Relação entre medidas fornecidas por smartwatches e a identificação de síndrome da fragilidade em idosos: revisão de escopo / Relationship between measures provided by smartwatches and identification of frailty syndrome in older adults: a scoping review

Resumo Objetivo Esta Revisão de Escopo teve como objetivo descrever e mapear as medidas disponibilizadas pelos smartwatches como ferramenta para identificação da Síndrome de Fragilidade em idosos. Métodos Foram incluídos estudos publicados em qualquer idioma, sem restrição de data de publicação, que descrevessem o uso de medidas fornecidas por smartwatches na avaliação da Síndrome de Fragilidade e/ou seus critérios em idosos. Descritores em inglês para smartwatches, smartbands, Síndrome da Fragilidade e envelhecimento foram utilizados para desenvolver uma estratégia de busca abrangente, que foi então aplicada para pesquisar nas seguintes bases de dados: COCHRANE LIBRARY, EMBASE, SCOPUS, PUBMED/MEDLINE, LILACS, WEB OF SCIENCE e PEDRO. Resultados A busca inicial identificou um total de 156 artigos e foram identificados 2 artigos a partir da busca manual nas referências dos estudos elegíveis. Em seguida, foram incluídos 4 estudos que utilizaram medidas diárias de contagem de passos para síntese descritiva, e três dos quatro também utilizaram dados relacionados ao sono e FC para avaliar a fragilidade em idosos. Os resultados obtidos nesta revisão indicam que parâmetros derivados de smartwatches têm sido utilizados para identificar estágios de fragilidade em diferentes ambientes, sendo a maioria dos estudos associados a outras condições clínicas. Conclusão Os smartwatches são uma excelente ferramenta de monitoramento de fragilidade por meio de medições diárias de contagem de passos, dados de sono e frequência cardíaca. Os resultados obtidos com o uso desses dispositivos podem sugerir uma avaliação mais ampla dos idosos que enfrentam risco aumentado de desenvolver a Síndrome da Fragilidade.

Abstract Objective This scoping review aimed to describe and map the measures provided by smartwatches as a tool for identifying Frailty Syndrome in older adults. Methods Studies published in any language, without publication date restrictions, that described the use of measures provided by smartwatches in evaluating or identifying Frailty Syndrome and/or its criteria in older adults were included. English descriptors for smartwatches, smartbands, Frailty Syndrome and Older Adults were used to develop a comprehensive search strategy, which was then applied to search the following databases: COCHRANE LIBRARY, EMBASE, SCOPUS, PUBMED/MEDLINE, LILACS, WEB OF SCIENCE and PEDRO. Results The initial search identified a total of 156 articles and 2 articles were identified from the manual search in the references of eligible studies. Next, 4 studies that used daily step count measurements for descriptive synthesis were included, and three of the four also used sleep and heart rate data to assess frailty in older adults. The results obtained in this review indicate that parameters derived from smartwatches have been used to identify stages of frailty in different areas, with the majority of studies being associated with other clinical conditions. Conclusion Smartwatches are an excellent frailty monitoring tool through daily measurements of step count, sleep data and heart rate. The results obtained with the use of these devices may suggest a broader evaluation of older adults who face an increased risk of developing Frailty Syndrome.

Research progress on the application of wearable devices in foot monitoring and management of diabetic patients / 中国实用护理杂志

As the focus of public health work in the world, diabetic foot disease has aroused high public concern. This paper introduces the application of the diabetic foot wearable monitoring equipment types, including plantar pressure monitoring, temperature monitoring, monitoring of the biomechanics and multimode monitoring, and wearable devices application status in patients with diabetes, puts forward the existing problems and prospect, in order to carry out domestic related to diabetic foot wearable monitoring equipment research to provide the reference.

Exploratory study on quantitative analysis of nocturnal breathing patterns in patients with acute heart failure based on wearable devices / 生物医学工程学杂志

Patients with acute heart failure (AHF) often experience dyspnea, and monitoring and quantifying their breathing patterns can provide reference information for disease and prognosis assessment. In this study, 39 AHF patients and 24 healthy subjects were included. Nighttime chest-abdominal respiratory signals were collected using wearable devices, and the differences in nocturnal breathing patterns between the two groups were quantitatively analyzed. Compared with the healthy group, the AHF group showed a higher mean breathing rate (BR_mean) [(21.03 ± 3.84) beat/min vs. (15.95 ± 3.08) beat/min, P < 0.001], and larger R_RSBI_cv [70.96% (54.34%-104.28)% vs. 58.48% (45.34%-65.95)%, P = 0.005], greater AB_ratio_cv [(22.52 ± 7.14)% vs. (17.10 ± 6.83)%, P = 0.004], and smaller SampEn (0.67 ± 0.37 vs. 1.01 ± 0.29, P < 0.001). Additionally, the mean inspiratory time (TI_mean) and expiration time (TE_mean) were shorter, TI_cv and TE_cv were greater. Furthermore, the LBI_cv was greater, while SD1 and SD2 on the Poincare plot were larger in the AHF group, all of which showed statistically significant differences. Logistic regression calibration revealed that the TI_mean reduction was a risk factor for AHF. The BR_ mean demonstrated the strongest ability to distinguish between the two groups, with an area under the curve (AUC) of 0.846. Parameters such as breathing period, amplitude, coordination, and nonlinear parameters effectively quantify abnormal breathing patterns in AHF patients. Specifically, the reduction in TI_mean serves as a risk factor for AHF, while the BR_mean distinguishes between the two groups. These findings have the potential to provide new information for the assessment of AHF patients.

Wearable devices: Perspectives on assessing and monitoring human physiological status / 生物医学工程学杂志

This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyle-induced diseases currently account for a significant portion of all healthcare spending, with this proportion projected to increase with population aging. Wearable devices have emerged as a key technology for implementing large-scale healthcare systems focused on disease prevention and management. Advancements in miniaturized sensors, system integration, the Internet of Things, artificial intelligence, 5G, and other technologies have enabled wearable devices to perform high-quality measurements comparable to medical devices. Through various physical, chemical, and biological sensors, wearable devices can continuously monitor physiological status information in a non-invasive or minimally invasive way, including electrocardiography, electroencephalography, respiration, blood oxygen, blood pressure, blood glucose, activity, and more. Furthermore, by combining concepts and methods from complex systems and nonlinear dynamics, we developed a novel theory of continuous dynamic physiological signal analysis-dynamical complexity. The results of dynamic signal analyses can provide crucial information for disease prevention, diagnosis, treatment, and management. Wearable devices can also serve as an important bridge connecting doctors and patients by tracking, storing, and sharing patient data with medical institutions, enabling remote or real-time health assessments of patients, and providing a basis for precision medicine and personalized treatment. Wearable devices have a promising future in the healthcare field and will be an important driving force for the transformation of the healthcare system, while also improving the health experience for individuals.

Application and research of smart wearable devices for heart and brain diseases related to high altitude / 生物医学工程学杂志

Smart wearable devices play an increasingly important role in physiological monitoring and disease prevention because they are portable, real-time, dynamic and continuous.The popularization of smart wearable devices among people under high-altitude environment would be beneficial for the prevention for heart and brain diseases related to high altitude. The current review comprehensively elucidates the effects of high-altitude environment on the heart and brain of different population and experimental subjects, the characteristics and applications of different types of wearable devices, and the limitations and challenges for their application. By emphasizing their application values, this review provides practical reference information for the prevention of high-altitude disease and the protection of life and health.

Investigation on new paradigm of clinical physiological monitoring by using wearable devices / 生物医学工程学杂志

As a low-load physiological monitoring technology, wearable devices can provide new methods for monitoring, evaluating and managing chronic diseases, which is a direction for the future development of monitoring technology. However, as a new type of monitoring technology, its clinical application mode and value are still unclear and need to be further explored. In this study, a central monitoring system based on wearable devices was built in the general ward (non-ICU ward) of PLA General Hospital, the value points of clinical application of wearable physiological monitoring technology were analyzed, and the system was combined with the treatment process and applied to clinical monitoring. The system is able to effectively collect data such as electrocardiogram, respiration, blood oxygen, pulse rate, and body position/movement to achieve real-time monitoring, prediction and early warning, and condition assessment. And since its operation from March 2018, 1 268 people (657 patients) have undergone wearable continuous physiological monitoring until January 2020, with data from a total of 1 198 people (632 cases) screened for signals through signal quality algorithms and manual interpretation were available for analysis, accounting for 94.48 % (96.19%) of the total. Through continuous physiological data analysis and manual correction, sleep apnea event, nocturnal hypoxemia, tachycardia, and ventricular premature beats were detected in 232 (36.65%), 58 (9.16%), 30 (4.74%), and 42 (6.64%) of the total patients, while the number of these abnormal events recorded in the archives was 4 (0.63%), 0 (0.00%), 24 (3.80%), and 15 (2.37%) cases. The statistical analysis of sleep apnea event outcomes revealed that patients with chronic diseases were more likely to have sleep apnea events than healthy individuals, and the incidence was higher in men (62.93%) than in women (37.07%). The results indicate that wearable physiological monitoring technology can provide a new monitoring mode for inpatients, capturing more abnormal events and provide richer information for clinical diagnosis and treatment through continuous physiological parameter analysis, and can be effectively integrated into existing medical processes. We will continue to explore the applicability of this new monitoring mode in different clinical scenarios to further enrich the clinical application of wearable technology and provide richer tools and methods for the monitoring, evaluation and management of chronic diseases.

Finite element analysis on the biomechanical changes of patellar tendinitis / 中国组织工程研究

BACKGROUND: It is difficult to obtain the biomechanics of patellar tendinitis by using experimental conditions. Finite element method can solve this problem by using its powerful modeling and computer simulation functions. OBJECTIVE: To summarize the application of finite element analysis in several aspects, such as the mechanism of patellar tendinitis, treatment method and design of knee wearable device, so as to provide theoretical guidance for the prevention and rehabilitation of patellar tendinitis, and provide new ideas for the application of finite element analysis in the study of patellar tendinitis. METHODS: The first author used the search terms “finite element analysis, patellar tendon (patellar tendinitis), knee, biomechanics” in Chinese and English, respectively. Relevant literature published from 1981 to 2019 in CNKI, SportDiscus, PubMed and Elsevier databases were searched. RESULTS AND CONCLUSION: At present, a variety of simulation and analysis algorithms for simulating the mechanism of human biomechanics are continuously developed, so as to establish and analyze the knee tissue with complex structure and the wearable device model. The nonlinear and dynamic analysis of the continuous motion of the knee will be realized, and the simulation analysis will be more real. Further exploration of the treatment of patellar tendinitis by using finite element method, research and development of rehabilitation equipment, and design of overall materials and structures of wearable devices will be the development direction of future research.

Application of wearable devices in the diagnosis and treatment of Parkinson disease / 中华老年医学杂志

Parkinson disease(PD)is the second most common neurodegenerative disease,and its motor and non-motor symptoms seriously affect the patients' quality of life.The existing methods of evaluation of PD contain a lot of shortages,such as inter-rater variability and recall bias,which promote patients,clinicians and researchers to have a strong demand for more objective and long-term assessment and monitoring methods.The wearable device-based quantitative technology,which is easy to operate and have the features of objective quantification,daily permanence and meticulous accuracy,makes it have an extensive series of perspective and advantage for application in the management of PD.This article describes,and illustrates with several examples,the applications of wearable devices in the diagnosis and treatment of various motor symptoms such as bradykinesia,resting tremor,gait disorder,motor fluctuation,dyskinesia and non-motor symptoms.We also discuss its current limitations and future directions.

Compensation technique for environmental and light source power variations applied in a polymer optical fiber curvature sensor for wearable devices

Abstract Introduction Polymer optical fibers (POF) are lightweight, present high elastic strain limits, fracture toughness, flexibility in bend, and are not influenced by electromagnetic fields. These characteristics enable the application of POF as curvature sensor and can overcome the limitations of the conventional technologies, especially for wearable and soft robotics devices. Nevertheless, POF based curvature sensors can suffer from environmental and light source power deviations. This paper presents a compensation technique for the environmental and light source power deviations in a POF curvature sensor. Methods The curvature sensor was submitted to variations of temperature, humidity and light source power to characterize the sensor response and evaluate the proposed compensation technique. In addition, tests with the simultaneous variation of the angle and light source power variation were performed. Results Results show that temperature and humidity effects do not lead to significative errors on the sensor measurement for wearable devices application, where a hardware-based compact and portable compensation technique of the light source deviation is applied. Moreover, the sensor with the compensation technique developed is compared with a potentiometer for dynamic measurements and the root-mean-square error of about 1° is obtained, which is lower than sensors based on similar operation principle presented in the literature and some commercially available devices. Conclusions The compensation technique proposed was able to compensate power deviations applied and resulted in a sensor with low errors with the additional advantages of compactness and low-cost, which enable its application as wearable sensors and on the instrumentation of wearable robots.

Evaluation of wearable health monitoring equipment for community-based management of hypertension / 中华健康管理学杂志

Objective@#To evalate the effectiveness and suitability of a wearable health monitoring device for community-based management of hypertension.@*Methods@#In December 2015, 400 patients with hypertension were enrolled from Beijing, Chaoyang. Subjects were divided into an experimental group (220 cases) and control group (180 cases), and baseline data were collected. The control group received follow-up with general planning while the experimental group received wearable health devices. Follow-up was performed three times using a questionnaire (April, August, and December 2016), and medical staff provided feedback and guidance. The experimental group was also classified according to risk factors and intervention measures were individually designed, and included monitor and medication compliance, self-management ability, and social support. Communication between patients and medical staff was recorded to form a case system. Evaluation indexes included accuracy and reliability, blood pressure management efficacy, behavior intervention efficacy, satisfaction, and disease burden. A t-test, non-parametric test, and chi-square test were used to compare the experimental and control groups before and after intervention.@*Results@#At 1-year follow-up, after correcting for differences in baseline information between the two groups, statistically significant differences in numerical indexes were observed for number of visits within 1 month [1(1) vs. 1(1), Z=5.42], payment within 1 month [85(141) yuan vs. 40(70) yuan, Z=-2.66], visiting time [20(20) min vs. 20(15) min, Z=-2.82], exercise times [4.79(2.24) times/week vs. 4.09(2.00) times/week, Z=9.27], medication compliance score [7.33(5.77) vs. 8.70(5.24), Z=6.86], satisfaction [9.27(0.08) vs. 8.88(0.10), Z=11.77], diastolic pressure [(78.93±0.56) mmHg vs. (81.32±0.61)mmHg, F=8.70] (1 mmHg=0.133 kPa), and body mass index [(25.55±0.27) kg/m2 vs. (27.74±0.43) kg/m2, F=-2.24]. In addition, classification indexes adjusted for normalized blood pressure and habitus were different between experimental and control groups (χ2=3.89, 8.38, P≤0.05). The equipment worked well, with performance rates of over 90% (90.9%, 97.3%, and 92.7%).@*Conclusion@#The wearable health monitoring equipment showed good stability and reliability, and was able to effectively support health management in patients with hypertension in the community. At the same time, the equipment can improve healthy lifestyle compliance and awareness or self-management of blood pressure. In this manner, the burden of disease is reduced and the quality of life is improved.

Inteligência Artificial e Medicina / Artificial Intelligence and Medicine

RESUMO Ao mesmo tempo em que se discutem problemas na relação médico-paciente e a deficiência do exame clínico na atenção médica, que torna o diagnóstico clínico mais dependente de exames complementares, enfatiza-se cada vez mais a importância do computador em medicina e na saúde pública. Isto se dá seja pela adoção de sistemas de apoio à decisão clínica, seja pelo uso integrado de novas tecnologias, incluindo as tecnologias vestíveis/corporais (wearable devices), seja pelo armazenamento de grandes volumes de dados de saúde de pacientes e da população. A capacidade de armazenamento e processamento de dados aumentou exponencialmente ao longo dos recentes anos, criando o conceito de big data. A Inteligência Artificial processa esses dados por meio de algoritmos, que tendem a se aperfeiçoar pelo seu próprio funcionamento (self learning) e a propor hipóteses diagnósticas cada vez mais precisas. Sistemas computadorizados de apoio à decisão clínica, processando dados de pacientes, têm indicado diagnósticos com elevado nível de acurácia. O supercomputador da IBM, denominado Watson, armazenou um volume extraordinário de informações em saúde, criando redes neurais de processamento de dados em vários campos, como a oncologia e a genética. Watson assimilou dezenas de livros-textos em medicina, toda a informação do PubMed e Medline, e milhares de prontuários de pacientes do Sloan Kettering Memorial Cancer Hospital. Sua rede de oncologia é hoje consultada por especialistas de um grande número de hospitais em todo o mundo. O supercomputador inglês Deep Mind, da Google, registrou informações de 1,6 milhão de pacientes atendidos no National Health Service (NHS), permitindo desenvolver novos sistemas de apoio à decisão clínica, analisando dados desses pacientes, permitindo gerar alertas sobre a sua evolução, evitando medicações contraindicadas ou conflitantes e informando tempestivamente os profissionais de saúde sobre seus pacientes. O Deep Mind, ao avaliar um conjunto de imagens dermatológicas na pesquisa de melanoma, mostrou um desempenho melhor do que o de especialistas (76% versus 70,5%), com uma especificidade de 62% versus 59% e uma sensibilidade de 82%. Mas se o computador fornece o know-what, caberá ao médico discutir o problema de saúde e suas possíveis soluções com o paciente, indicando o know-why do seu caso. Isto requer uma contínua preocupação com a qualidade da educação médica, enfatizando o conhecimento da fisiopatologia dos processos orgânicos e o desenvolvimento das habilidades de ouvir, examinar e orientar um paciente e, consequentemente, propor um diagnóstico e um tratamento de seu problema de saúde, acompanhando sua evolução.

ABSTRACT While discussions develop regarding problems in the doctor-patient relationship and the deficiency of the clinical examination in medical practice, which leaves diagnoses more dependent of complementary tests, the importance of the computer in medicine and public health is highlighted. This is happening, either through the adoption of clinical decision support systems, the use of new technologies, such as wearable devices, or the storage and processing of large volumes of patient and population data. Data storage and processing capacity has increased exponentially over recent years, creating the concept of "big data". Artificial Intelligence processes such data using algorithms that continually improve through intrinsic self-learning, thus proposing increasingly precise diagnostic hypotheses. Computerized clinical decision support systems, analyzing patient data, have achieved a high degree of accuracy in their diagnoses. IBM's supercomputer, named "Watson", has stored an extraordinary volume of health information, creating a neural network of data processing in several fields, such as oncology and genetics. Watson has assimilated dozens of medical textbooks, all the information from PubMed and Medline, and thousands of medical records from the Sloan Kettering Cancer Memorial Hospital. Its oncology network is now consulted by numerous specialists from all over the world. The English supercomputer Deep-Mind, by Google, has stored data from 1.6 million National Health Service patients, enabling the development of new clinical decision support systems, analysis of these patient data and generating alerts on their evolution in order to avoid contraindicated or conflicting medications, whilst also sending timely updates to the physicians about the health of their patients. Analyzing a set of dermatological images in a melanoma study, Deep-Mind showed a higher level of performance than that of specialists (76% versus 70.5%), with a specificity of 62% versus 59% and a sensitivity of 82%. Nevertheless, whereas the computer provides the know-what, it is the physician that will discuss the medical problem and the possible solutions with the patient, indicating the know-why of his or her case. This area requires continuous focus on the quality of medical training, emphasizing knowledge of the physiopathology of the organic processes and the development of the abilities to listen to, examine and advise a patient and, consequently, propose a diagnosis and treatment, accompanying his or her evolution.

Medical wearable devices and the healthcare model innovation / 中华健康管理学杂志

The design principles of healthcare wearable devices: ambient intelligence, service continuity, and micro-context provide more choice and solutions for the healthcare and social needs, and have the potential to be an integral part of the modern health care system. The use of wearable devices will contribute to the innovation of healthcare data acquisition and healthcare behaviors, the promotion of health consciousness and literacy, it also benefits the patient education, clinical pathway, medical model and health management performance.

Flexible sensors and their application in healthcare / 军事医学

The traditional approach to accessing healthcare information restricts the further development of healthcare services,thus unable to meet the growing needs of individual healthcare.The flexible sensor technology has emerged along with the development of new materials,machinery and manufacturing technology.As a result,textiles,accessories,human skin and even internal body organs can be integrated with various sensors.The popularization of flexible sensors provides new methods for monitoring health,improving therapeutics,investigating disease status and building the human-machine in-terface.Through a systematic investigation of literature,this paper reviews the applications of flexible sensors in health-care,discusses the key technologies,and introduces the common materials and manufacturing technology.

The Information Privacy Protection Issues and Countermeasures Analysis from the Development of Wearable Medical Devices / 中国医学伦理学

This paper introduced the concept of wearable medical equipment, the development trend, a parti-cular way of gathering information and privacy protection from residential to people, to the development trend of da-ta-centric. Thus, this paper analyzes the information privacy protection of ethical challenges are: data has been weakened by the autonomy of the parties, the right to self-determination; The double-edged effect of wearable medical equipment increases the difficulty of the privacy protection, Has not been perfect wearable medical equip-ment behavior increase the difficulty of privacy protection. Privacy protection facing the challenge of wearable medi-cal devices for causes mainly include:commercial interests drive;Privacy violation cost greatly reduced. Doctor-patient information asymmetry, the patients privacy protection consciousness is weak. To solve above problems, and puts forward the countermeasures of information privacy protection:perfect wearable medical equipment's ethics and policies and regulations;improve the wearable medical devices the user's ego to protect consciousness;improve the wearable technology protection capabilities of medical equipment.