SD) of 69.1 (42.7) kcal and 71.4 (37.8) kcal per 10-min activity were reported for the MetaMax 3B and the Polar Vantage, respectively, with a strong correlation of r=0.892 (P<.001). The systematic bias was 2.3 kcal (3.3%), with 37.8 kcal limits of agreement. The lowest mean absolute percentage errors were reported during the sitting and reading activities (9.1%), and the highest error rates during household chores (31.4%). On average, 59.5% of the mean EE values obtained by the Polar Vantage were within ±20% of accuracy when compared with the MetaMax 3B. The activity intensity quantified by perceived exertion (odds ratio [OR] 2.028; P<.001) and wrist circumference (OR -1.533; P=.03) predicted 29% of the error rates within the Polar Vantage. CONCLUSIONS: The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent. During sitting and reading activities, the EE estimation is very good, whereas during nonsteady activities that require wrist and arm movement, the EE accuracy is only moderate. However, compared with other available wrist-worn EE monitors, the Polar Vantage can be recommended, as it performs among the best.

Positive Effects of Augmented Feedback to Reduce Time on Ground in Well-Trained Runners.

CONTEXT: Successful elite sprint to long-distance runners are known to have shorter ground-contact time (GCT) than their less successful counterparts. PURPOSE: To investigate whether augmented feedback (aF) about GCT can reduce the time on ground (TOG) per minute in long-distance runners and, if so, whether this reduction improves running performance. METHODS: Thirty well-trained runners were allocated to 3 groups. The intervention group (IG) received visual aF about their GCT during 8 high-intensity interval sessions in the 4-wk training period and were instructed to minimize GCT. The 1st control group (CG1) trained with the IG but was not given any feedback. The 2nd control group (CG2) followed their own training routine. Data were obtained pre- and postintervention for all 3 groups. The dependent variable was TOG per minute, computed from step frequency and GCT. RESULTS: The IG significantly reduced TOG (P = .043, -1.7%, 90%CL -3.1;-0.3) and improved their mean 10 × 400-m performance time (P < .001, -1.5%, 90%CL -1.9;-1.1). In contrast, the 2 control groups revealed unchanged values, indicating that normal high-intensity training and an individualized routine without aF were not able to reduce TOG. The fact that CG1 received the same instructions and participated in the same training sessions as the IG underlined that aF was crucial to reduce TOG. CONCLUSIONS: The provision of aF about GCT seems to be a promising approach that should be considered during training practice of well-trained runners.

Gait Asymmetry During 400- to 1000-m High-Intensity Track Running in Relation to Injury History.

PURPOSE: To quantify gait asymmetry in well-trained runners with and without previous injuries during interval training sessions incorporating different distances. METHODS: Twelve well-trained runners participated in 8 high-intensity interval-training sessions on a synthetic track over a 4-wk period. The training consisted of 10 × 400, 8 × 600, 7 × 800, and 6 × 1000-m running. Using an inertial measurement unit, the ground-contact time (GCT) of every step was recorded. To determine gait asymmetry, the GCTs between the left and right foot were compared. RESULTS: Overall, gait asymmetry was 3.3% ± 1.4%, and over the course of a training session, the gait asymmetry did not change (F1,33 = 1.673, P = .205). The gait asymmetry of the athletes with a previous history of injury was significantly greater than that of the athletes without a previous injury. However, this injury-related enlarged asymmetry was detectable only at short (400 m), but not at longer, distances (600-1000 m). CONCLUSION: The gait asymmetry of well-trained athletes differed, depending on their history of injury and the running distance. To detect gait asymmetries, high-intensity runs over relatively short distances are recommended.

Energy expenditure estimation from respiration variables.

The aim of this study was to develop and cross-validate two models to estimate total energy expenditure (TEE) based on respiration variables in healthy subjects during daily physical activities. Ninety-nine male and female subjects systematically varying in age (18-60 years) and body mass index (BMI; 17-36 kg*m-2) completed eleven aerobic activities with a portable spirometer as the criterion measure. Two models were developed using linear regression analyses with the data from 67 randomly selected subjects (50.0% female, 39.9 ± 11.8 years, 25.1 ± 5.2 kg*m-2). The models were cross-validated with the other 32 subjects (49% female, 40.4 ± 10.7 years, 24.7 ± 4.6 kg*m-2) by applying equivalence testing and Bland-and-Altman analyses. Model 1, estimating TEE based solely on respiratory volume, respiratory rate, and age, was significantly equivalent to the measured TEE with a systematic bias of 0.06 kJ*min-1 (0.22%) and limits of agreement of ±6.83 kJ*min-1. Model 1 was as accurate in estimating TEE as Model 2, which incorporated further information on activity categories, heart rate, sex, and BMI. The results demonstrated that respiration variables and age can be used to accurately determine daily TEE for different types of aerobic activities in healthy adults across a broad range of ages and body sizes.

The influence of the gait-related arm swing on elevation gain measured by sport watches.

The elevation gain is an important contributor to the total workload in endurance sports. The purpose of this study was to evaluate the influence of the arm swing on elevation gain in three sport watches (Garmin® Forerunner 910XT, Polar® RS800CX and Suunto® Ambit2) on a flat 400 m outdoor track. Altogether, a total of 120 repetitions of 1,200 m were performed at self-selected speeds corresponding to strolling, walking, jogging and running. During the assessment two devices of each sport watch, one secured on the hip and one on the wrist, were worn by the participants. A small but significant (effect size = .39; p < .001) influence of the arm swing on elevation was revealed in all sport watches. Elevation indication errors recorded on the wrist were significantly larger than the ones recorded on the hip (4.0-7.4 vs. 1.2-5.7 m per 1,200 m; p < .05). Furthermore, when wearing the devices on the wrist, errors in elevation indication increased when gait speed increased. Users should be aware that wearing the devices on the hip can significantly decrease measurement errors. This might be especially relevant for activities with high dynamics, such as jogging and running.

Can a website-delivered computer-tailored physical activity intervention be acceptable, usable, and effective for older people?

Despite the numerous health benefits, population physical activity levels are low and declining with age. A continued increase of Internet access allows for website-delivered interventions to be implemented across age-groups, though older people have typically not been considered for this type of intervention. Therefore, the purpose of this study was to evaluate a website-delivered computer-tailored physical activity intervention, with a specific focus on differences in tailored advice acceptability, website usability, and physical activity change between three age-groups. To mimic "real-life" conditions, the intervention, which provided personalized physical activity feedback delivered via the Internet, was implemented and evaluated without any personal contact for the entire duration of the study. Data were collected online at baseline, 1-week, and 1-month follow-up and analyzed for three age-groups (≤44, 45-59, and ≥60 years) using linear mixed models. Overall, 803 adults received the intervention and 288 completed all measures. The oldest age-group increased physical activity more than the other two groups, spent the most time on the website, though had significantly lower perceived Internet self-confidence scores when compared with the youngest age-group. No differences were found in terms of website usability and tailored advice acceptability. These results suggest that website-delivered physical activity interventions can be suitable and effective for older aged adults.