The Future of Wearable Technologies and Remote Monitoring in Health Care.
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ABSTRACT:
SUBMITTER: Liao Y
PROVIDER: S-EPMC8325475 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThere is growing interest in the potential for wearable and mobile devices to deliver clinically relevant information in real-world contexts. However, there is limited information on their acceptability and barriers to long-term use in people living with psychosis.ObjectiveThis study aimed to describe the development, implementation, feasibility, acceptability, and user experiences of the Sleepsight platform, which harnesses consumer wearable devices and smartphones for the passive and unobtrusive capture of sleep and rest-activity profiles in people with schizophrenia living in their homes.MethodsA total of 15 outpatients with a diagnosis of schizophrenia used a consumer wrist-worn device and smartphone to continuously and remotely gather rest-activity profiles over 2 months. Once-daily sleep and self-rated symptom diaries were also collected via a smartphone app. Adherence with the devices and smartphone app, end-of-study user experiences, and agreement between subjective and objective sleep measures were analyzed. Thresholds for acceptability were set at a wear time or diary response rate of 70% or greater.ResultsOverall, 14 out of 15 participants completed the study. In individuals with a mild to moderate symptom severity at baseline (mean total Positive and Negative Syndrome Scale score 58.4 [SD 14.4]), we demonstrated high rates of engagement with the wearable device (all participants meeting acceptability criteria), sleep diary, and symptom diary (93% and 86% meeting criteria, respectively), with negative symptoms being associated with lower diary completion rate. The end-of-study usability and acceptability questionnaire and qualitative analysis identified facilitators and barriers to long-term use, and paranoia with study devices was not a significant barrier to engagement. Comparison between sleep diary and wearable estimated sleep times showed good correspondence (?=0.50, P<.001).ConclusionsExtended use of wearable and mobile technologies are acceptable to people with schizophrenia living in a community setting. In the future, these technologies may allow predictive, objective markers of clinical status, including early markers of impending relapse.
| S-EPMC6234334 | biostudies-literature
Project description: Not available
| S-EPMC10727511 | biostudies-literature
Project description:Purpose of reviewSensitive, scalable and affordable assays are critically needed for monitoring the success of interventions for preventing, treating and attempting to cure HIV infection. This review evaluates current and emerging technologies that are applicable for both surveillance of HIV drug resistance (HIVDR) and characterization of HIV reservoirs that persist despite antiretroviral therapy and are obstacles to curing HIV infection.Recent findingsNext-generation sequencing (NGS) has the potential to be adapted into high-throughput, cost-efficient approaches for HIVDR surveillance and monitoring during continued scale-up of antiretroviral therapy and rollout of preexposure prophylaxis. Similarly, improvements in PCR and NGS are resulting in higher throughput single genome sequencing to detect intact proviruses and to characterize HIV integration sites and clonal expansions of infected cells.SummaryCurrent population genotyping methods for resistance monitoring are high cost and low throughput. NGS, combined with simpler sample collection and storage matrices (e.g. dried blood spots), has considerable potential to broaden global surveillance and patient monitoring for HIVDR. Recent adaptions of NGS to identify integration sites of HIV in the human genome and to characterize the integrated HIV proviruses are likely to facilitate investigations of the impact of experimental 'curative' interventions on HIV reservoirs.
| S-EPMC6738332 | biostudies-literature
Project description:PurposeAltered respiratory rate (RR) has been identified as an important predictor of serious adverse events during hospitalization. Introduction of a well-tolerated continuous RR monitor could potentially reduce serious adverse events such as opioid-induced respiratory depression. The purpose of this study was to investigate the ability of different monitor devices to detect RR in low care clinical settings.MethodsThis was a prospective method-comparison study with a cross-sectional design. Thoracic impedance pneumography (IPG), frequency modulated continuous wave radar, and an acoustic breath sounds monitor were compared with the gold standard of capnography for their ability to detect RR in breaths per minute (breaths·min-1) in awake postoperative patients in the postanesthesia care unit. The Bland and Altman method for repeated measurements and mixed effect modelling was used to obtain bias and limits of agreement (LoA). Furthermore, the ability of the three devices to assist with correct treatment decisions was evaluated in Clarke Error Grids.ResultsTwenty patients were monitored for 1,203 min, with a median [interquartile range] of 61 [60-63] min per patient. The bias (98.9% LoA) were 0.1 (-7.9 to 7.9) breaths·min-1 for the acoustic monitor, -1.6 (-10.8 to 7.6) for the radar, and -1.9 (-13.1 to 9.2) for the IPG. The extent to which the monitors guided adequate or led to inadequate treatment decisions (determined by Clarke Error Grid analysis) differed significantly between the monitors (P = 0.011). Decisions were correct 96% of the time for acoustic, 95% of the time for radar, and 94% of the time for IPG monitoring devices.ConclusionsNone of the studied devices (acoustic, IPG, and radar monitor) had LoA that were within our predefined (based on clinical judgement) limits of ± 2 breaths·min-1. The acoustic breath sound monitor predicted the correct treatment more often than the IPG and the radar device.
| S-EPMC6244627 | biostudies-literature
Project description:We conducted a systematic literature review to identify key trends associated with remote patient monitoring (RPM) via noninvasive digital technologies over the last decade.A search was conducted in EMBASE and Ovid MEDLINE. Citations were screened for relevance against predefined selection criteria based on the PICOTS (Population, Intervention, Comparator, Outcomes, Timeframe, and Study Design) format. We included studies published between January 1, 2005 and September 15, 2015 that used RPM via noninvasive digital technology (smartphones/personal digital assistants [PDAs], wearables, biosensors, computerized systems, or multiple components of the formerly mentioned) in evaluating health outcomes compared to standard of care or another technology. Studies were quality appraised according to Critical Appraisal Skills Programme.Of 347 articles identified, 62 met the selection criteria. Most studies were randomized control trials with older adult populations, small sample sizes, and limited follow-up. There was a trend toward multicomponent interventions (n?=?26), followed by smartphones/PDAs (n?=?12), wearables (n?=?11), biosensor devices (n?=?7), and computerized systems (n?=?6). Another key trend was the monitoring of chronic conditions, including respiratory (23%), weight management (17%), metabolic (18%), and cardiovascular diseases (16%). Although substantial diversity in health-related outcomes was noted, studies predominantly reported positive findings.This review will help decision makers develop a better understanding of the current landscape of peer-reviewed literature, demonstrating the utility of noninvasive RPM in various patient populations. Future research is needed to determine the effectiveness of RPM via noninvasive digital technologies in delivering patient healthcare benefits and the feasibility of large-scale implementation.
| S-EPMC5240011 | biostudies-literature
Project description:Realization of remote wearable health monitoring (RWHM) technology for the flexible photodiodes is highly desirable in remote-sensing healthcare systems used in space stations, oceans, and forecasting warning, which demands high external quantum efficiency (EQE) and detectivity in NIR region. Traditional inorganic photodetectors (PDs) are mechanically rigid and expensive while the widely reported solution-processed mixed tin-lead (MSP) perovskite photodetectors (PPDs) exhibit a trade-off between EQE and detectivity in the NIR region. Herein, a novel functional passivating antioxidant (FPA) strategy has been introduced for the first time to simultaneously improve crystallization, restrain Sn2+ oxidization, and reduce defects in MSP perovskite films by multiple interactions between thiophene-2-carbohydrazide (TAH) molecules and cations/anions in MSP perovskite. The resultant solution-processed rigid mixed Sn-Pb PPD simultaneously achieves high EQE (75.4% at 840 nm), detectivity (1.8 × 1012 Jones at 840 nm), ultrafast response time (trise /tfall = 94 ns/97 ns), and improved stability. This work also highlights the demonstration of the first flexible photodiode using MSP perovskite and FPA strategy with remarkably high EQE (75% at 840 nm), and operational stability. Most importantly, the RWHM is implemented for the first time in the PIN MSP perovskite photodiodes to remotely monitor the heart rate of humans at rest and after-run conditions.
| S-EPMC9929128 | biostudies-literature
Project description:BackgroundWearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.ObjectiveIn this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.MethodsWe performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.ResultsWe included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations-wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).ConclusionsWearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.
| S-EPMC8826148 | biostudies-literature
Project description:Contemporary cardiac and heart rate monitoring devices capture physiological signals using optical and electrode-based sensors. However, these devices generally lack the form factor and mechanical flexibility necessary for use in ambulatory and home environments. Here, we report an ultrathin (~1 mm average thickness) and highly flexible wearable cardiac sensor (WiSP) designed to be minimal in cost (disposable), light weight (1.2 g), water resistant, and capable of wireless energy harvesting. Theoretical analyses of system-level bending mechanics show the advantages of WiSP's flexible electronics, soft encapsulation layers and bioadhesives, enabling intimate skin coupling. A clinical feasibility study conducted in atrial fibrillation patients demonstrates that the WiSP device effectively measures cardiac signals matching the Holter monitor, and is more comfortable. WiSP's physical attributes and performance results demonstrate its utility for monitoring cardiac signals during daily activity, exertion and sleep, with implications for home-based care.
| S-EPMC6550217 | biostudies-literature
Project description:BackgroundThe digital age, with digital sensors, the Internet of Things (IoT), and big data tools, has opened new opportunities for improving the delivery of health care services, with remote monitoring systems playing a crucial role and improving access to patients. The versatility of these systems has been demonstrated during the current COVID-19 pandemic. Health remote monitoring systems (HRMS) present various advantages such as the reduction in patient load at hospitals and health centers. Patients that would most benefit from HRMS are those with chronic diseases, older adults, and patients that experience less severe symptoms recovering from SARS-CoV-2 viral infection.ObjectiveThis paper aimed to perform a systematic review of the literature of HRMS in primary health care (PHC) settings, identifying the current status of the digitalization of health processes, remote data acquisition, and interactions between health care personnel and patients.MethodsA systematic literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines to identify articles that explored interventions with HRMS in patients with chronic diseases in the PHC setting.ResultsThe literature review yielded 123 publications, 18 of which met the predefined inclusion criteria. The selected articles highlighted that sensors and wearables are already being used in multiple scenarios related to chronic disease management at the PHC level. The studies focused mostly on patients with diabetes (9/26, 35%) and cardiovascular diseases (7/26, 27%). During the evaluation of the implementation of these interventions, the major difficulty that stood out was the integration of information into already existing systems in the PHC infrastructure and in changing working processes of PHC professionals (83%).ConclusionsThe PHC context integrates multidisciplinary teams and patients with often complex, chronic pathologies. Despite the theoretical framework, objective identification of problems, and involvement of stakeholders in the design and implementation processes, these interventions mostly fail to scale up. Despite the inherent limitations of conducting a systematic literature review, the small number of studies in the PHC context is a relevant limitation. This study aimed to demonstrate the importance of matching technological development to the working PHC processes in interventions regarding the use of sensors and wearables for remote monitoring as a source of information for chronic disease management, so that information with clinical value is not lost along the way.
| S-EPMC8734917 | biostudies-literature
Project description:Use of wearable devices that monitor physical activity is projected to increase more than fivefold per half-decade1. We investigated how device-based physical activity energy expenditure (PAEE) and different intensity profiles were associated with all-cause mortality. We used a network harmonization approach to map dominant-wrist acceleration to PAEE in 96,476 UK Biobank participants (mean age 62 years, 56% female). We also calculated the fraction of PAEE accumulated from moderate-to-vigorous-intensity physical activity (MVPA). Over the median 3.1-year follow-up period (302,526 person-years), 732 deaths were recorded. Higher PAEE was associated with a lower hazard of all-cause mortality for a constant fraction of MVPA (for example, 21% (95% confidence interval 4-35%) lower hazard for 20 versus 15 kJ kg-1 d-1 PAEE with 10% from MVPA). Similarly, a higher MVPA fraction was associated with a lower hazard when PAEE remained constant (for example, 30% (8-47%) lower hazard when 20% versus 10% of a fixed 15 kJ kg-1 d-1 PAEE volume was from MVPA). Our results show that higher volumes of PAEE are associated with reduced mortality rates, and achieving the same volume through higher-intensity activity is associated with greater reductions than through lower-intensity activity. The linkage of device-measured activity to energy expenditure creates a framework for using wearables for personalized prevention.
| S-EPMC7116559 | biostudies-literature