Compliance and technical feasibility of long-term health monitoring with wearable and ambient technologies

Evaluating compliance with HeatSuite for monitoring in situ physiological and perceptual responses and personal environmental exposure

Extreme heat events pose a significant health threat to vulnerable populations such as the elderly and those living with disease. Recent extreme heat events highlight that heat-related mortality often occurs indoors, urging a need to better understand how at-risk populations physiologically and behaviorally respond in their natural environment. However, a low-cost and scalable all-in-one solution to comprehensively monitor individuals during periods of extreme heat does not presently exist. We developed HeatSuite, a fully data-governed multimodal sensor platform, that can monitor the local environmental conditions, and physiological and behavioural responses, of free-living individuals. Compliance to the platform was assessed over 28 days among 21 older individuals living in low-income housing (70 ± 7 y, body mass index: 28.7 ± 6.3). Moderate (>77%) to near optimal (94%) compliance was observed among the physiological and perceptual metrics obtained. In conclusion, HeatSuite is an effective and comprehensive solution for at-home monitoring of at-risk populations.

A systematic review on the efficacy of artificial intelligence in geriatric healthcare: a critical analysis of current literature

OBJECTIVE

To carry out systematic analysis of existing literature on role of Artificial Intelligence in geriatric patient healthcare.

METHODS

A detailed online search was carried out using search phrases in reliable sources of information like Pubmed database, Embase database, Ovid database, Global Health database, PsycINFO, and Web of Science. Study specific information was gathered, including the organisation, year of publication, nation, setting, design of the research, information about population, size of study sample, group dynamics, eligibility and exclusion requirements, information about intervention, duration of exposure to the intervention , comparators, details of outcome measures, scheduling of evaluations, and consequences. After information gathering, the reviewers gathered to discuss any differences.

RESULTS

Thirty-one studies were finally selected for systemic review. Although there was some disagreement on the acceptance of AI-enhanced treatments in LTC settings, this review indicated that there was little consensus about the efficacy of those initiatives for older individuals. Social robots have been shown to increase social interaction and mood, but the data was more conflicting and less definitive for the other innovations and consequences. The majority of research evaluated a variety of results, which made it impossible to synthesise them in a meaningful way and prevented a meta-analysis. In addition, many studies have moderate to severe bias risks due to underpowered design CONCLUSION: It is challenging to determine whether AI supplemented technologies for geriatric patients are significantly beneficial. Although some encouraging findings were made, more study is required.

Unobtrusive measurement of gait parameters using seismographs: An observational study

Analyzing irregularities in walking patterns helps detect human locomotion abnormalities that can signal health changes. Traditional observation-based assessments have limitations due to subjective biases and capture only a single time point. Ambient and wearable sensor technologies allow continuous and objective locomotion monitoring but face challenges due to the need for specialized expertise and user compliance. This work proposes a seismograph-based algorithm for quantifying human gait, incorporating a step extraction algorithm derived from mathematical morphologies, with the goal of achieving the accuracy of clinical reference systems. To evaluate our method, we compared the gait parameters of 50 healthy participants, as recorded by seismographs, and those obtained from reference systems (a pressure-sensitive walkway and a camera system). Participants performed four walking tests, including traversing a walkway and completing the timed up-and-go (TUG) test. In our findings, we observed linear relationships with strong positive correlations (R2 > 0.9) and tight 95% confidence intervals for all gait parameters (step time, cycle time, ambulation time, and cadence). We demonstrated that clinical gait parameters and TUG mobility test timings can be accurately derived from seismographic signals, with our method exhibiting no significant differences from established clinical reference systems.

Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review

BACKGROUND

Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential.

OBJECTIVE

This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations.

METHODS

We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

RESULTS

A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation.

CONCLUSIONS

Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Computer-aided screening of aspiration risks in dysphagia with wearable technology: a Systematic Review and meta-analysis on test accuracy

Aspiration caused by dysphagia is a prevalent problem that causes serious health consequences and even death. Traditional diagnostic instruments could induce pain, discomfort, nausea, and radiation exposure. The emergence of wearable technology with computer-aided screening might facilitate continuous or frequent assessments to prompt early and effective management. The objectives of this review are to summarize these systems to identify aspiration risks in dysphagic individuals and inquire about their accuracy. Two authors independently searched electronic databases, including CINAHL, Embase, IEEE Xplore^® Digital Library, PubMed, Scopus, and Web of Science (PROSPERO reference number: CRD42023408960). The risk of bias and applicability were assessed using QUADAS-2. Nine (n = 9) articles applied accelerometers and/or acoustic devices to identify aspiration risks in patients with neurodegenerative problems (e.g., dementia, Alzheimer's disease), neurogenic problems (e.g., stroke, brain injury), in addition to some children with congenital abnormalities, using videofluoroscopic swallowing study (VFSS) or fiberoptic endoscopic evaluation of swallowing (FEES) as the reference standard. All studies employed a traditional machine learning approach with a feature extraction process. Support vector machine (SVM) was the most famous machine learning model used. A meta-analysis was conducted to evaluate the classification accuracy and identify risky swallows. Nevertheless, we decided not to conclude the meta-analysis findings (pooled diagnostic odds ratio: 21.5, 95% CI, 2.7-173.6) because studies had unique methodological characteristics and major differences in the set of parameters/thresholds, in addition to the substantial heterogeneity and variations, with sensitivity levels ranging from 21.7% to 90.0% between studies. Small sample sizes could be a critical problem in existing studies (median = 34.5, range 18-449), especially for machine learning models. Only two out of the nine studies had an optimized model with sensitivity over 90%. There is a need to enlarge the sample size for better generalizability and optimize signal processing, segmentation, feature extraction, classifiers, and their combinations to improve the assessment performance. Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/), identifier (CRD42023408960).

Wearable device and smartphone data quantify ALS progression and may provide novel outcome measures

Amyotrophic lateral sclerosis (ALS) therapeutic development has largely relied on staff-administered functional rating scales to determine treatment efficacy. We sought to determine if mobile applications (apps) and wearable devices can be used to quantify ALS disease progression through active (surveys) and passive (sensors) data collection. Forty ambulatory adults with ALS were followed for 6-months. The Beiwe app was used to administer the self-entry ALS functional rating scale-revised (ALSFRS-RSE) and the Rasch Overall ALS Disability Scale (ROADS) surveys every 2-4 weeks. Each participant used a wrist-worn activity monitor (ActiGraph Insight Watch) or an ankle-worn activity monitor (Modus StepWatch) continuously. Wearable device wear and app survey compliance were adequate. ALSFRS-R highly correlated with ALSFRS-RSE. Several wearable data daily physical activity measures demonstrated statistically significant change over time and associations with ALSFRS-RSE and ROADS. Active and passive digital data collection hold promise for novel ALS trial outcome measure development.

Feasibility of High-Frequency Monitoring of the Home Environment and Health in Older Adults: Proof of Concept

Technology provides new opportunities to understand and optimize the relationship between the home indoor environmental quality and health outcomes in older adults. We aimed to establish proof-of-concept and feasibility of remote, real-time, high-frequency, and simultaneous monitoring of select environmental variables and outcomes related to health and wellbeing in older adults. Thirty-four participants (27 were female) with an average age (SD) of 81 years (±7.1) were recruited from community and supportive housing environments. Environmental sensors were installed in each home and participants were asked to use a wearable device on their finger and answer smartphone-based questionnaires on a daily basis. Further, a subgroup of participants were asked to complete tablet-based cognitive tests on a daily basis. Average compliance with the wearable (time worn properly / total time with device) was 81%. Participants responded to 69% of daily smartphone surveys and completed 80% of the prescribed cognitive tests. These results suggest that it is feasible to study the impact of the home thermal environment and air quality on biological rhythms, cognition, and other outcomes in older adults. However, the success of non-passive data collection elements may be contingent upon baseline cognition.

A Review of Stimuli-Responsive Smart Materials for Wearable Technology in Healthcare: Retrospective, Perspective, and Prospective

In recent years thanks to the Internet of Things (IoT), the demand for the development of miniaturized and wearable sensors has skyrocketed. Among them, novel sensors for wearable medical devices are mostly needed. The aim of this review is to summarize the advancements in this field from current points of view, focusing on sensors embedded into textile fabrics. Indeed, they are portable, lightweight, and the best candidates for monitoring biometric parameters. The possibility of integrating chemical sensors into textiles has opened new markets in smart clothing. Many examples of these systems are represented by color-changing materials due to their capability of altering optical properties, including absorption, reflectance, and scattering, in response to different external stimuli (temperature, humidity, pH, or chemicals). With the goal of smart health monitoring, nanosized sol-gel precursors, bringing coupling agents into their chemical structure, were used to modify halochromic dyestuffs, both minimizing leaching from the treated surfaces and increasing photostability for the development of stimuli-responsive sensors. The literature about the sensing properties of functionalized halochromic azo dyestuffs applied to textile fabrics is reviewed to understand their potential for achieving remote monitoring of health parameters. Finally, challenges and future perspectives are discussed to envisage the developed strategies for the next generation of functionalized halochromic dyestuffs with biocompatible and real-time stimuli-responsive capabilities.

Artificial intelligence for older people receiving long-term care: a systematic review of acceptability and effectiveness studies

Artificial intelligence (AI)-enhanced interventions show promise for improving the delivery of long-term care (LTC) services for older people. However, the research field is developmental and has yet to be systematically synthesised. This systematic review aimed to synthesise the literature on the acceptability and effectiveness of AI-enhanced interventions for older people receiving LTC services. We conducted a systematic search that identified 2720 records from Embase, Ovid, Global Health, PsycINFO, and Web of Science. 31 articles were included in the review that evaluated AI-enhanced social robots (n=22), environmental sensors (n=6), and wearable sensors (n=5) with older people receiving LTC services across 15 controlled and 14 non-controlled trials in high-income countries. Risk of bias was evaluated using the RoB 2, RoB 2 CRT, and ROBINS-I tools. Overall, AI-enhanced interventions were found to be somewhat acceptable to users with mixed evidence for their effectiveness across different health outcomes. The included studies were found to have high risk of bias which reduced confidence in the results. AI-enhanced interventions are promising innovations that could reshape the landscape of LTC globally. However, more trials are required to support their widespread implementation. Pathways are needed to support more high-quality trials, including in low-income and middle-income countries.

Analysing gait patterns in degenerative lumbar spine diseases: a literature review

OBJECTIVES

To collate the current state of knowledge and explore differences in the spatiotemporal gait patterns of degenerative lumbar spine diseases: lumbar spinal stenosis (LSS), lumbar disc herniation (LDH) and low back pain (LBP).

BACKGROUND

LBP is common presenting complaint with degenerative lumbar spine disease being a common cause. In particular, the gait patterns of LSS, LDH and mechanical-type (facetogenic and discogenic) LBP is not established.

METHODS

A search of the literature was conducted to determine the changes in spatial and temporal gait metrics involved with each type of degenerative lumbar spine disease. A search of databases including Medline, Embase and PubMed from their date of inception to April 18th, 2021 was performed to screen, review and identify relevant studies for qualitative synthesis. Seventeen relevant studies were identified for inclusion in the present review. Of these, 5 studies investigated gait patterns in LSS, 10 studies investigated LBP and 2 studies investigated LDH. Of these, 4 studies employed wearable accelerometry in LSS (2 studies) and LBP (2 studies).

CONCLUSIONS

Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. LSS is characterised by asymmetry and variability. Spatiotemporal gait deterioration in gait velocity, cadence with increased double-support duration and gait variability are distinguishing features in LDH. LBP involves marginal abnormalities in temporal and spatial gait metrics. Previous studies suggest degenerative diseases of the lumbar spine have unique patterns of gait deterioration. Gait asymmetry and variability, may be relevant metrics for distinguishing between the gait profiles of lumbar spine diseases.

Predicting Participant Compliance With Fitness Tracker Wearing and Ecological Momentary Assessment Protocols in Information Workers: Observational Study

Background

Studies that use ecological momentary assessments (EMAs) or wearable sensors to track numerous attributes, such as physical activity, sleep, and heart rate, can benefit from reductions in missing data. Maximizing compliance is one method of reducing missing data to increase the return on the heavy investment of time and money into large-scale studies.

Objective

This paper aims to identify the extent to which compliance can be prospectively predicted from individual attributes and initial compliance.

Methods

We instrumented 757 information workers with fitness trackers for 1 year and conducted EMAs in the first 56 days of study participation as part of an observational study. Their compliance with the EMA and fitness tracker wearing protocols was analyzed. Overall, 31 individual characteristics (eg, demographics and personalities) and behavioral variables (eg, early compliance and study portal use) were considered, and 14 variables were selected to create beta regression models for predicting compliance with EMAs 56 days out and wearable compliance 1 year out. We surveyed study participation and correlated the results with compliance.

Results

Our modeling indicates that 16% and 25% of the variance in EMA compliance and wearable compliance, respectively, could be explained through a survey of demographics and personality in a held-out sample. The likelihood of higher EMA and wearable compliance was associated with being older (EMA: odds ratio [OR] 1.02, 95% CI 1.00-1.03; wearable: OR 1.02, 95% CI 1.01-1.04), speaking English as a first language (EMA: OR 1.38, 95% CI 1.05-1.80; wearable: OR 1.39, 95% CI 1.05-1.85), having had a wearable before joining the study (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.50, 95% CI 1.23-1.83), and exhibiting conscientiousness (EMA: OR 1.25, 95% CI 1.04-1.51; wearable: OR 1.34, 95% CI 1.14-1.58). Compliance was negatively associated with exhibiting extraversion (EMA: OR 0.74, 95% CI 0.64-0.85; wearable: OR 0.67, 95% CI 0.57-0.78) and having a supervisory role (EMA: OR 0.65, 95% CI 0.54-0.79; wearable: OR 0.66, 95% CI 0.54-0.81). Furthermore, higher wearable compliance was negatively associated with agreeableness (OR 0.68, 95% CI 0.56-0.83) and neuroticism (OR 0.85, 95% CI 0.73-0.98). Compliance in the second week of the study could help explain more variance; 62% and 66% of the variance in EMA compliance and wearable compliance, respectively, was explained. Finally, compliance correlated with participants’ self-reflection on the ease of participation, usefulness of our compliance portal, timely resolution of issues, and compensation adequacy, suggesting that these are avenues for improving compliance.

Conclusions

We recommend conducting an initial 2-week pilot to measure trait-like compliance and identify participants at risk of long-term noncompliance, performing oversampling based on participants’ individual characteristics to avoid introducing bias in the sample when excluding data based on noncompliance, using an issue tracking portal, and providing special care in troubleshooting to help participants maintain compliance.

Enabling Older Adults' Health Self-Management through Self-Report and Visualization-A Systematic Literature Review

Aging is associated with a progressive decline in health, resulting in increased medical care and costs. Mobile technology may facilitate health self-management, thus increasing the quality of care and reducing costs. Although the development of technology offers opportunities in monitoring the health of older adults, it is not clear whether these technologies allow older adults to manage their health data themselves. This paper presents a review of the literature on mobile health technologies for older adults, focusing on whether these technologies enable the visualization of monitored data and the self-reporting of additional information by the older adults. The systematic search considered studies published between 2009 and 2019 in five online databases. We screened 609 articles and identified 95 that met our inclusion and exclusion criteria. Smartphones and tablets are the most frequently reported technology for older adults to enter additional data to the one that is monitored automatically. The recorded information is displayed on the monitoring device and screens of external devices such as computers. Future designs of mobile health technology should allow older users to enter additional information and visualize data; this could enable them to understand their own data as well as improve their experience with technology.

Innovative Assisted Living Tools, Remote Monitoring Technologies, Artificial Intelligence-Driven Solutions, and Robotic Systems for Aging Societies: Systematic Review

BACKGROUND

The increase in life expectancy and recent advancements in technology and medical science have changed the way we deliver health services to the aging societies. Evidence suggests that home telemonitoring can significantly decrease the number of readmissions, and continuous monitoring of older adults' daily activities and health-related issues might prevent medical emergencies.

OBJECTIVE

The primary objective of this review was to identify advances in assistive technology devices for seniors and aging-in-place technology and to determine the level of evidence for research on remote patient monitoring, smart homes, telecare, and artificially intelligent monitoring systems.

METHODS

A literature review was conducted using Cumulative Index to Nursing and Allied Health Literature Plus, MEDLINE, EMBASE, Institute of Electrical and Electronics Engineers Xplore, ProQuest Central, Scopus, and Science Direct. Publications related to older people's care, independent living, and novel assistive technologies were included in the study.

RESULTS

A total of 91 publications met the inclusion criteria. In total, four themes emerged from the data: technology acceptance and readiness, novel patient monitoring and smart home technologies, intelligent algorithm and software engineering, and robotics technologies. The results revealed that most studies had poor reference standards without an explicit critical appraisal.

CONCLUSIONS

The use of ubiquitous in-home monitoring and smart technologies for aged people's care will increase their independence and the health care services available to them as well as improve frail elderly people's health care outcomes. This review identified four different themes that require different conceptual approaches to solution development. Although the engineering teams were focused on prototype and algorithm development, the medical science teams were concentrated on outcome research. We also identified the need to develop custom technology solutions for different aging societies. The convergence of medicine and informatics could lead to the development of new interdisciplinary research models and new assistive products for the care of older adults.

Exploring barriers to physical activity of patients at the internal medicine and surgical wards: a retrospective analysis of continuously collected data

PURPOSE

To analyse physical activity of patients during their hospital stay and to explore the relationship between physical activity and barriers to physical activity.

METHODS

This was a secondary analysis of physical activity data for patients admitted to the internal medicine and surgical wards. Physical activity data, collected with a wireless patch sensor, was operationalized as time spent lying, sitting/standing, and walking. Barriers to physical activity included patients' pain levels, the use of urinary catheters, intravenous tubing, oxygen lines, drains, and level of dependence. Regression analysis explored the relationship between physical activity and barriers to physical activity.

RESULTS

Physical activity data were collected in 39 patients (aged 27-88, mean 54 years) during hospital stay. Patients were admitted for a median of 10 d (interquartile range [IQR]: 7-15 d). These patients were lying for a median of 12.1 h (7.6-17.7), sitting/standing 11.8 h (6.3-15.7), and walking 0.1 h (0-0.3) per day. Time lying during the day related to pain levels (β = 0.4 h per unit increase in pain, p < 0.01) and drain use (β = 3.1 h, p < 0.01).

CONCLUSIONS

Patients spent the most time during the hospital stay lying in bed. Improved pain management and decreased drain use may be worth exploring to increase inpatient physical activity.Implications for rehabilitationContinuous monitoring of physical activity in patients during hospital stay is an important tool for health care professionals to improve multidisciplinary care and rehabilitation.Health care professionals should be aware of the necessity of adequate pain management and critically review the use of drains in order to improve physical activity of patients during hospital stay.Patients need extra support of health care professionals to increase physical activity during consecutive days of their hospital stay.

Energy Management for Smart Homes—State of the Art

Smart home is a concept that aims to enhance the comfort of residents and facilitate household activities. The smart home is an application of ubiquitous computing which can provide the user with context-aware automated or assistive services in the form of ambient intelligence, remote control of home appliances, or automation. Smart homes attempt to integrate smartness into homes to guarantee the residents’ convenience, safety, and security, while conserving the energy. The capabilities of a smart home in the context of different applications, have been scrutinized for this investigation. Different proposed architectures, protocols, and infrastructures have been taken into consideration. As the data management process is a vital part of a smart home system, many procedures of data collection, storage, and analysis have been surveyed. Methods of data acquisition has also been discussed. Existing challenges, pros, and cons of proposed schemes along with future perspectives of smart homes are identified in this report, which is intended to promote future research directions.

Multimodal Human and Environmental Sensing for Longitudinal Behavioral Studies in Naturalistic Settings: Framework for Sensor Selection, Deployment, and Management

Background

Recent advances in mobile technologies for sensing human biosignals are empowering researchers to collect real-world data outside of the laboratory, in natural settings where participants can perform their daily activities with minimal disruption. These new sensing opportunities usher a host of challenges and constraints for both researchers and participants.

Objective

This viewpoint paper aims to provide a comprehensive guide to aid research teams in the selection and management of sensors before beginning and while conducting human behavior studies in the wild. The guide aims to help researchers achieve satisfactory participant compliance and minimize the number of unexpected procedural outcomes.

Methods

This paper presents a collection of challenges, consideration criteria, and potential solutions for enabling researchers to select and manage appropriate sensors for their research studies. It explains a general data collection framework suitable for use with modern consumer sensors, enabling researchers to address many of the described challenges. In addition, it provides a description of the criteria affecting sensor selection, management, and integration that researchers should consider before beginning human behavior studies involving sensors. On the basis of a survey conducted in mid-2018, this paper further illustrates an organized snapshot of consumer-grade human sensing technologies that can be used for human behavior research in natural settings.

Results

The research team applied the collection of methods and criteria to a case study aimed at predicting the well-being of nurses and other staff in a hospital. Average daily compliance for sensor usage measured by the presence of data exceeding half the total possible hours each day was about 65%, yielding over 355,000 hours of usable sensor data across 212 participants. A total of 6 notable unexpected events occurred during the data collection period, all of which had minimal impact on the research project.

Conclusions

The satisfactory compliance rates and minimal impact of unexpected events during the case study suggest that the challenges, criteria, methods, and mitigation strategies presented as a guide for researchers are helpful for sensor selection and management in longitudinal human behavior studies in the wild.

The fabric of digital life

Purpose

This paper aims to examine how metadata taxonomies in embodied computing databases indicate context (e.g. a marketing context or an ethical context) and describe ways to track the evolution of the embodied computing industry over time through digital media archiving.

Design/methodology/approach

The authors compare the metadata taxonomies of two embodied computing databases by providing a narrative of their top-level categories. After identifying these categories, they describe how they structure the databases around specific themes.

Findings

The growing wearables market often hides complex sociotechnical tradeoffs. Marketing products like Vandrico Inc.’s Wearables Database frame wearables as business solutions without conveying information about the various concessions users make (about giving up their data, for example). Potential solutions to this problem include enhancing embodied computing literacy through the construction of databases that track media about embodied computing technologies using customized metadata categories. Databases such as FABRIC contain multimedia related to the emerging embodied computing market – including patents, interviews, promotional videos and news articles – and can be archived through user-curated collections and tagged according to specific themes (privacy, policing, labor, etc.). One of the benefits of this approach is that users can use the rich metadata fields to search for terms and create curated collections that focus on tradeoffs related to embodied computing technologies.

Originality/value

This paper describes the importance of metadata for framing the orientation of embodied computing databases and describes one of the first attempts to comprehensively track the evolution of embodied computing technologies, their developers and their diverse applications in various social contexts through media archiving.

A smartphone-based solution to monitor daily physical activity in a care home

INTRODUCTION

In an ageing population, increasing chronic disease prevalence puts a high economic burden on society. Physical activity plays an important role in disease prevention and should therefore be promoted in the elderly.

METHODS

In this study, a mobile health (mHealth) system was implemented in a care home setting to monitor and promote elderly peoples' daily activity. The physical activity of 20 elderly people (8 female and 12 male, aged 81 ± 9 years old) was monitored over 10 weeks using the mHealth system, consisting of a smartphone and heart rate belt. Feedback on physical activity was provided weekly. A reference performance test battery derived from the Senior Fitness Test determined the participants' physical fitness.

RESULTS

Activity levels increased from week 1 onwards, peaking at week 5, and decreasing slightly until week 10. This illustrates that the use of mHealth and feedback on physical activity can motivate the elderly to become more active, but that the effect is transient without other incentives. Bio-data from the mHealth system were translated into a fitness score explaining 65% of the test battery's variance. After separating the elderly into three groups depending on physical fitness determined from the test battery, classification based on the fitness score resulted in a correct classification rate of 67.3%.

DISCUSSION

This study demonstrates that an mHealth system can be implemented in a care home setting to motivate activity of the elderly, and that the bio-data can be translated in a fitness score predicting the outcome of labour-intensive tests.

Patient Adherence to Scheduled Vital Sign Measurements During Home Telemonitoring: Analysis of the Intervention Arm in a Before and After Trial

BACKGROUND

In a home telemonitoring trial, patient adherence with scheduled vital signs measurements is an important aspect that has not been thoroughly studied and for which data in the literature are limited. Levels of adherence have been reported as varying from approximately 40% to 90%, and in most cases, the adherence rate usually dropped off steadily over time. This drop is more evident in the first few weeks or months after the start. Higher adherence rates have been reported for simple types of monitoring and for shorter periods of intervention. If patients do not follow the intended procedure, poorer results than expected may be achieved. Hence, analyzing factors that can influence patient adherence is of great importance.

OBJECTIVE

The goal of the research was to present findings on patient adherence with scheduled vital signs measurements in the recently completed Commonwealth Scientific and Industrial Research Organisation (CSIRO) national trial of home telemonitoring of patients (mean age 70.5 years, SD 9.3 years) with chronic conditions (chronic obstructive pulmonary disease, coronary artery disease, hypertensive diseases, congestive heart failure, diabetes, or asthma) carried out at 5 locations along the east coast of Australia. We investigated the ability of chronically ill patients to carry out a daily schedule of vital signs measurements as part of a chronic disease management care plan over periods exceeding 6 months (302 days, SD 135 days) and explored different levels of adherence for different measurements as a function of age, gender, and supervisory models.

METHODS

In this study, 113 patients forming the test arm of a Before and After Control Intervention (BACI) home telemonitoring trial were analyzed. Patients were required to monitor on a daily basis a range of vital signs determined by their chronic condition and comorbidities. Vital signs included noninvasive blood pressure, pulse oximetry, spirometry, electrocardiogram (ECG), blood glucose level, body temperature, and body weight. Adherence was calculated as the number of days during which at least 1 measurement was taken over all days where measurements were scheduled. Different levels of adherence for different measurements, as a function of age, gender, and supervisory models, were analyzed using linear regression and analysis of covariance for a period of 1 year after the intervention.

RESULTS

Patients were monitored on average for 302 (SD 135) days, although some continued beyond 12 months. The overall adherence rate for all measurements was 64.1% (range 59.4% to 68.8%). The adherence rates of patients monitored in hospital settings relative to those monitored in community settings were significantly higher for spirometry (69.3%, range 60.4% to 78.2%, versus 41.0%, range 33.1% to 49.0%, P<.001), body weight (64.5%, range 55.7% to 73.2%, versus 40.5%, range 32.3% to 48.7%, P<.001), and body temperature (66.8%, range 59.7% to 73.9%, versus 55.2%, range 48.4% to 61.9%, P=.03). Adherence with blood glucose measurements (58.1%, range 46.7% to 69.5%, versus 50.2%, range 42.8% to 57.6%, P=.24) was not significantly different overall. Adherence rates for blood pressure (68.5%, range 62.7% to 74.2%, versus 59.7%, range 52.1% to 67.3%, P=.04), ECG (65.6%, range 59.7% to 71.5%, versus 56.5%, range 48.7% to 64.4%, P=.047), and pulse oximetry (67.0%, range 61.4% to 72.7%, versus 56.4%, range 48.6% to 64.1%, P=.02) were significantly higher in males relative to female subjects. No statistical differences were observed between rates of adherence for the younger patient group (70 years and younger) and older patient group (older than 70 years).

CONCLUSIONS

Patients with chronic conditions enrolled in the home telemonitoring trial were able to record their vital signs at home at least once every 2 days over prolonged periods of time. Male patients maintained a higher adherence than female patients over time, and patients supervised by hospital-based care coordinators reported higher levels of adherence with their measurement schedule relative to patients supervised in community settings. This was most noticeable for spirometry.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12613000635763; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364030&isReview=true (Archived by WebCite at http://www.webcitation.org/6xPOU3DpR).

Reduced Healthcare Use and Apparent Savings with Passive Home Monitoring Technology: A Pilot Study

OBJECTIVES

To conduct a cost analysis of ambient assisted living technology, which is promising for improving the ability of individuals and care providers to monitor daily activities and gain better awareness through proactive management of health and safety.

DESIGN

Three-arm cohort study.

SETTING

Homes of enrollees of a state-based healthcare plan for older adults.

PARTICIPANTS

Enrollees dually eligible for Medicare and Medicaid (N = 268).

INTERVENTION

Health and safety passive remote patient monitoring (PRPM) systems were installed in enrollees' homes (the intervention group) with monitoring and proactive intervention of a case manager when deviation from baseline subject behavior was detected.

MEASUREMENTS

Claims data were collected over 12 months to assess healthcare use and costs in the intervention group and to compare use and costs with those of two control groups: a concurrent group of enrollees who declined the technology and a historical cohort matched on age to the participation group.

RESULTS

Although the small sample size precluded cost differences that were statistically significant, the participant group used substantially less custodial care, emergency department (ED) services, inpatient stays, and ED costs than the two control groups.

CONCLUSION

In this pilot study, the PRPM system was associated with apparent healthcare cost savings. Although more cost analyses are warranted, ambient assisted living technologies are a potentially valuable investment for older adult care.

Patient Compliance in Home-Based Self-Care Telehealth Projects

This paper presents the findings of a literature review on patient compliance in home-based self-care telehealth monitoring situations, intended to establish a knowledge base for this aspect which is often neglected alongside more conventional clinical, economic and service evaluations. A systematic search strategy led to 72 peer-reviewed published scientific papers being selected as most relevant to the topic, 58 of which appeared in the last 10 years. Patient conditions in which most evidence for compliance was found were blood pressure, heart failure and stroke, diabetes, asthma, chronic obstructive pulmonary disease and other respiratory diseases. In general, good compliance at the start of a study was found to drop off over time, most rapidly in the period immediately after the start. Success factors identified in the study included the extent of patient health education, telehealth system implementation style, user training and competence in system usage, active human support from the healthcare provider and maintaining strong participant motivation.

Usability in telemedicine systems-A literature survey

INTRODUCTION

The rapid development of sensors and communication technologies enable the growth of new innovative services in healthcare, such as Telemedicine. An essential ingredient in the development of a telemedicine system and its final acceptance by end users are usability studies. The principles of usability engineering, evaluations and telemedicine are well established, and it may contribute to the adoption and eventually deployment of such systems and services. An in-depth usability analysis, including performance and attitude measures, requires knowledge about available usability techniques, and is depending on the amount of resources. Therefore it is worth investigating how usability methods are applied in developing telemedicine systems. Our hypothesis is: with increasing research and development of telemedicine systems, we expect that various usability methods are more equally employed for different end-user groups and applications.

METHOD

A literature survey was conducted to find telemedicine systems that have been evaluated for usability or ease of use. The elements of the PICO framework were used as a basis for the selection criteria in the literature search. The search was not limited by year. Two independent reviewers screened all search results first by title, and then by abstract for inclusion. Articles were included up to May 2015.

RESULTS

In total, 127 publications were included in this survey. The number of publications on telemedicine systems significantly increased after 2008. Older adults and end-users with cardiovascular conditions were among largest target end-user groups. Remote monitoring systems were found the most, in 90 publications. Questionnaires are the most common means for evaluating telemedicine systems, and were found in 88 publications. Questionnaires are used frequently in studies focusing on cardiovascular diseases, Parkinson's disease and older adult conditions. Interviews are found the most in publications related to stroke. In total 71% of the publications were trial-orientated and the remaining process orientated. An increase in telemedicine research, development and applications is found worldwide, with the majority of publications conducted in America.

DISCUSSION AND CONCLUSION

Monitoring patients in their homes can lead to better healthcare at lower costs which implies an increased demand of new healthcare strategies like telemedicine. We expected that with the increase in telemedicine research and development, a greater range of usability methods would also be employed in the included publications. This is not the case. Researchers employed questionnaires as a preferred usability method for each type of telemedicine system and most end-users. However, in process-orientated studies a greater range of usability evaluations were applied, with fewer differences found in the amount of publications for each evaluation method. Questionnaires enable researchers to evaluate a system quickly on end users, as it requires less expertise on the evaluation method compared to the other methods. They are easily distributed and are customizable. The use of questionnaires is therefore an evaluation method of choice for a variety of telemedicine systems and end-users.

Smart homes and home health monitoring technologies for older adults: A systematic review

BACKGROUND

Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes.

OBJECTIVES

The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs.

RESULTS

We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score ≥6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease.

CONCLUSIONS

The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs.

Using data from ambient assisted living and smart homes in electronic health records

INTRODUCTION

This editorial is part of the Focus Theme of Methods of Information in Medicine on "Using Data from Ambient Assisted Living and Smart Homes in Electronic Health Records".

BACKGROUND

To increase efficiency in the health care of the future, data from innovative technology like it is used for ambient assisted living (AAL) or smart homes should be available for individual health decisions. Integrating and aggregating data from different medical devices and health records enables a comprehensive view on health data.

OBJECTIVES

The objective of this paper is to present examples of the state of the art in research on information management that leads to a sustainable use and long-term storage of health data provided by innovative assistive technologies in daily living.

RESULTS

Current research deals with the perceived usefulness of sensor data, the participatory design of visual displays for presenting monitoring data, and communication architectures for integrating sensor data from home health care environments with health care providers either via a regional health record bank or via a telemedical center.

CONCLUSIONS

Integrating data from AAL systems and smart homes with data from electronic patient or health records is still in an early stage. Several projects are in an advanced conceptual phase, some of them exploring feasibility with the help of prototypes. General comprehensive solutions are hardly available and should become a major issue of medical informatics research in the near future.

Cloud computing for context-aware enhanced m-Health services

m-Health services are increasing its presence in our lives due to the high penetration of new smartphone devices. This new scenario proposes new challenges in terms of information accessibility that require new paradigms which enable the new applications to access the data in a continuous and ubiquitous way, ensuring the privacy required depending on the kind of data accessed. This paper proposes an architecture based on cloud computing paradigms in order to empower new m-Health applications to enrich their results by providing secure access to user data.

Quality of the wireless electrocardiogram signal during physical exercise in different age groups

Electrocardiographic (ECG) recordings are usually obtained at rest. In many cases, real-time ECG monitoring in the home environment during daily life would be useful, but that requires a wireless device. The purpose of this paper is to evaluate the quality of the wireless ECG signals during physical activities. The test data were collected both in a normal exercise environment and in a radio frequency (RF)-shielded and noiseless environment. 30 test persons performed running, biking, or Nordic walking exercises in normal indoor conditions, while electrical activity of the heart and acceleration of the body were measured by a VitalSens VS100 device (InteleSens). The acceleration data were also acquired with a DogIMU movement sensor (Domuset). Six more persons were measured in an RF-shielded environment, while they followed a specific list of exercises to verify the tests of the first group. The list consisted of exercise movements, thought to introduce disturbance in the ECG signals. The collected data were classified into three quality classes, good (3%), moderate (66%), and poor (31%), based on the recognition of the QRS-complex and R-R intervals as well as the amount of disturbance. The accelerometer data were compared to the amount of noise in the ECG data. A clear correlation was found between increased noise and level of activity. Increasing age also appeared to decrease the ECG signal quality. Careful consideration of the quality of the data versus positive and negative features of wirelessness shows great potential for the wireless ECG in future home healthcare and fitness industries.

Monitoring activities of daily living of the elderly and the potential for its use in telecare and telehealth: a review

OBJECTIVE

This review was designed to determine whether telemonitoring activities of daily living (ADL) of elderly people can improve quality of life and be beneficial to their healthcare.

MATERIALS AND METHODS

Electronic databases were searched for studies that monitored ADL of elderly people and preferably measured some clinical outcomes such as ability to predict key events that require intervention and for studies that assessed perception of elderly people of such telemonitoring systems. The articles were reviewed and assessed independently by two reviewers.

RESULTS

One hundred seventy-five unique studies were found. Sixty-seven of these were identified for potential inclusion, and 25 studies were finally included. Study characteristics, parameters monitored, outcomes, and problems encountered were summarized and discussed. The main focus was on the potential benefits of ADL monitoring on the care of elderly people.

CONCLUSIONS

Although most studies reported on technical improvements in methods for detecting changes in ADL, few, if any, determined the benefits to the patient of telemonitoring for changes in ADL or correlation with any physiological changes. We propose sensor and system characteristics for improved user acceptance and deployment in a large-scale care plan. We present areas requiring further investigation.

A multi-sensor monitoring system of human physiology and daily activities

OBJECTIVE

To present the design and pilot test results of a continuous multi-sensor monitoring system of real-world physiological conditions and daily life (activities, travel, exercise, and food consumption), culminating in a Web-based graphical decision-support interface.

MATERIALS AND METHODS

The system includes a set of wearable sensors wirelessly connected to a "smartphone" with a continuously running software application that compresses and transmits the data to a central server. Sensors include a Global Positioning System (GPS) receiver, electrocardiogram (ECG), three-axis accelerometer, and continuous blood glucose monitor. A food/medicine diary and prompted recall activity diary were also used. The pilot test involved 40 type 2 diabetic patients monitored over a 72-h period.

RESULTS

All but three subjects were successfully monitored for the full study period. Smartphones proved to be an effective hub for managing multiple streams of data but required attention to data compression and battery consumption issues. ECG, accelerometer, and blood glucose devices performed adequately as long as subjects wore them. GPS tracking for a full day was feasible, although significant efforts are needed to impute missing data. Activity detection algorithms were successful in identifying activities and trip modes but could benefit by incorporating accelerometer data. The prompted recall diary was an effective tool for augmenting algorithm results, although subjects reported some difficulties with it. The food and medicine diary was completed fully, although end times and medicine dosages were occasionally missing.

CONCLUSIONS

The unique combination of sensors holds promise for increasing accuracy and reducing burden associated with collecting individual-level activity and physiological data under real-world conditions, but significant data processing issues remain. Such data will provide new opportunities to explore the impacts of human geography and daily lifestyle on health at a fine spatial/temporal scale.

Comparison of four different mobile devices for measuring heart rate and ECG with respect to aspects of usability and acceptance by older people

In the area of product design and usability, most products are developed for the mass-market by technically oriented designers and developers for use by persons who themselves are also technically adept by today's standards. The demands of older people are commonly not given sufficient consideration within the early developmental process. In the present study, the usability and acceptability of four different devices meant to be worn for the measurement of heart rate or ECG were analyzed on the basis of qualitative subjective user ratings and structured interviews of twelve older participants. The data suggest that there was a relatively high acceptance concerning these belts by older adults but none of the four harnesses was completely usable. Especially problematic to the point of limiting satisfaction among older subjects were problems encountered while adjusting the length of the belt and/or closing the locking mechanism. The two devices intended for dedicated heart rate recording yielded the highest user ratings for design, and were clearly preferred for extended wearing time. Yet for all the devices participants identified several important deficiencies in their design, as well as suggestions for improvement. We conclude that the creation of an acceptable monitoring device for older persons requires designers and developers to consider the special demands and abilities of the target group.

A review of wearable sensors and systems with application in rehabilitation

The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

[Facing the challenges of ubiquitous computing in the health care sector]

The steady progress of microelectronics, communications and information technology will enable the realisation of the vision for "ubiquitous computing" where the Internet extends into the real world embracing everyday objects. The necessary technical basis is already in place. Due to their diminishing size, constantly falling price and declining energy consumption, processors, communications modules and sensors are being increasingly integrated into everyday objects today. This development is opening up huge opportunities for both the economy and individuals. In the present paper we discuss possible applications, but also technical, social and economic barriers to a wide-spread use of ubiquitous computing in the health care sector.

Guest editorial. Special section on personal health systems

This special section on personal health systems (PHSs) features 13 papers in three main areas: new-micro-nano instrumentation, sensors, and sensor-based systems; new information processing technology via embedding intelligence in PHS; and PHS platforms to address specific clinical applications.