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Wearable technologies represent a strong development axis for various medical applications and these devices are increasingly used in daily life as illustrated by smart watches’ popularisation. Combined with new data processing methods, it constitutes a promising opportunity for telemonitoring, triage in mass casualty situations, or early diagnosis after a traffic or sport accident. An approach to processing the physiological data is to develop severity scoring systems to quantify the critical level of an individual’s health status. However, the existing severity scores require a human evaluation. A first version of a severity scoring system adapted to continuous and real-time wearable monitoring is proposed in this article. The focus is made on three physiological parameters straightforwardly measurable with wrist-wearables: heart rate, respiratory rate, and SpO 2 , which may be enough to characterise continuously hemodynamic and respiratory status. Intermediate score functions corresponding to each physiological parameter have been established using a sigmoid model. The boundary conditions have been defined based on a survey conducted among 54 health professionals. An adapted function has also been developed to merge the three intermediate scores into a global score. The scores are associated with a triage tricolour code: green for a low-priority casualty, orange for a delayable one, red for an urgent one. Preliminary confrontation of the new severity scoring system with real data has been carried out using a database of 84 subjects admitted to the intensive care unit. Colour classification by the new scoring system was compared with independent physicians’ direct evaluation as a reference. The prediction success rate values 74% over the entire database. Two examples of continuous monitoring over time are also given. The new score has turned out to be consistent, and may be easily upgraded with the integration of additional vital signs monitoring or medical information.

Globally, a lower‐extremity amputation occurs every 20 s as a complication of a diabetic foot ulcer, underscoring the urgent need for effective preventive strategies. Previous studies have shown that temperature‐based foot monitoring can reduce both the incidence and severity of diabetic foot ulcers. However, real‐world adherence data for remote temperature monitoring remain limited, particularly in diverse or resource‐constrained communities. We conducted a pilot implementation study of 20 adults with diabetes and a history of diabetic foot ulcers to assess adherence to a remote foot temperature monitoring mat within the context of receiving podiatric care. Participants are instructed to stand on the mat for 20 s daily, and data are transmitted wirelessly for remote monitoring. Adherence was defined as use of the mat at least four times a week. Participants demonstrated high adherence to the foot monitoring mat, averaging 6 scans per week, with sustained adherence over the 6‐month study period. These findings suggest that high‐risk patients with diabetes can reliably engage with the foot temperature monitoring technology, supporting its potential as a management tool to improve outcomes and reduce the burden of diabetic foot ulcer‐related complications in high‐risk, resource constrained patient populations. Highlights Our study demonstrates that high risk patients with diabetes from diverse and resource‐constrained communities are highly and consistently adherent to the uptake of foot mat temperature monitoring. These findings support the use of foot temperature monitoring technology as a management tool for diabetic foot ulcer recurrence in this patient population.

Remote patient monitoring (RPM) is recommended for hypertension control. However, less is known about short-term responses of hypertension to RPM and which program components are most important for hypertension control. This study aimed to evaluate the association between frequency of blood pressure monitoring, nurse monitoring, and their combination and hypertension control within 3 months. This retrospective cohort study was conducted among a convenience sample of 1464 patients with hypertension enrolled in the Brook Remote Care RPM program who sought care at any of the 68 participating primary care clinics in New York or Massachusetts, United States, between 2021 and 2023. Patients with at least 3 blood pressure measures for 70% of the weeks they were in the program were defined as having adequate readings. Brook nurses monitored patients from certain clinics, whereas clinic nurses monitored other patients. Hypertension control was defined as a weekly average blood pressure of less than 140/90 mm Hg. Generalized linear models with a binomial specification and log link were used to estimate the prevalence ratio (PR) and 95% CI of the mutually adjusted associations between adequate blood pressure readings and Brook nurse monitoring, as well as their combination with hypertension control, at 4, 8, and 12 weeks, adjusted for patient age and sex. At weeks 4, 8, and 12, patients with adequate readings had 10% (PR=1.10, 95% CI 1.02-1.20), 12% (PR=1.12, 95% CI 1.04-1.20), and 15% (PR=1.15, 95% CI 1.07-1.24) higher prevalence of hypertension control than patients with lower frequencies of readings, respectively. Brook nurse monitoring was associated with 16% (PR=1.16, 95% CI 1.07-1.27), 6% (PR=1.06, 95% CI 0.99-1.15), and 8% (PR=1.08, 95% CI 1.00-1.16) higher prevalence of hypertension control at weeks 4, 8, and 12, respectively, compared to clinical staff monitoring. The combination of adequate readings plus Brook nurse monitoring was associated with 26% (PR=1.26, 95% CI 1.11-1.44), 17% (PR=1.17, 95% CI 1.05-1.31), and 27% (PR=1.27, 95% CI 1.12-1.43) higher prevalence of hypertension control at weeks 4, 8, and 12, respectively, compared to an inadequate number of blood pressure readings and not receiving Brook nurse monitoring. This is the first study to compare outcomes for RPM patients using clinical nurse monitoring and independent staff monitoring. This study represents a contribution to the literature on clinical outcomes for RPM patients with a focus on short-term, rather than longer-term, hypertension control, evaluation of nurse monitoring conducted by Brook Health compared to clinical staff, and the joint association of monitoring frequency and Brook nurse monitoring on hypertension control. Our study findings suggest that both frequency of monitoring and specialized nurse monitoring improve hypertension control within 3 months of program enrollment. The combination of higher monitoring frequency and Brook nurse monitoring may serve as a cost-effective approach to hypertension control in high-risk populations that overcomes the limitations of clinical care staff.

In the context of Doppler radar, studies have examined the changes in the phase shift of the S21 transmission coefficient related to minute movements of the human chest as a response to breathing or heartbeat. Detecting human vital signs remains a challenge, especially when obstacles interfere with the attempt to detect the presence of life. The sensitivity of a measurement system’s perception of vital signs is highly dependent on the monitoring systems and antennas that are used. The current work proposes a computational approach that aims to extract an empirical law of the dependence of the phase shift of the transmission coefficient (S21) on the sensitivity at reception, based upon a set of four parameters. These variables are as follows: (a) the frequency of the continuous wave utilized; (b) the antenna type and its gain/directivity; (c) the electric field strength distribution on the chest surface (and its average value); and (d) the type of material (dielectric properties) impacted by the incident wave. The investigated frequency range is (1–20) GHz, while the simulations are generated using a doublet of dipole or gain-convenient identical Yagi antennas. The chest surface is represented by a planar rectangle that moves along a path of only 3 mm, with a step of 0.3 mm, mimicking respiration movement. The antenna–target system is modeled in the computational space in each new situation considered. The statistics illustrate the multiple regression function, empirically extracted. This enables the subsequent building of a continuous-wave bio-radar Doppler system with controlled and improved sensitivity.

Wearable devices enable the remote collection of health parameters, supporting the outpatient care plans recommended by the World Health Organization to manage chronic diseases. While disease-specific monitoring is accurate, a comprehensive analysis of wearables across various chronic diseases helps to standardize remote patient monitoring systems. This review aimed to identify wearables for remote monitoring of chronic diseases, focusing on (1) wearable devices, (2) sensor types, (3) health parameters, (4) body locations, and (5) medical applications. We developed a search strategy and conducted searches across three databases: PubMed, Web of Science, and Scopus. After reviewing 1160 articles, we selected 61 that addressed cardiovascular, cancer, neurological, metabolic, respiratory, and other diseases. We created a data analysis method based on our 5 objectives to organize the articles for a comprehensive analysis. From the 61 articles, 39 (64%) used wearable bands such as smartwatches, wristbands, armbands, and straps to monitor chronic diseases. Wearable devices commonly included various sensor types, such as accelerometers (n=39, 64%), photoplethysmographic sensors (n=18, 30%), biopotential meters (n=17, 28%), pressure meters (n=11, 18%), and thermometers (n=9, 15%). These sensors collected diverse health parameters, including acceleration (n=39, 64%), heart rate (n=24, 39%), body temperature (n=9, 15%), blood pressure (n=8, 13%), and peripheral oxygen saturation (n=7, 11%). Common sensor body locations were the wrist, followed by the upper arm and the chest. The medical applications of wearable devices were neurological (n=21, 34%) and cardiovascular diseases (n=15, 25%). Additionally, researchers applied wearable devices for wellness and lifestyle monitoring (n=39, 64%), mainly for activity (n=39, 100%) and sleep (n=10, 26%). This review underscores that wearable devices primarily function as bands, commonly worn on the wrist, to monitor chronic diseases. These devices collect data on acceleration, heart rate, body temperature, blood pressure, and peripheral oxygen saturation, with a focus on neurological and cardiovascular diseases. Our findings provide a foundational road map for designing generalized remote patient monitoring systems to manage multimorbidity and support standardized terminology for interoperability across digital health systems. To translate this into practice, we recommend that future research prioritize pragmatic clinical trials with medically certified devices.

Globally, the older population is rapidly increasing and might be a challenge for healthcare providers in the future. Therefore, new methods of providing home-based care are urgently needed. Telemonitoring (TM) has been proposed to optimize patient care and enhance remote monitoring and management by clinicians. This feasibility study aimed to describe the experiences and perceptions of home-based TM among older adults with chronic conditions and healthcare professionals (HCPs). A feasibility study including interviews with older adults and diaries written by HCPs during the intervention. Participants were recruited from two municipalities in central Sweden. The intervention involved home-based TM for 4 months. TM systems, equipped with sensors for monitoring blood pressure, body weight, physical activity, and oxygen saturation, were tailored to individual needs and installed in participants' homes by an IT company. Data were collected between 2023 and 2024 and analysed using deductive content analysis regarding demand, acceptability, implementation and practicality, to examine whether TM is feasible in real-life settings. The data collection included 12 older adults and 21 healthcare professionals. From interviews with older adults (n=4), and diaries (n=9) from HCPs. Older adults measured their blood pressure every morning and entered the data on a tablet. They reported becoming more aware of changes in their health, particularly with body weight and blood pressure. For sustained engagement and motivation, a comprehensive education plan for TM involving patients, relatives, and HCP is essential. This study indicates that raising health awareness among older adults is positive and underscores the importance of person-centered care. However, some aspects were not fully realized in our study, highlighting the need for further research and refinement in TM implementation to better meet the needs of older adults and healthcare professionals. ClinicalTrials.gov Identifier: NCT04955600 registration date 2021-03-01.

Diabetes mellitus is characterized by impaired glucose regulation, predisposing patients to both hyperglycemia and hypoglycemia. Hypoglycemia, particularly frequent in insulin-treated individuals, remains a serious but underrecognized complication. Remote patient monitoring (RPM) technologies, such as continuous glucose monitors, smartphone apps, and hybrid closed-loop systems with remote monitoring capabilities, have emerged as promising tools to improve glycemic control and prevent hypoglycemia in nonclinical settings. Evidence examining the use of RPM technologies has expanded rapidly; however, the scope, characteristics, and reported outcomes of these interventions remain fragmented across modalities and settings. This scoping review aims to systematically map and describe the extent, range, and characteristics of published evidence on RPM interventions for glycemic management among adults with type 1 and type 2 diabetes in nonclinical settings. The review will follow the Joanna Briggs Institute scoping review methodology and adhere to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines. The population, concept, and context framework defines the population as adults with type 1 or type 2 diabetes who experience or are at risk for hypoglycemia; the concept as RPM techniques (continuous glucose monitors, hybrid closed-loop systems with remote monitoring capabilities, telemedicine, and smartphone apps); and the context as nonclinical environments. The PubMed, Embase, and Scopus databases will be searched, supplemented by gray literature. Eligible studies will include clinical trials, observational studies, and cohort studies; reviews, case studies, and non-English articles will be excluded. Two independent reviewers will conduct screening, data extraction, and summarization. Findings will be synthesized descriptively in tabular and narrative formats. At the time of submission, the protocol has been registered, and the formal search strategy is being finalized. As of March 2026, the formal database search has been completed, and screening of studies is scheduled to begin in April 2026. This protocol outlines a structured approach to mapping the current landscape of RPM interventions for glycemic management in nonclinical settings. The completed review will synthesize reported intervention characteristics and outcomes to clarify existing evidence and identify areas for future investigation. OSF Registries 10.17605/OSF.IO/XNBWF; https://osf.io/xnbwf/overview. PRR1-10.2196/88197.

IntroductionExacerbations, impaired health-related quality of life (HRQoL) and reduced exercise capacity increase the risk of hospitalisations and death in chronic obstructive pulmonary disease (COPD). However, their monitoring relies on in-person assessments, potentially delaying early care. While smart sensing technologies can enable remote monitoring, their use in predicting disease worsening remains limited. The TOLIFE Clinical Study A (CSA) aims to develop an artificial intelligence (AI) model integrating clinical data with smart sensing devices data to predict exacerbation onset and changes in HRQoL, dyspnoea and exercise capacity in people with COPD.Methods and analysesTOLIFE CSA is a longitudinal observational study that will recruit 150 clinically stable people with COPD from three clinical sites in Spain, Italy and Germany. Over 1 year, participants will attend quarterly in-person visits to collect clinical data, while being continuously monitored using six unobtrusive smart sensing devices collecting daily metrics calculated from triaxial acceleration, angular velocity, photoplethysmogram, sound intensity, changes in latitude and longitude, ambient light intensity, biomechanical pressure and respiratory airflow parameters. Clinical outcomes are exacerbation onset through medical records; 3-month changes in HRQoL through the COPD Assessment Test and the Clinical COPD Questionnaire; 3-month changes in dyspnoea severity through the modified Medical Research Council Dyspnoea Scale; and 6-month changes in functional exercise capacity through the 6-minute walk test. We will train, internally validate and test AI-based models (Random Forests, XGBoost, multilayer perceptrons, cumulative link model and standard classification model) to predict clinical outcomes.Ethics and disseminationEthical approval was issued for all sites by the Ethical Commission (EC) of the Medical Association of Schleswig-Holstein (Bad Segeberg; vote 074/23 ff), EC of the Tuscany Region–North West Area (Pisa; vote CET10/2023) and EC of Parc de Salut Mar (Barcelona; vote 2023/11230). All participants will sign a written informed consent.Trial registration numberNCT06172712.

Exercise capacity and lifestyle have proven to be important prognostic factors for cardiovascular patients. Both can be ameliorated through different preventive interventions. Cardiac rehabilitation and remote patient monitoring have been proven to reduce cardiac events and cardiovascular mortality. One of the most important goals of cardiac rehabilitation and remote patient monitoring is improving physical fitness and monitoring of cardiovascular parameters, which could predict cardiac deterioration. In order to monitor cardiac patients successfully, reliable and nonobtrusive devices to assess physical activity and cardiovascular parameters need to be available. This validation study aims to determine the accuracy of the Philips Health Band (PHB), a noninvasive, wrist-worn, medically certified device, for the assessment of heart rate (HR) and energy expenditure (EE) in patients with chronic cardiovascular diseases and recreational athletes (RAs). The assessment of HR and EE by the PHB was compared with indirect calorimetry (Oxycon Mobile [OM; CareFusion GmbH]) during an activity protocol consisting of daily activities. Three groups were assessed: patients with heart failure with reduced ejection fraction (HFrEF), patients with stable coronary artery disease (CAD) with preserved left ventricular ejection fraction, and RAs. A total of 57 patients were included: 19 with CAD, 19 with HFrEF, and 19 RAs. HR assessment in the HFrEF and CAD groups was significantly underestimated over the entire protocol by the PHB as compared to the OM, with poor and fair reliability, respectively. No significant difference in HR was found between the PHB and OM over the entire protocol for the RA group, with good reliability (HFrEF: mean difference 3.0; P<.001; intraclass correlation coefficient [ICC] 0.36; CAD: mean difference 2.7; P<.001; ICC 0.55; RA: mean difference 0.8; ICC 0.60). Assessment of EE showed an underestimation over the entire protocol for the RA and CAD group, with poor and fair reliability, respectively. The HFrEF group showed no significant difference in EE assessment over the entire protocol, with poor reliability (HFrEF: mean difference 0.09; ICC 0.32; CAD: mean difference 0.29; P<.001; ICC 0.46; RA: mean difference 0.79; P<.001; ICC 0.26). The responsiveness to detect within-patient changes in activity intensity of the PHB was moderate for the HFrEF and CAD groups and acceptable for the RA group. HR and EE assessment of a medically certified noninvasive sensor using a photoplethysmogram and accelerometer showed poor accuracy and moderate responsiveness during an activity protocol reflecting daily living activities in patients with stable CAD and chronic HFrEF. Accuracy of HR in RAs was good and the responsiveness for both HR and EE was acceptable. This research confirms previous research and stresses the need for better patient-specific algorithms in noninvasive sensors, taking cardiovascular pathology and medication usage into account, for assessing HR and EE prior to their implemention in patient care.

Objective To determine whether mobile phone based monitoring improves asthma control compared with standard paper based monitoring strategies.Design Multicentre randomised controlled trial with cost effectiveness analysis.Setting UK primary care.Participants 288 adolescents and adults with poorly controlled asthma (asthma control questionnaire (ACQ) score ≥1.5) from 32 practices.Intervention Participants were centrally randomised to twice daily recording and mobile phone based transmission of symptoms, drug use, and peak flow with immediate feedback prompting action according to an agreed plan or paper based monitoring.Main outcome measures Changes in scores on asthma control questionnaire and self efficacy (knowledge, attitude, and self efficacy asthma questionnaire (KASE-AQ)) at six months after randomisation. Assessment of outcomes was blinded. Analysis was on an intention to treat basis.Results There was no significant difference in the change in asthma control or self efficacy between the two groups (ACQ: mean change 0.75 in mobile group v 0.73 in paper group, mean difference in change −0.02 (95% confidence interval −0.23 to 0.19); KASE-AQ score: mean change −4.4 v −2.4, mean difference 2.0 (−0.3 to 4.2)). The numbers of patients who had acute exacerbations, steroid courses, and unscheduled consultations were similar in both groups, with similar healthcare costs. Overall, the mobile phone service was more expensive because of the expenses of telemonitoring.Conclusions Mobile technology does not improve asthma control or increase self efficacy compared with paper based monitoring when both groups received clinical care to guidelines standards. The mobile technology was not cost effective.Trial registration Clinical Trials NCT00512837.