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BACKGROUND: Hand function assessment heavily relies on specific task scenarios, making it challenging to ensure validity and reliability. In addition, the wide range of assessment tools, limited and expensive data recording, and analysis systems further aggravate the issue. However, smartphones provide a promising opportunity to address these challenges. Thus, the built-in, high-efficiency sensors in smartphones can be used as effective tools for hand function assessment. OBJECTIVE: This review aims to evaluate existing studies on hand function evaluation using smartphones. METHODS: An information specialist searched 8 databases on June 8, 2023. The search criteria included two major concepts: (1) smartphone or mobile phone or mHealth and (2) hand function or function assessment. Searches were limited to human studies in the English language and excluded conference proceedings and trial register records. Two reviewers independently screened all studies, with a third reviewer involved in resolving discrepancies. The included studies were rated according to the Mixed Methods Appraisal Tool. One reviewer extracted data on publication, demographics, hand function types, sensors used for hand function assessment, and statistical or machine learning (ML) methods. Accuracy was checked by another reviewer. The data were synthesized and tabulated based on each of the research questions. RESULTS: In total, 46 studies were included. Overall, 11 types of hand dysfunction-related problems were identified, such as Parkinson disease, wrist injury, stroke, and hand injury, and 6 types of hand dysfunctions were found, namely an abnormal range of motion, tremors, bradykinesia, the decline of fine motor skills, hypokinesia, and nonspecific dysfunction related to hand arthritis. Among all built-in smartphone sensors, the accelerometer was the most used, followed by the smartphone camera. Most studies used statistical methods for data processing, whereas ML algorithms were applied for disease detection, disease severity evaluation, disease prediction, and feature aggregation. CONCLUSIONS: This systematic review highlights the potential of smartphone-based hand function assessment. The review suggests that a smartphone is a promising tool for hand function evaluation. ML is a conducive method to classify levels of hand dysfunction. Future research could (1) explore a gold standard for smartphone-based hand function assessment and (2) take advantage of smartphones' multiple built-in sensors to assess hand function comprehensively, focus on developing ML methods for processing collected smartphone data, and focus on real-time assessment during rehabilitation training. The limitations of the research are 2-fold. First, the nascent nature of smartphone-based hand function assessment led to limited relevant literature, affecting the evidence's completeness and comprehensiveness. This can hinder supporting viewpoints and drawing conclusions. Second, literature quality varies due to the exploratory nature of the topic, with potential inconsistencies and a lack of high-quality reference studies and meta-analyses.

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In many regions globally, including low-resource settings, there is a growing trend towards using mHealth technology, such as wearable sensors, to enhance health behaviors and outcomes. However, adoption of such devices in research conducted in low-resource settings lags behind use in high-resource areas. Moreover, there is a scarcity of research that specifically examines the user experience, readiness for and challenges of integrating wearable sensors into health research and community interventions in low-resource settings specifically. This study summarizes the reactions and experiences of young women (N = 57), ages 18 to 24 years, living in poverty in Kampala, Uganda, who wore Garmin vívoactive 3 smartwatches for five days for a research project. Data collected from the Garmins included participant location, sleep, and heart rate. Through six focus group discussions, we gathered insights about the participants' experiences and perceptions of the wearable devices. Overall, the wearable devices were met with great interest and enthusiasm by participants. The findings were organized across 10 domains to highlight reactions and experiences pertaining to device settings, challenges encountered with the device, reports of discomfort/comfort, satisfaction, changes in daily activities, changes to sleep, speculative device usage, community reactions, community dynamics and curiosity, and general device comfort. The study sheds light on the introduction of new technology in a low-resource setting and also on the complex interplay between technology and culture in Kampala's slums. We also learned some insights into how wearable devices and perceptions may influence behaviors and social dynamics. These practical insights are shared to benefit future research and applications by health practitioners and clinicians to advance and enhance the implementation and effectiveness of wearable devices in similar contexts and populations. These insights and user experiences, if incorporated, may enhance device acceptance and data quality for those conducting research in similar settings or seeking to address population-specific needs and health issues.

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The COVID-19 pandemic exposed the vulnerabilities of global health care systems, underscoring the need for innovative solutions to meet the demands of an aging population, workforce shortages, and rising physician burnout. In recent years, wearable technology has helped segue various medical specialties into the digital era, yet its adoption in vascular surgery remains limited. This article explores the applications of wearable devices in vascular surgery and explores their potential outlets, such as enhancing primary and secondary prevention, optimizing perioperative care, and supporting surgical training. The integration of artificial intelligence and machine learning with wearable technology further expands its applications, enabling predictive analytics, personalized care, and remote monitoring. Despite the promising prospects, challenges such as regulatory complexities, data security, and interoperability must be addressed. As the digital health movement unfolds, wearable technology could play a pivotal role in reshaping vascular surgery while offering cost-effective, accessible, and patient-centered care.

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BACKGROUND: Telementoring studies found technical challenges in achieving accurate and stable annotations during live surgery using commercially available telestration software intraoperatively. To address the gap, a wireless handheld telestration device was developed to facilitate dynamic user interaction with live video streams. OBJECTIVE: This study aims to find the perceived usability, ergonomics, and educational value of a first-generation handheld wireless telestration platform. METHODS: A prototype was developed with four core hand-held functions: (1) free-hand annotation, (2) cursor navigation, (3) overlay and manipulation (rotation) of ghost (avatar) instrumentation, and (4) hand-held video feed navigation on a remote monitor. This device uses a proprietary augmented reality platform. Surgeons and trainees were invited to test the core functions of the platform by performing standardized tasks. Usability and ergonomics were evaluated with a validated system usability scale and a 5-point Likert scale survey, which also evaluated the perceived educational value of the device. RESULTS: In total, 10 people (9 surgeons and 1 senior resident; 5 male and 5 female) participated. Participants strongly agreed or agreed (SA/A) that it was easy to perform annotations (SA/A 9, 90% and neutral 0, 0%), video feed navigation (SA/A 8, 80% and neutral 1, 10%), and manipulation of ghost (avatar) instruments on the monitor (SA/A 6, 60% and neutral 3, 30%). Regarding ergonomics, 40% (4) of participants agreed or strongly agreed (neutral 4, 40%) that the device was physically comfortable to use and hold. These results are consistent with open-ended comments on the device's size and weight. The average system usability scale was 70 (SD 12.5; median 75, IQR 63-84) indicating an above average usability score. Participants responded favorably to the device's perceived educational value, particularly for postoperative coaching (agree 6, 60%, strongly agree 4, 40%). CONCLUSIONS: This study presents the preliminary usability results of a novel first-generation telestration tool customized for use in surgical coaching. Favorable usability and perceived educational value were reported. Future iterations of the device should focus on incorporating user feedback and additional studies should be conducted to evaluate its effectiveness for improving surgical education. Ultimately, such tools can be incorporated into pedagogical models of surgical coaching to optimize feedback and training.

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OBJECTIVES: In an era when telemedicine is becoming increasingly essential, the development and validation of miniaturized Bioelectrical Impedance Analysis (BIA) devices for accurate and reliable body composition assessment is crucial. This study investigates the BIA Metadieta, a novel miniaturized BIA device, by comparing its performance with that of standard hospital BIA equipment across a diverse demographic. The aim is to enhance remote health monitoring by integrating compact and efficient technology into routine healthcare practices. METHODS: A cross-sectional observational study was conducted with 154 participants from the Clinical Nutrition Unit. The study compared resistance (R), reactance (Xc), and phase angle (PhA) measurements obtained from the BIA Metadieta device and a traditional hospital-based BIA device. RESULTS: Analysis revealed strong positive correlations between the BIA Metadieta and the hospital-based device for R (r = 0.988, P < 0.001), Xc (r = 0.946, P < 0.001), and PhA (r = 0.929, P < 0.001), indicating the miniaturized device's high accuracy and reliability. These correlations were consistent across different genders and BMI categories, demonstrating the device's versatility. CONCLUSIONS: The BIA Metadieta device, with its miniaturized form factor, represents a significant step forward in the field of remote health monitoring, providing a reliable, accurate, and accessible means for assessing body composition.

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The aim of this work was to validate the measurements of three physiological parameters, namely, body temperature, heart rate, and peripheral oxygen saturation, captured with an out-of-the-lab device using measurements taken with clinically proven devices. The out-of-the-lab specialized device was integrated into a customized mHealth application, e-CoVig, developed within the AIM Health project. To perform the analysis, single consecutive measurements of the three vital parameters obtained with e-CoVig and with the standard devices from patients in an intensive care unit were collected, preprocessed, and then analyzed through classical agreement analysis, where we used Lin's concordance coefficient to assess the agreement correlation and Bland-Altman plots with exact confidence intervals for the limits of agreement to analyze the paired data readings. The existence of possible systematic errors was also addressed, where we found the presence of additive errors, which were corrected, and weak proportional biases. We obtained the mean overall agreement between the measurements taken with the novel e-CoVig device and the reference devices for the measured quantities. Although some limitations in this study were encountered, we present more advanced methods for their further assessment.

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The practice of auscultation, interpreting body sounds to assess organ health, has greatly benefited from technological advancements in sensing and electronics. The advent of portable and wearable acoustic sensing devices marks a significant milestone in telemedicine, home health, and clinical diagnostics. This review summarises the contemporary advancements in acoustic sensing devices, categorized based on varied sensing principles, including capacitive, piezoelectric, and triboelectric mechanisms. Some representative acoustic sensing devices are introduced from the perspective of portability and wearability. Additionally, the characteristics of sound signals from different human organs and practical applications of acoustic sensing devices are exemplified. Challenges and prospective trends in portable and wearable acoustic sensors are also discussed, providing insights into future research directions.

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This systematic review examines the components of technology used in device-based monitoring and its impact on hospital service use. The most impactful remote monitoring interventions were those measuring vital signs and behavior, while non-implantable devices had less impact on hospital service use.

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OBJECTIVE: Advances in mobile technology are helping with health management practices, and smart toothbrushes provide proper dental care by collecting and analyzing users' toothbrushing data. The purpose of this study is to assess the effect of a telemonitoring device on oral hygiene management in individuals with intellectual or developmental disabilities and its role in promoting oral health. MATERIALS AND METHODS: Participants were split into two groups: one initially using the telemonitoring device (telemonitoring device/manual toothbrush) and the other using it later (manual toothbrush/telemonitoring device), with a one-month washout period. The study compared plaque index, halitosis, changes in oral microbiota, and guardian questionnaire responses between the groups. RESULTS: In period 1, the QHI index score significantly decreased from 1.93 to 0.83 in the group using the remote monitoring device, compared to an increase from 1.75 to 2.01 in the manual toothbrush group. Additionally, toothbrushing frequency, time, and cooperation increased by 0.82 ± 0.60, 0.82 ± 1.16, and 1.09 ± 0.94, respectively, with initial telemonitoring device use. However, these measures decreased by -1.45 ± 0.68, -1.09 ± 0.70, and - 1.00 ± 1.00 after switching to a manual toothbrush, and decreased by -0.64 ± 0.67, -0.27 ± 1.19, and 0.09 ± 0.94 overall, respectively. However, there were no significant differences in oral microbiota between the groups at these different time points. CONCLUSIONS: The study shows that telemonitoring devices effectively reduce plaque index and improve toothbrushing frequency, time, and cooperation. However, these benefits decrease after switching to a manual toothbrush. Follow-up is needed to assess satisfaction and compliance with telemonitoring device use. CLINICAL RELEVANCE: Using telemonitoring devices in the oral health management of individuals with intellectual and developmental disabilities can improve their oral health quality.

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INTRODUCTION: The need for remote ventilator control has been highlighted by the COVID-19 Public Health Emergency. Remote ventilator control from outside a patient's room can improve response time to patient needs, protect health care workers, and reduce personal protective equipment (PPE) consumption. Extending remote control to distant locations can expand the capabilities of frontline health care workers by delivering specialized clinical expertise to the point of care, which is much needed in diverse health care settings, such as tele-critical care and military medicine. However, the safety and effectiveness of remote ventilator control can be affected by many risk factors, including communication failures and network disruptions. Consensus safety requirements and test methods are needed to assess the resilience and safety of remote ventilator control under communication failures and network disruptions. MATERIALS AND METHODS: We designed two test methods to assess the robustness, usability, and safety of a remote ventilator control prototype system jointly developed by Nihon Kohden OrangeMed, Inc. and DocBox, Inc. ("the NK-DocBox system") to control the operation of an NKV-550 critical care ventilator under communication failures and network disruptions. First, the robustness of the NKV-550 ventilator was tested using a remote-control application developed on OpenICE - an open-source medical device interoperability platform - to transmit customized high-frequency and erroneous remote-control commands that could be caused by communication failures in a real-world environment. The second method utilized a network emulator to create different types and severity of network quality of service (QoS) degradation, including bandwidth throttling, network delay and jitter, packet drop and reordering, and bit errors, in the NKV-DocBox system to quantitatively assess the impact on system usability and safety. RESULTS: The NKV-550 ventilator operated as expected when remote-control commands arrived as fast as once per second. It ignored erroneous commands attempting to adjust invalid ventilation parameters. When facing commands that set the ventilation mode and parameters to invalid values, it reset the ventilation mode or parameters to default values, the safety implication of which may merit further evaluation. When any network QoS attribute (except for packet reordering) started to degrade, the NK-DocBox System experienced interference to its remote-control function, such as delays in the transmission of ventilator data and remote-control commands within the system. When the network QoS was worse than 500 ms network delay, 100 ms network jitter, 1% data drop rate, 12 Mbps minimal bandwidth, or 1e-6 bit error rate, the system became unsafe to use. For example, ventilator waveforms visualized on the remote-control application demonstrated freezes, out-of-synchronization, and moving backwards; and the connection between the ventilator and the remote-control application became unstable. CONCLUSION: The presented test methods confirmed the robustness of the NKV-550 ventilator against high-frequency and erroneous remote control, quantified the impact of network disruptions on the usability, reliability, and safety of the NK-DocBox system and identified the minimum network QoS requirements for it to function safely. These generalizable test methods can be customized to evaluate other remote ventilator control technologies and remote control of other types of medical devices against communication failures and network disruptions.

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BACKGROUND: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. METHODS: Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). RESULTS: Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %. LIMITATIONS: Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected. CONCLUSION: Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

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Background: Mobile mental health apps are a cost-effective option for managing mental health problems, such as posttraumatic stress disorder (PTSD). The efficacy of mobile health (mHealth) apps depends on engagement with the app, but few studies have examined how users engage with different features of mHealth apps for PTSD. Objective: This study aims to examine the relationship between app engagement indices and PTSD symptom reduction using data from an unblinded pilot randomized controlled trial of "Renew" (Vertical Design), an exposure-based app for PTSD with and without coaching support. Because exposure is an effective approach for treating PTSD, we expected that engagement with exposure activities would be positively related to symptom reduction, over and above overall app usage. Methods: Participants were veterans (N=69) with clinically significant PTSD symptoms who were recruited online using Facebook advertisements and invited to use the Renew app as often as they wanted over a 6-week period. Participants completed screening and assessments online but provided informed consent, toured the app, and completed feedback interviews via telephone. We assessed users' self-reported PTSD symptoms before and after a 6-week intervention period and collected app usage data using a research-instrumented dashboard. To examine overall app engagement, we used data on the total time spent in the app, the number of log-in days, and the number of points that the user gained in the app. To examine engagement with exposure components, we used data on total time spent completing exposure activities (both in vivo and imaginal), the number of in vivo exposure activities completed, and the number of characters written in response to imaginal exposure prompts. We used hierarchical regression analyses to test the effect of engagement indices on change in PTSD symptoms. Results: Usage varied widely. Participants spent an average of 166.09 (SD 156.52) minutes using Renew, over an average of 14.7 (SD 10.71) mean log-in days. Engagement with the exposure components of the app was positively associated with PTSD symptom reduction (F6,62=2.31; P=.04). Moreover, this relationship remained significant when controlling for overall engagement with the app (ΔF3,62=4.42; P=.007). The number of characters written during imaginal exposure (ß=.37; P=.009) and the amount of time spent completing exposure activities (ß=.36; P=.03) were significant contributors to the model. Conclusions: To our knowledge, this is the first study to show a relationship between symptom improvement and engagement with the active therapeutic components of an mHealth app (ie, exposure) for PTSD. This relationship held when controlling for overall app use, which suggests that it was engagement with exposure, specifically, that was associated with symptom change. Future work to identify ways of promoting greater engagement with self-guided exposure may help improve the effectiveness of mHealth apps for PTSD.

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IoT sensors offer a wide range of sensing capabilities, many of which have potential health applications. Existing solutions for IoT in healthcare have notable limitations, such as closed-source, limited I/O protocols, limited cloud platform support, and missing specific functionality for health use cases. Developing an open-source internet of things (IoT) gateway solution that addresses these limitations and provides reliability, broad applicability, and utility is highly desirable. Combining a wide range of sensor data streams from IoT devices with ambulatory mHealth data would open up the potential to provide a detailed 360-degree view of the relationship between patient physiology, behavior, and environment. We have developed RADAR-IoT as an open-source IoT gateway framework, to harness this potential. It aims to connect multiple IoT devices at the edge, perform limited on-device data processing and analysis, and integrate with cloud-based mobile health platforms, such as RADAR-base, enabling real-time data processing. We also present a proof-of-concept data collection from this framework, using prototype hardware in two locations. The RADAR-IoT framework, combined with the RADAR-base mHealth platform, provides a comprehensive view of a user's health and environment by integrating static IoT sensors and wearable devices. Despite its current limitations, it offers a promising open-source solution for health research, with potential applications in managing infection control, monitoring chronic pulmonary disorders, and assisting patients with impaired motor control or cognitive ability.

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Remote patient-monitoring systems are helpful since they can provide timely and effective healthcare facilities. Such online telemedicine is usually achieved with the help of sophisticated and advanced wearable sensor technologies. The modern type of wearable connected devices enable the monitoring of vital sign parameters such as: heart rate variability (HRV) also known as electrocardiogram (ECG), blood pressure (BLP), Respiratory rate and body temperature, blood pressure (BLP), respiratory rate, and body temperature. The ubiquitous problem of wearable devices is their power demand for signal transmission; such devices require frequent battery charging, which causes serious limitations to the continuous monitoring of vital data. To overcome this, the current study provides a primary report on collecting kinetic energy from daily human activities for monitoring vital human signs. The harvested energy is used to sustain the battery autonomy of wearable devices, which allows for a longer monitoring time of vital data. This study proposes a novel type of stress- or exercise-monitoring ECG device based on a microcontroller (PIC18F4550) and a Wi-Fi device (ESP8266), which is cost-effective and enables real-time monitoring of heart rate in the cloud during normal daily activities. In order to achieve both portability and maximum power, the harvester has a small structure and low friction. Neodymium magnets were chosen for their high magnetic strength, versatility, and compact size. Due to the non-linear magnetic force interaction of the magnets, the non-linear part of the dynamic equation has an inverse quadratic form. Electromechanical damping is considered in this study, and the quadratic non-linearity is approximated using MacLaurin expansion, which enables us to find the law of motion for general case studies using classical methods for dynamic equations and the suitable parameters for the harvester. The oscillations are enabled by applying an initial force, and there is a loss of energy due to the electromechanical damping. A typical numerical application is computed with Matlab 2015 software, and an ODE45 solver is used to verify the accuracy of the method.

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BACKGROUND: Despite the increasing need for digital services to support geriatric mental health, the development and implementation of digital mental health care systems for older adults have been hindered by a lack of studies involving socially vulnerable older adult users and their caregivers in natural living environments. OBJECTIVE: This study aims to determine whether digital sensing data on heart rate variability, sleep quality, and physical activity can predict same-day or next-day depressive symptoms among socially vulnerable older adults in their everyday living environments. In addition, this study tested the feasibility of a digital mental health monitoring platform designed to inform older adult users and their community caregivers about day-to-day changes in the health status of older adults. METHODS: A single-arm, nonrandomized living lab pilot study was conducted with socially vulnerable older adults (n=25), their community caregivers (n=16), and a managerial social worker over a 6-week period during and after the COVID-19 pandemic. Depressive symptoms were assessed daily using the 9-item Patient Health Questionnaire via scripted verbal conversations with a mobile chatbot. Digital biomarkers for depression, including heart rate variability, sleep, and physical activity, were measured using a wearable sensor (Fitbit Sense) that was worn continuously, except during charging times. Daily individualized feedback, using traffic signal signs, on the health status of older adult users regarding stress, sleep, physical activity, and health emergency status was displayed on a mobile app for the users and on a web application for their community caregivers. Multilevel modeling was used to examine whether the digital biomarkers predicted same-day or next-day depressive symptoms. Study staff conducted pre- and postsurveys in person at the homes of older adult users to monitor changes in depressive symptoms, sleep quality, and system usability. RESULTS: Among the 31 older adult participants, 25 provided data for the living lab and 24 provided data for the pre-post test analysis. The multilevel modeling results showed that increases in daily sleep fragmentation (P=.003) and sleep efficiency (P=.001) compared with one's average were associated with an increased risk of daily depressive symptoms in older adults. The pre-post test results indicated improvements in depressive symptoms (P=.048) and sleep quality (P=.02), but not in the system usability (P=.18). CONCLUSIONS: The findings suggest that wearable sensors assessing sleep quality may be utilized to predict daily fluctuations in depressive symptoms among socially vulnerable older adults. The results also imply that receiving individualized health feedback and sharing it with community caregivers may help improve the mental health of older adults. However, additional in-person training may be necessary to enhance usability. TRIAL REGISTRATION: ClinicalTrials.gov NCT06270121; https://clinicaltrials.gov/study/NCT06270121.

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INTRODUCTION: Effective management of hypertension (HTN) is a priority in primary care. With telehealth now considered a staple care delivery method, uninsured and low-income patients without home blood pressure (BP) monitors may need additional attention and resources to achieve successful HTN control. METHODS: This prospective study at an underserved community clinic assessed the impact of distributing free BP monitors on patients' HTN control and therapy adherence. Enrollees were randomized into 2 groups, both completing 4 primary care physician (PCP) visits over a 6-month study period. Intervention participants collected home BP readings to report to their PCP and comparison participants completed an equivalent number of visits without having home BP data available for their PCP to review. Both groups completed an initial and final Therapy Adherence Scale (TAS) questionnaire. RESULTS: 263 patients were invited and 200 participants (mean age 50, 60% female, 19% Black, 67% Hispanic) completed the study. Intervention and comparison subjects featured comparable initial BP levels and TAS scores. After adjusting for age, race, ethnicity, sex, presence of diabetes and therapy adherence, intervention participants experienced higher odds of controlled HTN (OR 4.0; 95% Confidence Interval 2.1 to 7.7). A greater proportion of participants achieved BP control in the intervention arm compared with the comparison arm (82% vs 54% of participants, P < .001). TAS scores were higher in the intervention group (Mean = 44.1 vs 41.1; P < .001). DISCUSSION: The provision of free home BP monitors to low-income patients may feasibly and effectively improve BP control and therapy adherence.

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PURPOSE: Eye gaze tracking and pupillometry are evolving areas within the field of tele-robotic surgery, particularly in the context of estimating cognitive load (CL). However, this is a recent field, and current solutions for gaze and pupil tracking in robotic surgery require assessment. Considering the necessity of stable pupillometry signals for reliable cognitive load estimation, we compare the accuracy of three eye trackers, including head and console-mounted designs. METHODS: We conducted a user study with the da Vinci Research Kit (dVRK), to compare the three designs. We collected eye tracking and dVRK video data while participants observed nine markers distributed over the dVRK screen. We compute and analyze pupil detection stability and gaze prediction accuracy for the three designs. RESULTS: Head-worn devices present better stability and accuracy of gaze prediction and pupil detection compared to console-mounted systems. Tracking stability along the field of view varies between trackers, with gaze predictions detected at invalid zones of the image with high confidence. CONCLUSION: While head-worn solutions show benefits in confidence and stability, our results demonstrate the need to improve eye tacker performance regarding pupil detection, stability, and gaze accuracy in tele-robotic scenarios.

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BACKGROUND: Multi-parametric assessment, including heart sounds in addition to conventional parameters, may enhance the efficacy of noninvasive telemonitoring for heart failure (HF). We sought to assess the feasibility of self-telemonitoring with multiple devices including a handheld heart sound recorder and its association with clinical events in patients with HF. METHODS: Ambulatory HF patients recorded their own heart sounds, mono­lead electrocardiograms, oxygen saturation, body weight, and vital signs using multiple devices every morning for six months. RESULTS: In the 77 patients enrolled (63 ±â€¯13 years old, 84 % male), daily measurements were feasible with a self-measurement rate of >70 % of days in 75 % of patients. Younger age and higher Minnesota Living with Heart Failure Questionnaire scores were independently associated with lower adherence (p = 0.002 and 0.027, respectively). A usability questionnaire showed that 87 % of patients felt self-telemonitoring was helpful, and 96 % could use the devices without routine cohabitant support. Six patients experienced ten HF events of re-hospitalization and/or unplanned hospital visits due to HF. In patients who experienced HF events, a significant increase in heart rate and diastolic blood pressure and a decrease in the time interval from Q wave onset to the second heart sound were observed 7 days before the events compared with those without HF events. CONCLUSIONS: Self-telemonitoring with multiple devices including a handheld heart sound recorder was feasible even in elderly patients with HF. This intervention may confer a sense of relief to patients and enable monitoring of physiological parameters that could be valuable in detecting the deterioration of HF.

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