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The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

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BACKGROUND: Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity and a predictor of mortality in infected people. Given the large number of wearable devices that capture physiological signals of the human body easily and noninvasively, several studies have used this equipment to measure the HRV of individuals and related these measures to COVID-19. OBJECTIVE: The objective of this study was to assess the utility of HRV measurements obtained from wearable devices as predictive indicators of COVID-19, as well as the onset and worsening of symptoms in affected individuals. METHODS: A systematic review was conducted searching the following databases up to the end of January 2023: Embase, PubMed, Web of Science, Scopus, and IEEE Xplore. Studies had to include (1) measures of HRV in patients with COVID-19 and (2) measurements involving the use of wearable devices. We also conducted a meta-analysis of these measures to reduce possible biases and increase the statistical power of the primary research. RESULTS: The main finding was the association between low HRV and the onset and worsening of COVID-19 symptoms. In some cases, it was possible to predict the onset of COVID-19 before a positive clinical test. The meta-analysis of studies reported that a reduction in HRV parameters is associated with COVID-19. Individuals with COVID-19 presented a reduction in the SD of the normal-to-normal interbeat intervals and root mean square of the successive differences compared with healthy individuals. The decrease in the SD of the normal-to-normal interbeat intervals was 3.25 ms (95% CI -5.34 to -1.16 ms), and the decrease in the root mean square of the successive differences was 1.24 ms (95% CI -3.71 to 1.23 ms). CONCLUSIONS: Wearable devices that measure changes in HRV, such as smartwatches, rings, and bracelets, provide information that allows for the identification of COVID-19 during the presymptomatic period as well as its worsening through an indirect and noninvasive self-diagnosis.

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Frailty is a state of critical loss of physiological complexity resulting in greater vulnerability to stressors and has been characterized as a debility syndrome in the older adult. Changes in functional capacity and the cardiovascular system during aging are the most significant and relevant for this population, including the clinically healthy. In this sense, this review aims to investigate methods to monitor the performance of older adults, such as heart rate variability and verify how it can be related to frailty. It contributes to understanding that the changes in heart variability can be a marker for frailty in older adults.

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Objectives: Thousands of people suffer from cardiovascular diseases. Even though the electrocardiogram is an exam consolidated. The lack of methodological observation in the placement of sensors can compromise the results. This article proposes a wearable vest capable of conditioning cardiac signals from three simultaneous channels, reducing the chance of failures in the exam due to the smaller number of electrodes attached to the patient's body. Methods: It adds the vectorcardiogram technique to the electrocardiogram wearable, which consists of three orthonormal derivations Vx, Vy, and Vz, measuring dynamic components of the heart vector. Results: The display of the cardiac biopotential in the web-mobile application represents the visualization of the twelve derivations synthesized from the Dower transform and the spatial projections of the cardiac loop under a three-dimensional view. Conclusion: Feasibility of integrating the vectorcardiogram with the electrocardiogram exam.

Objetivos: Milhares de pessoas sofrem com doenças cardiovasculares, apesar do Eletrocardiograma ser um exame consolidado, a falta de observação metodológica na colocação dos sensores pode comprometer os resultados. O presente artigo propõe um colete vestível capaz de condicionar sinais cardíacos de três canais simultâneos, reduzindo a chance de falhas na execução do exame em função da menor quantidade de eletrodos fixados ao corpo do paciente. Métodos: Acrescenta a técnica do vetocardiograma ao vestível de eletrocardiograma, que consiste em três derivações ortonormais Vx, Vy e Vz, medindo componentes dinâmicos do vetor coração. Resultados: Exibição do biopotencial cardíaco na aplicação web-mobile representa de forma satisfatória a visualização das doze derivações sintetizadas a partir da transformada de Dower, bem como, as projeções espaciais do loop cardíaco sob uma visão tridimensional. Conclusão: Viabilidade de integração do vetocardiograma ao exame de eletrocardiograma.

Objetivos: Miles de personas padecen enfermedades cardiovasculares, a pesar de que el electrocardiograma es un examen consolidado, la falta de observación metodológica en la colocación de sensores puede comprometer los resultados. Este artículo propone una tecnología vestible capaz de acondicionar las señales cardíacas de tres canales simultáneos, reduciendo la posibilidad de fallas en el examen por la menor cantidad de electrodos adheridos al cuerpo del paciente. Métodos: Agrega la técnica del vetocardiograma al electrocardiograma vestible, que consta de tres derivaciones ortonormales Vx, Vy y Vz, midiendo los componentes dinámicos del vector cardíaco. Resultados: La visualización del biopotencial cardíaco en la aplicación web-móvil representa satisfactoriamente la visualización de las doce derivaciones sintetizadas a partir de la transformada de Dower, así como las proyecciones espaciales del bucle cardíaco bajo una vista tridimensional. Conclusión: Viabilidad de integrar el vetocardiograma con el examen electrocardiográfico.

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On-site monitoring the presence of pesticides on crops and food samples is essential for precision and post-harvest agriculture, which demands nondestructive analytical methods for rapid, low-cost detection that is not achievable with gold standard methods. The synergy between eco-friendly substrates and printed devices may lead to wearable sensors for decentralized analysis of pesticides in precision agriculture. In this paper we report on a wearable non-enzymatic electrochemical sensor capable of detecting carbamate and bipyridinium pesticides on the surface of agricultural and food samples. The low-cost devices (

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PURPOSE: This study aimed to develop and evaluate the feasibility and preliminary efficiency of a methodology to measure the mindfulness state using a wearable device ("Cap") capable of monitoring students' levels of full attention by means of real-time measured heart rate variability (HRV). METHODS: The device was developed to export the data to the user's smartphone via Bluetooth, which in turn stores the securely accessible data in the cloud. The autonomous wearable device consists of electronic boards of the Arduino platform that detect the period in milliseconds between two subsequent referential R peaks of the QRS complex wave through infrared oxygenation sensor. RESULTS: In a population of 13 subjects (8 female, 5 male, age 16.1 years ± 0.58 ), the Z-test ( p < 0.05 ) using rMSSD (root mean squared successive differences) and the Toronto Mindfulness (Curiosity) Scale within two 50 min windows, shows that increased HRV values converge to high values for the mindfulness state when the time difference between R n and R n + 1 samples is greater than 88 ms. CONCLUSION: The device proved to be viable and potentially effective for measuring the state of mindfulness. Thus, further studies should be conducted to test it on a large scale as well as in real classroom situations.

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Sign Language recognition systems aid communication among deaf people, hearing impaired people, and speakers. One of the types of signals that has seen increased studies and that can be used as input for these systems is surface electromyography (sEMG). This work presents the recognition of a set of alphabet gestures from Brazilian Sign Language (Libras) using sEMG acquired from an armband. Only sEMG signals were used as input. Signals from 12 subjects were acquired using a MyoTM armband for the 26 signs of the Libras alphabet. Additionally, as the sEMG has several signal processing parameters, the influence of segmentation, feature extraction, and classification was considered at each step of the pattern recognition. In segmentation, window length and the presence of four levels of overlap rates were analyzed, as well as the contribution of each feature, the literature feature sets, and new feature sets proposed for different classifiers. We found that the overlap rate had a high influence on this task. Accuracies in the order of 99% were achieved for the following factors: segments of 1.75 s with a 12.5% overlap rate; the proposed set of four features; and random forest (RF) classifiers.

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The widespread availability of wearable devices is evolving them into cooperative systems. Communication and distribution aspects such as the Internet of Things, Wireless Body Area Networks, and Local Wireless Networks provide the means to develop multi-device platforms. Nevertheless, the field research environment presents a specific feature set, which increases the difficulty in the adoption of this technology. In this text, we review the main aspects of Field Research Gears and Wearable Devices. This review is made aiming to understand how to create cooperative systems based on wearable devices directed to the Field Research Context. For a better understanding, we developed a case study in which we propose a cooperative system architecture and provide validation aspects. For this matter, we provide an overview of a previous device architecture and study an integration proposal.

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We tested the validity of the Hexoskin wearable vest to monitor heart rate (HR), breathing rate (BR), tidal volume (VT), minute ventilation, and hip motion intensity (HMI) in comparison with laboratory standard devices during lying, sitting, standing, and walking. Twenty healthy young volunteers participated in this study. First, participants walked 6 min on a treadmill at speeds of 1, 3, and 4.5 km/h followed by increasing treadmill grades until 80% of their predicted maximal heart rate. Second, lying, sitting, and standing tasks were performed (5 min each) followed by 6 min of treadmill walking at 80% of their ventilatory threshold. Analysis of each individual's mean values under each resting or exercise condition by the 2 measurement systems revealed low coefficient of variation and high intraclass correlation values for HR, BR, and HMI. The Bland-Altman results from HR, BR, and HMI indicated no deviation of the mean value from zero and relatively small variability about the mean. VT and minute ventilation were provided in arbitrary units by the Hexoskin device; however, relative magnitude of change from Hexoskin closely tracked the laboratory standard method. Hexoskin presented low variability, good agreement, and consistency. The Hexoskin wearable vest was a valid and consistent tool to monitor activities typical of daily living such as different body positions (lying, sitting, and standing) and various walking speeds.

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