Search Results (72)

Smart glasses are promising alternatives for the continuous, unobtrusive monitoring of heart rate (HR). This study validates HR estimates obtained with the “Essilor Connected Glasses” (SmartEW) during sedentary activities. Thirty participants wore the SmartEW, equipped with an IMU sensor for HR estimation, a commercial smartwatch (Garmin Venu 3), and an ECG device (Movesense Flash). The protocol included six static tasks performed under controlled laboratory conditions. The SmartEW algorithm analyzed 22.5 s signal windows using spectral analysis to estimate HR and provide a quality index (QI). Statistical analyses assessed agreement with ECG and the impact of QI on HR accuracy. SmartEW showed high agreement with ECG, especially with QI threshold equal to 70, as a trade-off between accuracy, low error, and acceptable data coverage (80%). Correlation for QI ≥ 70 was high across all the experimental phases (r² up to 0.96), and the accuracy within ±5 bpm reached 95%. QI ≥ 70 also allowed biases to decrease (e.g., from −1.83 to −0.19 bpm while standing), with narrower limits of agreement, compared to ECG. SmartEW showed promising HR accuracy across sedentary activities, yielding high correlation and strong agreement with ECG and Garmin. SmartEW appears suitable for HR monitoring in static conditions, particularly when data quality is ensured. Full article

In this study, the static and kinematic positioning performance of the Garmin GPSMAP 66sr handheld GNSS receiver has been tested. For the static test, GNSS data was collected for 24 h and divided into shorter sessions of 1, 2, and 4 h to assess the performance of the receiver as a function of occupation time. The whole and subgroup data were processed by the relative method for different satellite constellations using three reference stations, to form a very short (45 m), short (5.1 km), and relatively long (73.2 km) baselines. For the kinematic test, the data was collected for approximately 1 h and processed with the relative method. Additionally, the whole and subgroup static and kinematic GNSS data of the Garmin receiver were also processed with the Canadian Spatial Reference System-Precise Point Positioning (CSRS-PPP) online service. All Garmin static and kinematic solutions (both relative and PPP) were compared with those calculated by the geodetic receiver. The overall static results show that the Garmin GPSMAP 66sr handheld receiver provides accuracy in a few centimeters with the relative method when integer ambiguities were correctly fixed and in the decimeter-to-meter level using the PPP technique. For the kinematic scenario, the results were relatively poor within the level of decimeters with the relative method while the level of meters with the PPP technique. Full article

This study assesses the environmental status and water quality of the Saraswati River, an ancient and endangered waterway in Bengal, using an integrated approach. By combining traditional knowledge, advanced geospatial tools, and field analysis, it examines natural and human-induced factors driving the river’s degradation and proposes sustainable restoration strategies. Tools such as the Garmin Global Positioning System (GPS) eTrex10, Google Earth Pro, Landsat imagery, ArcGIS 10.8, and Google Earth Engine (GEE) were used to map the river’s trajectory and estimate its water quality. Remote sensing-derived indices, including the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Salinity Index (NDSI), Normalized Difference Turbidity Index (NDTI), Floating Algae Index (FAI), and Normalized Difference Chlorophyll Index (NDCI), Total Dissolved Solids (TDS), were computed to evaluate parameters such as the salinity, turbidity, chlorophyll content, and water extent. Additionally, field data from 27 sampling locations were analyzed for 11 critical water quality parameters, such as the pH, Total Dissolved Solids (TDS), Electrical Conductivity (EC), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), and microbial content, using an arithmetic weighted water quality index (WQI). The results highlight significant spatial variation in water quality, with WQI values ranging from 86.427 at Jatrasudhi (indicating relatively better conditions) to 358.918 at Gobra Station Road (signaling severe contamination). The pollution is primarily driven by urban solid waste, industrial effluents, agricultural runoff, and untreated sewage. A microbial analysis revealed the presence of harmful species, including Escherichia coli (E. coli), Bacillus, and Entamoeba, with elevated concentrations in regions like Bajra, Chinsurah, and Chandannagar. The study detected heavy metals, fertilizers, and pesticides, highlighting significant anthropogenic impacts. The recommended mitigation measures include debris removal, silt extraction, riverbank stabilization, modern hydraulic structures, improved waste management, systematic removal of water hyacinth and decomposed materials, and spoil bank design in spilling zones to restore the river’s natural flow. Full article

This paper explores the use of wearable technology (Garmin Fenix 7) to monitor physiological and psychological factors contributing to attrition during basic military training. Attrition, or the voluntary departure of recruits from the military, often results from physical and psychological challenges, such as fatigue, injury, and stress, which lead to significant costs for the military. To better understand and mitigate attrition, we designed and implemented a comprehensive and continuous data-capturing methodology to monitor 63 recruits during their basic infantry training. It’s optimized for military use by being minimally invasive (for both recruits and operators), preventing data leakage, and being built for scale. We analysed data collected from two test phases, focusing on seven key psychometric and physical features derived from baseline questionnaires and physiological measurements from wearable devices. The preliminary results revealed that recruits at risk of attrition tend to cluster in specific areas of the feature space in both Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA). Key indicators of attrition included low motivation, low resilience, and a stress mindset. Furthermore, we developed a predictive model using physiological data, such as sleep scores and step counts from Garmin devices, achieving a macro mean absolute error (MAE) of 0.74. This model suggests the potential to reduce the burden of daily wellness questionnaires by relying on continuous, unobtrusive monitoring. Full article

Background: This study compared the early rehabilitation progress of patients undergoing robotic-assisted medial unicompartmental knee arthroplasty (mUKA) and robotic-assisted kinematically aligned total knee arthroplasty (rKA-TKA), focusing on daily activity by step-count measurements. Methods: A retrospective analysis of prospectively collected data from 88 patients (53 rKA-TKA and 35 mUKA) was conducted. Patients wore Garmin Vivofit^® 4 activity trackers pre and postoperatively. Daily step counts were analyzed, and clinical outcomes were assessed using various scores, including the Knee Society Score (KSS) and Forgotten Joint Score (FJS). Results: Preoperative median daily step counts were comparable between groups (rKA-TKA: 3988 and mUKA: 4315; p = 0.128). At 6 and 7 weeks post-surgery, the mUKA group showed significantly higher median step counts (3741 and 4730) compared to the rKA-TKA group (2370 and 2910), with p-values of 0.015 and 0.048, respectively. The mUKA group reached 86.7% of their preoperative step count at week 6 and 100% at week 7, while the rKA-TKA group achieved 59.4% and 73%, respectively. Both groups surpassed their preoperative activity levels by week 9. Clinical outcomes at 2 months and 1 year post-surgery showed no significant differences between groups. Conclusions: While both the mUKA and rKA-TKA patients achieved their preoperative daily activity levels within nine weeks post-surgery, the mUKA patients reached this milestone approximately two weeks earlier. This study demonstrates a clinical benefit of mUKA in terms of faster postoperative remobilization, even when compared to kinematically aligned robotic-assisted TKA. Full article

Physical activity (PA) is essential for healthy aging, but its accurate assessment in older adults remains challenging due to the limitations and biases of traditional clinical assessment. Mobile technologies and wearable sensors offer a more ecological, less biased alternative for evaluating PA in this population. This study aimed to optimize digital phenotyping strategies for assessing PA patterns in older adults, by integrating ecological momentary assessment (EMA) and continuous wearable sensor data collection. Over two weeks, 108 community-dwelling older adults provided real-time EMA responses while their PA was continuously monitored using Garmin Vivo 5 sensors. The combined approach proved feasible, with 67.2% adherence to EMA prompts, consistent across time points (morning: 68.1%; evening: 65.4%). PA predominantly occurred at low (51.4%) and moderate (46.2%) intensities, with midday activity peaks. Motivation and self-efficacy were significantly associated with low-intensity PA (R = 0.20 and 0.14 respectively), particularly in the morning. However, discrepancies between objective step counts and self-reported PA measures, which showed no correlation (R = −0.026, p = 0.65), highlight the complementary value of subjective and objective data sources. These findings support integrating EMA, wearable sensors, and temporal frameworks to enhance PA assessment, offering precise insights for personalized, time-sensitive interventions to promote PA. Full article

This study evaluated the influence of cycle computers on the accuracy of power and cadence data. The research was divided into three phases: (1) a graded exercise test (GXT) at different constant loads to record power and cadence data; (2) a self-paced effort lasting 1 min to measure mean maximal power output (MMP); and (3) a short all-out effort. Eight cyclists completed the GXT, ten participated in the 1-min test, and thirty participated in the sprint effort. All participants pedaled on a controlled-resistance cycle ergometer, and the data were recorded using the ergometer itself and ten synchronized cycle computers of the same brand, configured to record at 1 Hz. The results showed minimal variations in power and cadence between devices during the GXT, suggesting adequate accuracy for constant efforts lasting a certain duration. However, in self-paced and high-intensity efforts (1-min and short all-out efforts), significant differences were observed between several devices, particularly in cadence and mean power, highlighting the relevance of device selection in these contexts. These findings suggest that, while variations in constant efforts may be negligible, in short-duration, high-intensity activities, the choice of device may be crucial for the accuracy and reliability of the data. Full article

Introduction: As wearable technology becomes increasingly popular and sophisticated, independent validation is needed to determine its accuracy and potential applications. Therefore, the purpose of this study was to evaluate the accuracy (validity) of VO2max estimates and blood oxygen saturation measured via pulse oximetry using the Garmin fēnix 6 with a general population participant pool. Methods: We recruited apparently healthy individuals (both active and sedentary) for VO2max (n = 19) and pulse oximetry testing (n = 22). VO2max was assessed through a graded exercise test and an outdoor run, comparing results from the Garmin fēnix 6 to a criterion measurement obtained from a metabolic system. Pulse oximetry involved comparing fēnix 6 readings under normoxic and hypoxic conditions against a medical-grade pulse oximeter. Data analysis included descriptive statistics, error analysis, correlation analysis, equivalence testing, and bias assessment, with the validation criteria set at a concordance correlation coefficient (CCC) > 0.7 and a mean absolute percentage error (MAPE) < 10%. Results: The Garmin fēnix 6 provided accurate VO2max estimates, closely aligning with the 15 s and 30 s averaged laboratory data (MAPE for 30 s avg = 7.05%; Lin’s concordance correlation coefficient for 30 s avg = 0.73). However, it failed to accurately measure blood oxygen saturation (BOS) under any condition or combined analysis (MAPE for combined conditions BOS = 4.29%; Lin’s concordance correlation coefficient for combined conditions BOS = 0.10). Conclusion: While the Garmin fēnix 6 shows promise for estimating the VO2max, reflecting its utility for both individuals and researchers, it falls short in accurately measuring BOS, limiting its application for monitoring acclimatization and managing pulmonary diseases. This research underscores the importance of validating wearable technology to leverage its full potential in enhancing personal health and advancing public health research. Full article

Heart rate (HR) is the most frequently used variable to monitor athletes’ internal load during training and competition. High-intensity effort and abrupt HR changes during exercise have presented measurement accuracy issues depending on the chosen device. Therefore, this study aimed to compare two chest straps (Garmin HRM-Dual and Coospo H6) and one armband (Coospo HW807) during intermittent exercise under controlled laboratory conditions. Thirty active young men performed an indoor cycling protocol consisting of seven intermittent efforts with a 2 min effort stage followed by a 2 min recovery stage. The results show no difference between the chest straps (Garmin vs. Coospo), with a high level of agreement between the two devices (Bias = −0.2 bpm, LoA_up = +2.5 bpm, LoA_low = −2.9 bpm, ICC = 0.6–1.0). Differences were found between the chest straps and the armband during effort stages (±5 bpm, p < 0.05), with similar bias and LoA values in the Garmin Strap vs. Coospo Armband (Bias = −0.5 bpm, LoA_up = 8.3 bpm, LoA_low = −9.3 bpm) and Coospo Strap vs. Coospo Armband (Bias = −0.4 bpm, LoA_up = 8.3 bpm, LoA_low = −9.0 bpm) comparison. Chest straps (Garmin HRM-Dual and Coospo H6) accurately measure HR during intermittent exercise with abrupt HR changes. However, caution should be taken when using armbands (Coospo HW807) to monitor intermittent and high-intensity effort. Full article

During the COVID-19 pandemic, a Canadian recreation centre launched a community-based intervention to increase physical activity (PA) and reduce sedentary behaviour (SB). The Vivo Play Scientist (VPS) program provided a free wearable device (Garmin Vivofit4) that synchronized with a customized eHealth dashboard. Aim: The study investigated the feasibility and effectiveness of the VPS program through the participants’ use and experiences of the device and dashboard using the Technology Acceptance Model (TAM). Method: We employed a concurrent mixed-methods approach of online surveys and semi-structured telephone interviews and estimated the device and dashboard’s perceived usefulness and ease of use with TAM. Results: Of the 318 participants (mean age 39.8) 87 enrolled and completed the survey at baseline-T₀, 4 wks-T₁, and 8 wks-T₂. Maximal-variation sampling was used to select 23 participants (78%, F) for interviews. We compared frequency of use, perceived usefulness and ease of use of the device and dashboard across all surveys using non-parametric statistical tests. A thematic analysis was used to analyze data. Participants had some experience using a wearable device (46%) or eHealth application (49%). A high use (≥4 d/wk.) of Vivofit4 at T₁ (93%) and T₂ (87%) occurred, but dashboard use was less frequent (≥1 d/wk. T₁ 54.0% and T₂ 47.1%). Average levels of perceived usefulness and ease of use for the Vivofit4 and dashboard remained constant from T₁ to T₂. Average daily PA scores decreased from T₁ to T₂ (4.9 to 4.5; p = 0.017). Conclusion: Participants were guarded about the value of the dashboard use and reported several challenges associated with the VPS program, but the free device and dashboard did provide PA support during the pandemic. Full article

Timber harvesting operations, including manual and motor-manual activities, require workers who are in good health to be able to work effectively. The aim of our paper was to introduce a simplified index methodology for workload assessment. Generally available wearable technology, namely Garmin, Biostrap, and Whoop devices, were used. The dependence of the heart rate (HR) on physical workload was examined to calculate the Heart Rate Index. The case study was performed with several variations of chainsaw devices cutting the poplar wood. It was proved that the use of a heavier work tool, MS 500i/90 cm 9.3 kg, contributes both to the creation of a non-ergonomic working position and to an increase in the energy required to perform work, which was represented by an increase in heart rate. With a lighter work tool and a shorter cutting blade, both a decrease in heart rate and a reduction in the working time performed in a non-ergonomic position were achieved. The results can be used in common practice for workers’ self-assessment to increase safety and health protection at work or work productivity, not only in forestry-related professions. Full article

Low-cost, portable devices capable of accurate physiological measurements are attractive tools for coaches, athletes, and practitioners. The purpose of this study was primarily to establish the validity and reliability of Movesense HR+ ECG measurements compared to the criterion three-lead ECG, and secondarily, to test the industry leader Garmin HRM. Twenty-one healthy adults participated in running and cycling incremental test protocols to exhaustion, both with rest before and after. Movesense HR+ demonstrated consistent and accurate R-peak detection, with an overall sensitivity of 99.7% and precision of 99.6% compared to the criterion; Garmin HRM sensitivity and precision were 84.7% and 87.7%, respectively. Bland–Altman analysis compared to the criterion indicated mean differences (SD) in RR’ intervals of 0.23 (22.3) ms for Movesense HR+ at rest and 0.38 (18.7) ms during the incremental test. The mean difference for Garmin HRM-Pro at rest was −8.5 (111.5) ms and 27.7 (128.7) ms for the incremental test. The incremental test correlation was very strong (r = 0.98) between Movesense HR+ and criterion, and moderate (r = 0.66) for Garmin HRM-Pro. This study developed a robust peak detection algorithm and data collection protocol for Movesense HR+ and established its validity and reliability for ECG measurement. Full article

In many regions globally, including low-resource settings, there is a growing trend towards using mHealth technology, such as wearable sensors, to enhance health behaviors and outcomes. However, adoption of such devices in research conducted in low-resource settings lags behind use in high-resource areas. Moreover, there is a scarcity of research that specifically examines the user experience, readiness for and challenges of integrating wearable sensors into health research and community interventions in low-resource settings specifically. This study summarizes the reactions and experiences of young women (N = 57), ages 18 to 24 years, living in poverty in Kampala, Uganda, who wore Garmin vívoactive 3 smartwatches for five days for a research project. Data collected from the Garmins included participant location, sleep, and heart rate. Through six focus group discussions, we gathered insights about the participants’ experiences and perceptions of the wearable devices. Overall, the wearable devices were met with great interest and enthusiasm by participants. The findings were organized across 10 domains to highlight reactions and experiences pertaining to device settings, challenges encountered with the device, reports of discomfort/comfort, satisfaction, changes in daily activities, changes to sleep, speculative device usage, community reactions, community dynamics and curiosity, and general device comfort. The study sheds light on the introduction of new technology in a low-resource setting and also on the complex interplay between technology and culture in Kampala’s slums. We also learned some insights into how wearable devices and perceptions may influence behaviors and social dynamics. These practical insights are shared to benefit future research and applications by health practitioners and clinicians to advance and enhance the implementation and effectiveness of wearable devices in similar contexts and populations. These insights and user experiences, if incorporated, may enhance device acceptance and data quality for those conducting research in similar settings or seeking to address population-specific needs and health issues. Full article

Pickleball is a popular sport. Also popular is wearable technology usage. Because the validity and reliability of wearable technology during pickleball is unknown, the purpose of this research was to evaluate the ability of common devices to return heart rate and estimated energy expenditure during pickleball activity. Twenty adult participants were outfitted with a portable metabolic unit and heart rate monitor (criterion measures). Experimental devices were a Garmin Instinct, Polar Vantage M2, Polar OH1, and Polar Verity Sense. Participants played simulated pickleball for 10 min. Validity measures included mean absolute percent error (MAPE) and Lin’s Concordance Correlation Coefficient (CCC), whereas reliability measures included coefficient of variation (CV) and intraclass correlation coefficient (ICC). The heart rate returned lower than 10% MAPE across all devices (Instinct = 5.73–6.32%, Verity Sense = 2.92–2.97%, OH1 = 3.39–3.45%) and greater than 0.85 CCC (Instinct = 0.85–0.88, Verity Sense = 0.96–0.96, OH1 = 0.93–0.94). The CV was below 10% (Instinct = 9.30%, Verity Sense = 2.68%, OH1 = 5.01%), and ICC was above 0.7 (Instinct = 0.77, Verity Sense = 0.98, OH1 = 0.91). The energy expenditure MAPE was greater than 10% (Instinct = 27.67–28.08%, Vantage M2 = 18.87–23.38%) with CCC lower than 0.7 (Instinct = 0.47–0.49, Vantage M2 = 0.62–0.63). Reliability thresholds were met in the Vantage M2 (CV = 6%, ICC = 0.98) but not in the Instinct (CV = 15%, ICC = 0.86). The Instinct was neither valid nor reliable for estimated energy expenditure, while the Polar Vantage M2 was reliable but not valid. All devices returned valid and reliable heart rates during pickleball. Full article

The power output in cycling is one of the most important factors for athletes and coaches. The cycling community has several commercial gears that can be used. One of the most used is the TACX Neo 2T (TN2T) smart trainer. The objective of this study was to investigate the metrological proprieties of the TN2T (accuracy and reliability), as well as its agreement with the Garmin Vector 3 (GV3) pedals at different power stages. The sample consisted of ten regional-level cyclists with a mean age of 45.6 ± 6.4 years, who regularly participated in regional and national competitions. Residual relative differences were found between the two devices. Both devices showed good reliability with coefficients of variation and intraclass correlation coefficients ranging from 0.03% to 0.15% and from 0.731 to 0.968, respectively. Independent samples t-test comparison between devices showed no significant differences in all power stages (p > 0.05). Bland–Altman plots showed that more than 80% of the plots were within the 95% confidence intervals in all power stages. The present data showed that there were non-significant differences between the two devices at power stages between 100 W and 270 W, with a strong agreement. Therefore, they can be used simultaneously. Full article