Search Results (49)

This study examines the performance of various machine learning (ML) models in predicting Interstitial Glucose (IG) levels using data from wrist-worn wearable sensors. The insights from these predictions can aid in understanding metabolic syndromes and disease states. A public dataset comprising information from the Empatica E4 smart watch, the Dexcom Continuous Glucose Monitor (CGM) measuring IG, and a food log was utilized. The raw data were processed into features, which were then used to train different ML models. This study evaluates the performance of decision tree (DT), support vector machine (SVM), Random Forest (RF), Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Gaussian Naïve Bayes (GNB), lasso cross-validation (LassoCV), Ridge, Elastic Net, and XGBoost models. For classification, IG labels were categorized into high, standard, and low, and the performance of the ML models was assessed using accuracy (40–78%), precision (41–78%), recall (39–77%), F1-score (0.31–0.77), and receiver operating characteristic (ROC) curves. Regression models predicting IG values were evaluated based on R-squared values (−7.84–0.84), mean absolute error (5.54–60.84 mg/dL), root mean square error (9.04–68.07 mg/dL), and visual methods like residual and QQ plots. To assess whether the differences between models were statistically significant, the Friedman test was carried out and was interpreted using the Nemenyi post hoc test. Tree-based models, particularly RF and DT, demonstrated superior accuracy for classification tasks in comparison to other models. For regression, the RF model achieved the lowest RMSE of 9.04 mg/dL with an R-squared value of 0.84, while the GNB model performed the worst, with an RMSE of 68.07 mg/dL. A SHAP analysis identified time from midnight as the most significant predictor. Partial dependence plots revealed complex feature interactions in the RF model, contrasting with the simpler interactions captured by LDA. Full article

Atrial fibrillation (AF) carries a stroke risk, often necessitating anticoagulation, especially in patients with risk factors. With the advent of implantable and wearable heart monitors, episodes of short bouts of atrial arrhythmias called atrial high-rate episodes (AHREs) or subclinical AF (SCAF) are commonly identified. The necessity of anticoagulation in patients with SCAF is unclear. However, recent randomized controlled trials, the NOAH-AFNET 6 and ARTESIA, have offered insights into this matter. Furthermore, a study-level meta-analysis combining data from both these trials has provided more detailed information. Reviewing the information thus far, we can conclude that DOACs can result in a notable reduction in the risk of ischemic stroke and can potentially decrease the risk of debilitating stroke, albeit with an increased risk of major bleeding. Thus, informed, shared decision-making is essential, weighing the potential benefits of stroke prevention against the risk of major bleeding when considering anticoagulation in this patient population. Full article

Smartwatches represent one of the most widely adopted technological innovations among wearable devices. Their evolution has equipped them with an increasing array of features, including the capability to record an electrocardiogram. This functionality allows users to detect potential arrhythmias, enabling prompt intervention or monitoring of existing arrhythmias, such as atrial fibrillation. In our research, we aimed to compile case reports, case series, and cohort studies from the Web of Science, PubMed, Scopus, and Embase databases published until 1 August 2023. The search employed keywords such as “Smart Watch”, “Apple Watch”, “Samsung Gear”, “Samsung Galaxy Watch”, “Google Pixel Watch”, “Fitbit”, “Huawei Watch”, “Withings”, “Garmin”, “Atrial Fibrillation”, “Supraventricular Tachycardia”, “Cardiac Arrhythmia”, “Ventricular Tachycardia”, “Atrioventricular Nodal Reentrant Tachycardia”, “Atrioventricular Reentrant Tachycardia”, “Heart Block”, “Atrial Flutter”, “Ectopic Atrial Tachycardia”, and “Bradyarrhythmia.” We obtained a total of 758 results, from which we selected 57 articles, including 33 case reports and case series, as well as 24 cohort studies. Most of the scientific works focused on atrial fibrillation, which is often detected using Apple Watches. Nevertheless, we also included articles investigating arrhythmias with the potential for circulatory collapse without immediate intervention. This systematic literature review provides a comprehensive overview of the current state of research on arrhythmia detection using smartwatches. Through further research, it may be possible to develop a care protocol that integrates arrhythmias recorded by smartwatches, allowing for timely access to appropriate medical care for patients. Additionally, continuous monitoring of existing arrhythmias using smartwatches could facilitate the assessment of the effectiveness of prescribed therapies. Full article

The proposed energy harvesting system is based on a rotational pendulum-like electromagnetic device. Pendulum energy harvesting systems can be used to generate power for wearable devices such as smart watches and fitness trackers, by harnessing the energy from the human body motion. These systems can also be used to power low-energy-consuming sensors and monitoring devices in industrial settings where consistent ambient vibrations are present, enabling continuous operation without any need for frequent battery replacements. The pendulum-based energy harvester presented in this work was equipped with additional adjustable permanent magnets placed inside the induction coils, governing the movement of the pendulum. This research pioneers a novel electromagnetic energy harvester design that offers customizable potential configurations. Such a design was realized using the 3D printing method for enhanced precision, and analyzed using the finite element method (FEM). The reduced dynamic model was derived for a real-size device and FEM-based simulations were carried out to estimate the distribution and interaction of the magnetic field. Dynamic simulations were performed for the selected magnet configurations of the system. Power output analyses are presented for systems with and without the additional magnets inside the coils. The primary outcome of this research demonstrates the importance of optimization of geometric configuration. Such an optimization was exercised here by strategically choosing the size and positioning of the magnets, which significantly enhanced energy harvesting performance by facilitating easier passage of the pendulum through magnetic barriers. Full article

Mid-gesture interfaces have become popular for specific scenarios, such as interactions with augmented reality via head-mounted displays, specific controls over smartphones, or gaming platforms. This article explores the use of a location-aware mid-air gesture-based command triplet syntax to interact with a smart space. The syntax, inspired by human language, is built as a vocative case with an imperative structure. In a sentence like “Light, please switch on!”, the object being activated is invoked via making a gesture that mimics its initial letter/acronym (vocative, coincident with the sentence’s elliptical subject). A geometrical or directional gesture then identifies the action (imperative verb) and may include an object feature or a second object with which to network (complement), which also represented by the initial or acronym letter. Technically, an interpreter relying on a trainable multidevice gesture recognition layer makes the pair/triplet syntax decoding possible. The recognition layer works on acceleration and position input signals from graspable (smartphone) and free-hand devices (smartwatch and external depth cameras), as well as a specific compiler. On a specific deployment at a Living Lab facility, the syntax has been instantiated via the use of a lexicon derived from English (with respect to the initial letters and acronyms). A within-subject analysis with twelve users has enabled the analysis of the syntax acceptance (in terms of usability, gesture agreement for actions over objects, and social acceptance) and technology preference of the gesture syntax within its three device implementations (graspable, wearable, and device-free ones). Participants express consensus regarding the simplicity of learning the syntax and its potential effectiveness in managing smart resources. Socially, participants favoured the Watch for outdoor activities and the Phone for home and work settings, underscoring the importance of social context in technology design. The Phone emerged as the preferred option for gesture recognition due to its efficiency and familiarity. The system, which can be adapted to different sensing technologies, addresses the scalability concerns (as it can be easily extended for new objects and actions) and allows for personalised interaction. Full article

Currently, wearable technology is an emerging trend that offers remarkable access to our data through smart devices like smartphones, watches, fitness trackers and textiles. As such, wearable devices can enable health monitoring without disrupting our daily routines. In clinical settings, electrocardiograms (ECGs) and photoplethysmographies (PPGs) are used to monitor heart and respiratory behaviors. In more practical settings, accelerometers can be used to estimate the heart rate when they are attached to the chest. They can also help filter out some noise in ECG signals from movement. In this work, we compare the heart rate data extracted from the built-in accelerometer of a commercial smart pen equipped with sensors (STABILO’s DigiPen) to standard ECG monitor readouts. We demonstrate that it is possible to accurately predict the heart rate from the smart pencil. The data collection is carried out with eight volunteers writing the alphabet continuously for five minutes. The signal is processed with a Butterworth filter to cut off noise. We achieve a mean-squared error (MSE) better than 6.685 × ${10}^{-3}$ comparing the DigiPen’s computed $\Delta t$ (time between pulses) with the reference ECG data. The peaks’ timestamps for both signals all maintain a correlation higher than 0.99. All computed heart rates (HR =$\frac{60}{\Delta t}$) from the pen accurately correlate with the reference ECG signals. Full article

Reflection-type photoplethysmography (PPG) pulse sensors used in wearable smart watches, true wireless stereo, etc., have been recently considered a key component for monitoring biological signals such as heart rate, SPO₃, and blood pressure. Typically, the optical front end (OFE) of these PPG sensors is heterogeneously configured and packaged with light sources and receiver chips. In this paper, a novel quarter-annulus photodetector (NQAPD) with identical inner and outer radii of curvature has been developed using a plasma dicing process to realize a ring-type OFE receiver, which maximizes manufacturing efficiency and increases the detector collection area by 36.7% compared to the rectangular PD. The fabricated NQAPD exhibits a high quantum efficiency of over 90% in the wavelength of 500 nm to 740 nm and the highest quantum efficiency of 95% with a responsivity of 0.41 A/W at the wavelength of 530 nm. Also, the NQAPD is shown to increase the SNR of the PPG signal by 5 to 7.6 dB compared to the eight rectangular PDs. Thus, reflective PPG sensors constructed with NQAPD can be applied to various wearable devices requiring low power consumption, high performance, and cost-effectiveness. Full article

Sleep is essential for overall health, yet various sleep disorders disrupt normal sleep patterns, affecting duration, quality, and timing. This pilot study investigate the impact of a food supplement (SPINOFF^®) on both sleep quality and mental well-being in 41 participants (mean age: 45.3 years). Initial assessments revealed sleep disturbances (Pittsburgh Sleep Quality Index—PSQ—mean score: 8.2) and insomnia symptoms (Insomnia Severity Index—ISI— mean score: 12.7). Mental health assessments showed psychological distress (Dass-21 Depression mean score: 4.2, Anxiety mean score: 6.9, Stress mean score: 11.6, Total mean score: 22.7). This study assessed sleep continuity using Awakenings per Night (ApN) via a smartwatch (HELO HEALTH^®) and conducted the study in two phases: baseline (T0) and after 30 days of treatment (T1) (Phase A). No placebo-control was used in this study. After 30 days (Phase B), 21 patients were selected for reassessment. Eleven continued treatment for another 30 days (T2), while ten discontinued. Following the intervention, we observed remarkable improvements in sleep quality and mental distress. The SPINOFF^® supplement significantly reduced the PSQI scores (22.4%), indicating enhanced sleep quality. Additionally, there was a 19.6% decrease in ISI scores, demonstrating a reduction in insomnia symptoms. Moreover, overall psychological distress decreased by 19.5% signifying improved psychological well-being. In the second phase, participants who continued treatment experienced more substantial improvements, with a mean decrease of 0.8 points in PSQI scores (±0.9) and a mean decrease of 0.9 points in ISI scores. Our findings suggest that the SPINOFF^® supplement has the potential to effectively address both sleep disturbances and psychological distress in our study population. Full article

Purpose: Given the growth in the use of wearable measuring technology, this study aimed to investigate the frequency of writing about wearable monitoring devices in the field of sports sciences and sports-related health professions during the years affected by the COVID-19 pandemic (2020 to 2022). The goal was to observe the number of studies right before the quarantine and during the first years of pandemic. Methodology: A systematic literature analysis was performed in the Web of Science Core Collection (WoS CC) and Scopus databases in March 2023. The filters used in the search were the following: original scientific papers in the English language and open access. The research field was sports sciences in the past three years (2020–2022) in the Wos CC, and health professions and medicine in Scopus. Results: The initial search resulted in 54 studies in the WoS, 16 of which were included in a detailed qualitative analysis, and 297 studies in Scopus with 19 of them analyzed (35 altogether). The keywords used were “fitness watch” (sport watch, smartwatch), “smart shoes”, “smart clothing”, “smart ring”, “smart belt”, and “smart glasses”. In the past three years, there has been a steady increase in the number of studies using smart monitoring devices to measure their data (nine in 2020, nine in 2021, and seventeen in 2022). Results showed that the most used device is a smartwatch, while the most carried out studies were about physical activity and daily activities of living. Furthermore, there are more studies about measuring devices being used as testing equipment than about device performance in general. Conclusions: This study summarizes various research conducted in the field of sports with the use of wearable measuring devices to determine the frequency of use of such devices in sport studies. Full article

Background: Smart devices that are able to measure blood pressure (BP) are valuable for hypertension or heart failure management using digital technology. Data regarding their diagnostic accuracy in comparison to standard noninvasive measurement in accordance to Riva-Rocci are sparse. This study compared a wearable watch-type oscillometric BP monitor (Omron HeartGuide), a wearable watch-type infrared BP monitor (Smart Wear), a conventional ambulatory BP monitor, and auscultatory sphygmomanometry. Methods: Therefore, 159 consecutive patients (84 male, 75 female, mean age 64.33 ± 16.14 years) performed observed single measurements with the smart device compared to auscultatory sphygmomanometry (n = 109) or multiple measurements during 24 h compared to a conventional ambulatory BP monitor on the upper arm (n = 50). The two BP monitoring devices were simultaneously worn on the same arm throughout the monitoring period. In a subgroup of 50 patients, single measurements were also performed with an additional infrared smart device. Results: The intraclass correlation coefficient (ICC) between the difference and the mean of the oscillometric Omron HeartGuide and the conventional method for the single measurement was calculated for both systole (0.765) and diastole (0.732). This is exactly how the ICC was calculated for the individual mean values calculated over the 24 h long-term measurement of the individual patients for both systole (0.880) and diastole (0.829). The ICC between the infrared device and the conventional method was “bad” for SBP (0.329) and DBP (0.025). Therefore, no further long-term measurements were performed with the infrared device. Conclusion: The Omron HeartGuide device provided comparable BP values to the standard devices for single and long-term measurements. The infrared smart device failed to acquire valid measurement data. Full article

This aim of this research was to explore the appraisal of the use of smart alert bracelets by older adults diagnosed with dementia. Convenience sampling was adopted to recruit older adults with dementia in Yunlin County, Taiwan. A manual questionnaire survey was conducted, and SPSS 26.0 statistical software was used for analysis. The results of this study showed noticeable positive correlation results in the post-test for the modes “wearing device”, “degree of dementia”, and “field configuration”. Based on the experimental results, the following suggestions are provided: (1) in terms of statistical calculation, the statistical results were affected by changes in some participants; (2) as for the design of equipment, to be more suitable for adult use, the size and color of bracelets need to be optimized; (3) as for the problem of battery charging of the device, because the charging location of the device is not easy to find, it is better to extend device standby time; (4) regarding the selection of equipment, older adults with early-stage dementia could be concerned about the function of the wearable device, so it is recommended to provide a device designed with clear functions, such as a watch, so that older adults are more willing to wear it. Patients diagnosed with moderate and severe dementia should be advised to use concealed non-sensory devices, such as charms and cards, to better facilitate assistance from caregivers in wearing them; and (5) as for the device, in case of a loss event, in addition to mobile phone notifications, other light and sound device notifications can be added, allowing caregivers to pay more attention to information in real time. In summary, the feedback from caregivers and older adults suggests that if the device is to be used without charging, the overall design should be light and small, which is more suitable for service designs. Full article

Resistance training is an exercise modality that involves using weights or resistance to strengthen and tone muscles. It has become popular in recent years, with numerous people including it in their fitness routines to ameliorate their strength, muscle mass, and overall health. Still, resistance training can be complex, requiring careful planning and execution to avoid injury and achieve satisfactory results. Wearable technology has emerged as a promising tool for resistance training, as it allows monitoring and adjusting training programs in real time. Several wearable devices are currently available, such as smart watches, fitness trackers, and other sensors that can yield detailed physiological and biomechanical information. In resistance training research, this information can be used to assess the effectiveness of training programs and identify areas for improvement. Wearable technology has the potential to revolutionize resistance training research, providing new insights and opportunities for developing optimized training programs. This review examines the types of wearables commonly used in resistance training research, their applications in monitoring and optimizing training programs, and the potential limitations and challenges associated with their use. Finally, it discusses future research directions, including the development of advanced wearable technologies and the integration of artificial intelligence in resistance training research. Full article

An erroneous squat movement might cause different injuries in amateur athletes who are not experts in workout exercises. Even when personal trainers watch out for the athletes’ workout performance, light variations in ankles, knees, and lower back movements might not be recognized. Therefore, we present a smart wearable to alert athletes whether their squats performance is correct. We collect data from people experienced with workout exercises and from learners, supervising personal trainers in annotation of data. Then, we use data preprocessing techniques to reduce noisy samples and train Machine Learning models with a small memory footprint to be exported to microcontrollers to classify squats’ movements. As a result, the k-Nearest Neighbors algorithm with k = 5 achieves an 85% performance and weight of 40 KB of RAM. Full article

The use of digital health and wrist-worn wearable technologies have been increasingly utilized, especially during COVID-19 surge, to help monitor patients and vulnerable groups such as elderly people. As one of the countries with highest aging population, South Korean older adults are expected to be familiarized with these healthcare technologies. However, there have been a few studies on the investigation of Korean older adults’ attitude towards the acceptance of wearable technologies, such as a smart health watch after the COVID-19 curve flattened in South Korea. Thus, the purpose of this study is to investigate the acceptability of digital health wearable technology in healthcare by the Korean older adults and their attitude towards the use of smart health watches by using an extended Technology Acceptance Model while considering the context of the COVID-19 pandemic. We performed a cross-sectional survey of Korean adults aged 56 years and older who are living in Busan, and a total of 170 respondents were received. Results reveal that perceived usefulness, perceived ease of use, and facilitating conditions have a significant impact on older Korean’s attitudes towards the use of a smart health watch, while the relationship between social influence and attitude towards its use was found to not be statistically significant. The attitude towards the use of smart health watches had an effect on their intention to use the smartwatch. By using the findings from the study, the digital wearables providers, manufacturers, and promotors can enhance their strategy to elevate the use of digital healthcare wearables among Korean elderly people while ensuring these products are of good quality and affordable, as well as ensuring necessary assistance is provided to the elderly people when utilizing and adopting these wearables in their everyday lives. Moreover, the results of this study can be utilized to accommodate the needs of Korean elderly people regarding their use of smart health watches and help promote the benefits of healthcare wearable technologies after the pandemic subsides. Full article

Long COVID consequences have changed the perception towards disease management, and it is moving towards personal healthcare monitoring. In this regard, wearable devices have revolutionized the personal healthcare sector to track and monitor physiological parameters of the human body continuously. This would be largely beneficial for early detection (asymptomatic and pre-symptomatic cases of COVID-19), live patient conditions, and long COVID monitoring (COVID recovered patients and healthy individuals) for better COVID-19 management. There are multitude of wearable devices that can observe various human body parameters for remotely monitoring patients and self-monitoring mode for individuals. Smart watches, smart tattoos, rings, smart facemasks, nano-patches, etc., have emerged as the monitoring devices for key physiological parameters, such as body temperature, respiration rate, heart rate, oxygen level, etc. This review includes long COVID challenges for frequent monitoring of biometrics and its possible solution with wearable device technologies for diagnosis and post-therapy of diseases. Full article