Technology-assisted quantification of movement to predict infants at high risk of motor disability: A systematic review

AIM

To systematically review the scientific literature to determine the predictive validity of technology-assisted measures of observable infant movement in infants less than six months of corrected age (CA) to identify high-risk of motor disability.

METHOD

A comprehensive search for randomised and non-randomised controlled trials, cohort studies and cross-comparison trials was performed on five electronic databases up to Feb 2021. Studies were included if they quantified infant movement before 6 months CA using some method of technology-assistance and compared the instrumented measure to a diagnostic clinical measure of neurodevelopment. Studies were excluded if they did not report a technology-assisted measure of infant movement. Methodological quality of the included studies was assessed using the Downs and Black scale.

RESULTS

23 studies met the full inclusion and exclusion criteria. Methodological quality of the included papers ranged from 9 to 24 (out of 26) on the Downs and Black scale. Infant movement assessments included the General Movements Assessment (GMA) and domains of the Hammersmith Infant Neurological Assessment (HINE). Studies used 2D video recordings, RGB-Depth recordings, accelerometry, and electromagnetic motion tracking technologies to quantify movement. Analytical approaches and movement features of interest were individual and varied. Technology assisted quantitative assessments identified cases of later diagnosed CP with sensitivity 44-100 %, specificity 59-95 %, Area under the ROC Curve 82-93 %; and typical development with sensitivity range 30-46 %, specificity 88-95 %, Area under the ROC Curve 68 %.

INTERPRETATION

Technology-assisted assessments of movement in infants less than 6 months CA using current technologies are feasible. Validation of measurement tools are limited. Although methods and results appear promising clinical uptake of technology-assisted assessments remains limited.

Lifespace metrics of older adults with mild cognitive impairment and dementia recorded via geolocation data

OBJECTIVE

Lifespace, the physical area in which someone conducts life activities, indicates lived community mobility. This study explored the feasibility of technology-based lifespace measurement for older people with dementia and mild cognitive impairment (MCI), including the generation of a range of lifespace metrics, and investigation of relationships with health and mobility status.

METHODS

An exploratory study was conducted within a longitudinal observational study. Eighteen older adults (mean age 86.7 years (SD: 3.2); 8 men; 15 MCI), participated. Lifespace metrics were generated from geolocation data (GPS and Bluetooth beacon) collected through a smartphone application for one week (2015-2016). Cognitive and mobility-related outcomes were compared from study data sets at baseline (2005-2007) and 6-year follow-up (2011-2014).

RESULTS

Lifespace data could be collected from all participants, and metrics were generated including percentage of time at home, maximum distance from home, episodes of travel in a week, days in a week participants left home, lifespace area (daily, weekly and total), indoor lifespace (regions in the home/hour), and a developed lifespace score that combined time, frequency of travel, distance and area. Results indicated a large range of lifespace areas (0.1 - 97.88 km² ; median 6.77 km² ) with similar patterns across lifespace metrics. Significant relationships were found between lifespace metrics and concurrent driving status and anteceding scores on the sit-to-stand test (at baseline and follow-up).

CONCLUSIONS

Further longitudinal exploration of lifespace is required to develop an understanding of the nature of lifespace of older community-dwelling people, and its relationship with health, mobility and well-being outcomes.

Digital health interventions for chronic diseases: a scoping review of evaluation frameworks

Background

Monitoring and evaluations of digital health (DH) solutions for the management of chronic diseases are quite heterogeneous and evidences around evaluating frameworks are inconsistent. An evidenced-based framework is needed to inform the evaluation process and rationale of such interventions. We aimed to explore the nature, extent and components of existing DH frameworks for chronic diseases.

Methods

This review was conducted based on the five steps of Arksey and O’Malley’s scoping review methodology. Out of 172 studies identified from, PubMed, Embase and Web of Science, 11 met our inclusion criteria. The reviewed studies developed DH frameworks for chronic diseases and published between 2010 and 2018.

Results

According to WHO guidelines for monitoring and evaluation of DH interventions, we identified seven Conceptual frameworks, two Results frameworks, one Logical framework and one Theory of change. The frameworks developed for providing interventions such as self-management, achieving personal goals and reducing relapse for cardiovascular disease, diabetes, chronic obstructive pulmonary disease and severe mental health. A few studies reported evaluation of the frameworks using randomised clinical trials (n=3) and feasibility testing via Likert scale survey (n=2). A wide range of outcomes were reported including access to care, cost-effectiveness, behavioural outcomes, patient–provider communications, technology acceptance and user experience.

Conclusion

There is a lack of evidence on the application of consistent DH frameworks. Future research should address the use of evidence-based frameworks into the research design, monitoring and evaluation process. This review explores the nature of DH frameworks for the management of chronic diseases and provides examples to guide monitoring and evaluation of interventions.

A prospective cohort study of prodromal Alzheimer's disease: Prospective Imaging Study of Ageing: Genes, Brain and Behaviour (PISA)

This prospective cohort study, "Prospective Imaging Study of Ageing: Genes, Brain and Behaviour" (PISA) seeks to characterise the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). In particular, we are recruiting midlife and older Australians with high and low genetic risk of dementia to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of disease onset. PISA utilises genetic prediction to recruit and enrich a prospective cohort and follow them longitudinally. Online surveys and cognitive testing are used to characterise an Australia-wide sample currently totalling over 3800 participants. Participants from a defined at-risk cohort and positive controls (clinical cohort of patients with mild cognitive impairment or early AD) are invited for onsite visits for detailed functional, structural and molecular neuroimaging, lifestyle monitoring, detailed neurocognitive testing, plus blood sample donation. This paper describes recruitment of the PISA cohort, study methodology and baseline demographics.

Sequence Classification Restricted Boltzmann Machines With Gated Units

For the classification of sequential data, dynamic Bayesian networks and recurrent neural networks (RNNs) are the preferred models. While the former can explicitly model the temporal dependences between the variables, and the latter have the capability of learning representations. The recurrent temporal restricted Boltzmann machine (RTRBM) is a model that combines these two features. However, learning and inference in RTRBMs can be difficult because of the exponential nature of its gradient computations when maximizing log likelihoods. In this article, first, we address this intractability by optimizing a conditional rather than a joint probability distribution when performing sequence classification. This results in the "sequence classification restricted Boltzmann machine" (SCRBM). Second, we introduce gated SCRBMs (gSCRBMs), which use an information processing gate, as an integration of SCRBMs with long short-term memory (LSTM) models. In the experiments reported in this article, we evaluate the proposed models on optical character recognition, chunking, and multiresident activity recognition in smart homes. The experimental results show that gSCRBMs achieve the performance comparable to that of the state of the art in all three tasks. gSCRBMs require far fewer parameters in comparison with other recurrent networks with memory gates, in particular, LSTMs and gated recurrent units (GRUs).

Use of eHealth in the management of pulmonary arterial hypertension: review of the literature

Background

Pulmonary arterial hypertension (PAH) is a severe chronic condition associated with poor quality of life and high risks of mortality and hospitalisation. The utilisation of novel diagnostic technologies has improved survival rates although the effectiveness of Electronic Health (eHealth) interventions in patients with a chronic cardiopulmonary disease remains controversial. As the effectiveness of eHealth can be established by specific evaluation for different chronic health conditions, the aim of this study was to explore and summarise the utilisation of eHealth in PAH.

Method

We searched PubMed, CINAHL and Embase for all studies reporting clinical trials on eHealth solutions for the management of PAH. No limitations in terms of study design or date of publication were imposed.

Results

18 studies (6 peer-reviewed journal papers and 12 conference papers) were identified. Seven studies addressed the accuracy, safety or reliability of eHealth technologies such as intra-arterial haemodynamic monitoring of the pulmonary artery pressure, self-administered 6-Minute walk test App, computerised step-pulse oximeter and ambulatory impedance cardiography. Two studies evaluated eHealth as part of the medical management and showed a reduction in hospitalisation rate.

Conclusions

The evidence of eHealth supporting the management of people with PAH is limited and only embraced through a few studies of small sample size and short-term duration. Given the proposed clinical benefits in heart failure, we postulate that the evaluation of eHealth for the clinical management of PAH is highly warranted.

Outcomes of a feasibility trial using an innovative mobile health programme to assist in insulin dose adjustment

Objective

Intensification of diabetes therapy with insulin is often delayed for people with suboptimal glycaemic control. This paper reports on the feasibility of using an innovative mobile health (mHealth) programme to assist a diabetes insulin dose adjustment (IDA) service.

Methods

Twenty adults with diabetes referred to a tertiary hospital IDA service were recruited. They were provided with a cloud-based mobile remote monitoring system—the mobile diabetes management system (MDMS). The credentialled diabetes educator (CDE) recorded the time taken to perform IDA utilising the MDMS versus the conventional method—which is a weekly adjustment of insulin doses by a CDE through telephone contact based on three or more daily blood glucose readings. Participants and staff completed a feedback questionnaire.

Results

The CDE spent 55% less time performing IDA using MDMS than using the conventional method. The participants were satisfied with MDMS use and the CDEs reported improved efficiency.

Conclusion

Incorporating a mHealth programme for an IDA service has the potential to improve service delivery efficiencies while simultaneously improving the patient experience.

P6215Limited functional capacity and physical activity associated with patient withdrawals from cardiac rehabilitation

Background

Cardiac rehabilitation (CR) assists patients with cardiovascular disease (CVD) in improving physical activity and effectively managing their health conditions. With numerous clinical benefits including reduced risks of mortality (by 25%) and all-cause hospitalizations (by 18% - 25%), CR has been strongly recommended by evidence-based clinical guidelines for secondary prevention of CVD. However, many CR participant withdraw and hence fail to fully benefit from their CR programme. To address this issue, knowledge on risk stratification of patients' characteristics to appropriate CR care pathways is important.

Purpose

The purpose of this study is to identify clinical baseline characteristics associated with patients who withdraw from a CR programme.

Methods

We retrospectively analysed patients who participated in the centre-based CR programmes of a research study in Queensland, Australia. The CR programmes provided structured sessions (training and education) once or twice a week for six weeks in community care centres. We compared the patients who withdrew from their CR programme (Group-W) with those who did not withdraw (or simply completion) (Group-C). Withdrawal was defined as discontinuing within the first four weeks of the CR programme. In the comparison, the one-way analysis of variance (ANOVA) and Fisher's exact test were used for analysing age and sex respectively. The analysis of covariance (ANCOVA) with an adjustment for age and sex was used for the body mass index (BMI), six-minute walk test (6WMT), and health-related quality of life (HeartQoL, ESC 2012), comprising physical (HeartQoL-Phy), emotional (HeartQoL-Emo), and global (HeartQoL-Glo) subscales. The study was approved by the Human Research Ethics Committee (Reference: HREC/16/QPAH/636).

Results

From Dec 2016 to Dec 2017, 600 outpatients with CVD were consented, and enrolled in the study. Seventy participants withdrew. Between the two groups (Group-W vs Group-C), no significant differences were found in age (64±12 years vs 65±10 years; p=0.4221), sex (Female, 31% vs 25%; p=0.2461) and BMI (30.5±6.2 vs 30.1±11.2; p=0.8211). The 6MWT distance was significantly lower in Group-W than Group-C (346±103 m vs 394±92 m; p=0.001). Significantly lower scores of HeartQoL-Phy (1.66±0.86 vs 1.93±0.74; p=0.0072) and HeartQoL-Glo scores (1.80±0.78 vs 2.02±0.67; p=0.0205) were found in Group-W. HeartQoL-Emo scores were lower in Group-W but the difference was not significant (2.19±0.73 vs 2.28±0.72; p=0.4550).

Conclusions

The levels of functional capacity measured by 6MWT and physical activity related quality of life were found to be significantly lower in withdrawal patients than those who completed their CR programme. The finding indicates that new care strategies, especially for patients with limited functional capacity and physical activity, are needed to improve the adherence and effectiveness of CR intervention in future studies.

Acknowledgement/Funding

CSIRO and Metro South Health

International feasibility trial on the use of an interactive mobile health platform for cardiac rehabilitation: protocol of the Diversity 1 study

Introduction

The implementation of home-based cardiac rehabilitation has demonstrated potential to increase patient participation, but the content and the delivering of the programmes varies across countries. The objective of this study is to investigate whether an Australian-validated mobile health (mHealth) platform for cardiac rehabilitation will be accepted and adopted irrespectively from the existing organisational and contextual factors in five different European countries.

Methods and analysis

This international multicentre feasibility study will use surveys, preliminary observations and analysis to evaluate the use and the user’s perceptions (satisfaction) of a validated mHealth platform in different contextual settings.

Ethics and dissemination

This study protocol has been approved by the Australian research organisation CSIRO and the respective ethical committees of the European sites. The dissemination of this trial will serve as a ground for the further implementation of an international large randomised controlled trial which will contribute to an effective global introduction of mHealth into daily clinical practice.

Evaluation of an innovative mobile health programme for the self-management of chronic obstructive pulmonary disease (MH-COPD): protocol of a randomised controlled trial

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death globally. In outpatient care, the self-management of COPD is essential, but patient adherence to this remains suboptimal. The objective of this study is to examine whether an innovative mobile health (mHealth)-enabled care programme (MH-COPD) will improve the patient self-management and relevant health outcomes.

METHODS AND ANALYSIS

A prospective open randomised controlled trial has been designed. In the trial, patients with COPD will be recruited from The Prince Charles Hospital, Brisbane, Australia. They will then be randomised to participate in either the MH-COPD intervention group (n=50 patients), or usual care control group (UC-COPD) (n=50 patients) for 6 months. The MH-COPD programme has been designed to integrate an mHealth system within a clinical COPD care service. In the programme, participants will use a mHealth application at home to review educational videos, monitor COPD symptoms, use an electronic action plan, modify the risk factors of cigarette smoking and regular physical activity, and learn to use inhalers optimally. All participants will be assessed at baseline, 3 months and 6 months. The primary outcomes will be COPD symptoms and quality of life. The secondary outcomes will be patient adherence, physical activity, smoking cessation, use of COPD medicines, frequency of COPD exacerbations and hospital readmissions, and user experience of the mobile app.

ETHICS AND DISSEMINATION

The clinical trial has been approved by The Prince Charles Hospital Human Research Ethics Committee (HREC/16/QPCH/252). The recruitment and follow-up of the trial will be from January 2019 to December 2020. The study outcomes will be disseminated according to the Consolidated Standards of Reporting Trials statement through a journal publication, approximately 6 months after finishing data collection.

TRIAL REGISTRATION NUMBER

ACTRN12618001091291.

Mobile-based insulin dose adjustment for type 2 diabetes in community and rural populations: study protocol for a pilot randomized controlled trial

BACKGROUND

Insulin initiation and/or titration for type 2 diabetes (T2DM) is often delayed as it is a resource-intensive process, often requiring frequent exchange of information between a patient and their diabetes healthcare professional, such as a credentialed diabetes educator (CDE) for insulin dose adjustment (IDA). Existing models of IDA are unlikely to meet the increasing service demand unless efficiencies are increased. Mobile health (mHealth), a subset of Ehealth, has been shown to improve glycaemic control through enhanced self-management and feedback leading to improved patient satisfaction and could simultaneously reduce costs. Considering the potential benefits of mHealth, we have developed an innovative mHealth-based care model to support patients and clinicians in diabetes specialist community outreach and telehealth clinics, that is, REthinking Model of Outpatient Diabetes care utilizing EheaLth - Insulin Dose Adjustment (REMODEL-IDA). This model primarily aims to improve the glycaemic management of patients with T2DM on insulin, with the secondary aims of improving healthcare service delivery efficiency and the patients' experience.

METHODS/DESIGN

A two-arm pilot randomized controlled trial (RCT) will be conducted for 3 months with 44 participants, randomized at a 1:1 ratio to receive either the mHealth-based model of care (intervention) or routine care (control), in diabetes specialist community outreach and telehealth clinics. The intervention arm will exchange information related to blood glucose levels via the Mobile Diabetes Management System developed for outpatients with T2DM. They will receive advice on insulin titration from the CDE via the mobile-app and receive automated text-message prompts for better self-management based on their blood glucose levels and frequency of blood glucose testing. The routine care arm will be followed up via telephone calls by the CDE as per usual practice. The primary outcome is change in glycated haemoglobin, a marker of glycaemic management, at 3 months. Patient and healthcare provider satisfaction, and time required to perform IDA by healthcare providers in both arms will be collected. This pilot study will guide the conduct of a large-scale pragmatic RCT in regional Australia.

Increasing Health Care Adherence Through Gamification, Video Feedback, and Real-World Rewards

Treatment non-adherence poses a sizeable and persistent challenge to health professionals. In the US alone, it is estimated that at least $100 billion per year is spent on avoidable health care costs with an additional $230 billion per year forfeited due to lost productivity. Efforts to increase adherence have yielded mixed results. We present an adaptable, theoretical framework that uses established gamification methods coupled with a means of motivating patients using real-world rewards. The framework presented herein is implemented via user interface modifications to a clinically validated health tracking app, as well as a means of delivering video feedback for viewing a variety of potential reward outcomes.

User Experience of an Innovative Mobile Health Program to Assist in Insulin Dose Adjustment: Outcomes of a Proof-Of-Concept Trial

BACKGROUND

Many patients with diabetes require insulin therapy to achieve optimal glycemic control. Initiation and titration of insulin often require an insulin dose adjustment (IDA) program, involving frequent exchange of blood glucose levels (BGLs) and insulin prescription advice between the patient and healthcare team. This process is time consuming with logistical barriers.

OBJECTIVE

To develop an innovative mobile health (m-Health) mobile-based IDA program (mIDA) and evaluate the user adherence and experience through a proof-of-concept trial.

METHODS

In the program, an m-Health system was designed to be integrated within a clinical IDA service, comprising a Bluetooth-enabled glucose meter, smartphone application, and clinician portal. Insulin-requiring patients with type-2 diabetes mellitus and stable BGL were recruited to use the m-Health system to record and exchange BGL entries, insulin dosages, and clinical messages for 2 weeks. The user experience was evaluated by a Likert scale questionnaire.

RESULTS

Nine participants, aged 58 ± 14 years (mean ± SD), completed the trial with average daily records of 3.1 BGL entries and 1.2 insulin dosage entries. The participants recognized the potential value of the clinical messages. They felt confident about managing their diabetes and were positive regarding ease of use and family support of the system, but disagreed that there were no technical issues. Finally, they were satisfied with the program and would continue to use it if possible.

CONCLUSIONS

The m-Health system for IDA showed promising levels of adherence, usability, perception of usefulness, and satisfaction. Further research is required to assess the feasibility and cost-effectiveness of using this system in outpatient settings.

Innovative Telemonitoring Enhanced Care Programme for Chronic Heart Failure (ITEC-CHF) to improve guideline compliance and collaborative care: protocol of a multicentre randomised controlled trial

INTRODUCTION

Chronic heart failure (CHF) is a life-threatening chronic disease characterised by periodic exacerbations and recurrent hospitalisations. In the management of CHF, patient compliance with evidence-based clinical guidelines is essential, but remains difficult practically. The objective of this study is to examine whether an Innovative Telemonitoring Enhanced Care Programme for CHF (ITEC-CHF) improves patients' compliance, and associated health and economic outcomes.

METHODS AND ANALYSIS

An open multicentre randomised controlled trial has been designed. Patients will be recruited and randomised to receive either ITEC-CHF (n=150) or usual care CHF (n=150) for at least 6 months. ITEC-CHF combines usual care and an additional telemonitoring service including remote weight monitoring, structured telephone support and nurse-led collaborative care. The primary outcomes are the compliance rates with the best-practice guidelines for daily weight monitoring. The secondary outcomes include the compliance with other guideline recommendations (health maintenance, medication, diet and exercise), health (health-related quality of life, risk factors, functional capacity and psychological states) and economic outcomes related to the use of healthcare resources such as hospital readmissions and general practitioner/emergency department visits.

ETHICS AND DISSEMINATION

The clinical trial has been approved by Peninsula Health Human Research Ethics Committee (HREC Reference: HREC/14/PH/27), Royal Perth Hospital Human Research Ethics Committee (Reference: 15-081) and the Curtin University Human Research Ethics Committee (Reference: HR 181/2014). We will disseminate the final results to the public via conferences and journal publications. A final study report will also be provided to the ethics committees.

TRIAL REGISTRATION NUMBER

Registered with Australian New Zealand Clinical Trial Registry (ACTRN12614000916640).

Predicting food nutrition facts using pocket-size near-infrared sensor

Diet monitoring is one of the most important aspects in preventative health care that aims to reduce various health risks. Manual recording has been a prevalence among all approaches yet it is tedious and often end up with a low adherence rate. Several existing techniques that have been developed to monitor food intake suffer too with accuracy, efficiency, and user acceptance rate. In this paper we propose a novel approach on measuring food nutrition facts, through a pocket-size non-intrusive near-infrared (NIR) scanner. We build efficient regression models that can make quantitative prediction on food nutrition contents, such as energy and carbohydrate. Our extensive experiments on off-the-shelf liquid foods demonstrates the accuracy of these regression models and proves the applicability of using NIR spectra that are collected by small hand-held scanner, on food nutrition prediction.

Understanding Smart Home Sensor Data for Ageing in Place Through Everyday Household Routines: A Mixed Method Case Study

Background

An ongoing challenge for smart homes research for aging-in-place is how to make sense of the large amounts of data from in-home sensors to facilitate real-time monitoring and develop reliable alerts.

Objective

The objective of our study was to explore the usefulness of a routine-based approach for making sense of smart home data for the elderly.

Methods

Maximum variation sampling was used to select three cases for an in-depth mixed methods exploration of the daily routines of three elderly participants in a smart home trial using 180 days of power use and motion sensor data and longitudinal interview data.

Results

Sensor data accurately matched self-reported routines. By comparing daily movement data with personal routines, it was possible to identify changes in routine that signaled illness, recovery from bereavement, and gradual deterioration of sleep quality and daily movement. Interview and sensor data also identified changes in routine with variations in temperature and daylight hours.

Conclusions

The findings demonstrated that a routine-based approach makes interpreting sensor data easy, intuitive, and transparent. They highlighted the importance of understanding and accounting for individual differences in preferences for routinization and the influence of the cyclical nature of daily routines, social or cultural rhythms, and seasonal changes in temperature and daylight hours when interpreting information based on sensor data. This research has demonstrated the usefulness of a routine-based approach for making sense of smart home data, which has furthered the understanding of the challenges that need to be addressed in order to make real-time monitoring and effective alerts a reality.

Feasibility of unobstrusive ambient sensors for fall detections in home environment

Falls are the leading threats of death, injury and hospital admissions of seniors. About one third of seniors fall every year. Real time fall detection is thus critical to support independent livings of seniors by getting timely interventions from carers/family members. Recent years along with the IoT booming, many wearable sensor based fall detection systems have been developed. However privacy concerns or simply forgot-to-wear make wearable sensors not very accepted by seniors in a home environment seeking long term monitoring solutions. This motivates the development of unobtrusive ambient fall detection system. In this paper, we reviewed studies in this area and categorised them into two types of approaches, namely active and passive. We also evaluated their feasibilities within five domains: obtrusiveness, power connectivity, affordability, complexity of installation and being tested in field trials. The evaluation results could be used as guidance in designing new unobtrusive ambient fall detection systems.

Activity of Daily Living assessment through wireless sensor data

Activity of Daily Living has become a clinical de facto instrument to assess daily functional status of older people living independently at home. Almost all ADLs scales are based on subjective assessment of clinical staff and self-reported responses of the elderly person. A great deal of variability in ADL assessment is likely due to the different cultural beliefs, language and education, and over-assessment of personal capability to potentially avoid negative consequences. This paper proposes automatic and objective ADLs assessment as key component of a technology platform that supports older people to live independently in their home, called Smarter Safer Homes. The objective ADL assessment is achieved through communicating data from simple non-intrusive, wireless sensors placed in a home environment. Pilot sensor data sets were collected over six months from nine independent living homes of participants aged 70+ year. The application of a clustering based, unsupervised learning method on these data sets demonstrates the potential to automatically detect five domains of activity contributing to functional independence. Furthermore, the method provides features that support elderlys self-monitoring of daily activities more regularly, that could provide the potential for timely and early intervention from family and carers.

Unsupervised daily routine and activity discovery in smart homes

The ability to accurately recognize daily activities of residents is a core premise of smart homes to assist with remote health monitoring. Most of the existing methods rely on a supervised model trained from a preselected and manually labeled set of activities, which are often time-consuming and costly to obtain in practice. In contrast, this paper presents an unsupervised method for discovering daily routines and activities for smart home residents. Our proposed method first uses a Markov chain to model a resident's locomotion patterns at different times of day and discover clusters of daily routines at the macro level. For each routine cluster, it then drills down to further discover room-level activities at the micro level. The automatic identification of daily routines and activities is useful for understanding indicators of functional decline of elderly people and suggesting timely interventions.

Examining an Australian physical activity and nutrition intervention using RE-AIM

Translating evidence-based interventions into community practice is vital to health promotion. This study used the RE-AIM framework to evaluate the larger dissemination of the ManUp intervention, an intervention which utilized interactive web-based technologies to improve the physical activity and nutrition behaviors of residents in Central Queensland, Australia. Data were collected for each RE-AIM measure (Reach, Effectiveness, Adoption, Implementation, Maintenance) using (i) computer-assisted telephone interview survey (N = 312) with adults (18 years and over) from Central Queensland, (ii) interviews with key stakeholders from local organizations (n = 12) and (iii) examination of project-related statistics and findings. In terms of Reach, 47% of participants were aware of the intervention; Effectiveness, there were no significant differences between physical activity and healthy nutrition levels in those aware and unaware; Adoption, 73 participants registered for the intervention and 25% of organizations adopted some part of the intervention; Implementation, 26% of participants initially logged onto the website, 29 and 17% started the web-based physical activity and nutrition challenges, 33% of organizations implemented the intervention, 42% considered implementation and 25% reported difficulties; Maintenance, an average of 0.57 logins and 1.35 entries per week during the 12 week dissemination and 0.27 logins and 0.63 entries per week during the 9-month follow-up were achieved, 22 and 0% of participants completed the web-based physical activity and nutrition challenges and 33.3% of organizations intended to continue utilizing components of the intervention. While this intervention demonstrated good reach, effectiveness, adoption and implementation warrant further investigation.

Making an APPropriate Care Program for Indigenous Cardiac Disease: Customization of an Existing Cardiac Rehabilitation Program

Cardiovascular disease is a major health problem for all Australians and is the leading cause of death in Aboriginal and Torres Strait Islanders. In 2010, more then 50% of all heart attack deaths were due to repeated events. Cardiac rehabilitation programs have been proven to be effective in preventing the recurrence of cardiac events and readmission to hospitals. There are however, many barriers to the use of these programs. To address these barriers, CSIRO developed an IT enabled cardiac rehabilitation program delivered by mobile phone through a smartphone app and succesfully trialed it in an urban general population. If these results can be replicated in Indigenous populations, the program has the potential to significantly improve life expectancy and help close the gap in health outcomes. The challenge described in this paper is customizing the existing cardiac health program to make it culturally relevant and suitable for Indigenous Australians living in urban and remote communities.

Modeling of human movement monitoring using Bluetooth Low Energy technology

Bluetooth Low Energy (BLE) is a wireless communication technology which can be used to monitor human movements. In this monitoring system, a BLE signal scanner scans signal strength of BLE tags carried by people, to thus infer human movement patterns within its monitoring zone. However to the extent of our knowledge one main aspect of this monitoring system which has not yet been thoroughly investigated in literature is how to build a sound theoretical model, based on tunable BLE communication parameters such as scanning time interval and advertising time interval, to enable the study and design of effective and efficient movement monitoring systems. In this paper, we proposed and developed a statistical model based on Monte-Carlo simulation, which can be utilized to assess impacts of BLE technology parameters in terms of latency and efficiency, on a movement monitoring system, and can thus benefit a more efficient system design.

Effectiveness of a web- and mobile phone-based intervention to promote physical activity and healthy eating in middle-aged males: randomized controlled trial of the ManUp study

BACKGROUND

The high number of adult males engaging in low levels of physical activity and poor dietary practices, and the health risks posed by these behaviors, necessitate broad-reaching intervention strategies. Information technology (IT)-based (Web and mobile phone) interventions can be accessed by large numbers of people, yet there are few reported IT-based interventions targeting males' physical activity and dietary practices.

OBJECTIVE

This study examines the effectiveness of a 9-month IT-based intervention (ManUp) to improve the physical activity, dietary behaviors, and health literacy in middle-aged males compared to a print-based intervention.

METHODS

Participants, recruited offline (eg, newspaper ads), were randomized into either an IT-based or print-based intervention arm on a 2:1 basis in favor of the fully automated IT-based arm. Participants were adult males aged 35-54 years living in 2 regional cities in Queensland, Australia, who could access the Internet, owned a mobile phone, and were able to increase their activity level. The intervention, ManUp, was based on social cognitive and self-regulation theories and specifically designed to target males. Educational materials were provided and self-monitoring of physical activity and nutrition behaviors was promoted. Intervention content was the same in both intervention arms; only the delivery mode differed. Content could be accessed throughout the 9-month study period. Participants' physical activity, dietary behaviors, and health literacy were measured using online surveys at baseline, 3 months, and 9 months.

RESULTS

A total of 301 participants completed baseline assessments, 205 in the IT-based arm and 96 in the print-based arm. A total of 124 participants completed all 3 assessments. There were no significant between-group differences in physical activity and dietary behaviors (P≥.05). Participants reported an increased number of minutes and sessions of physical activity at 3 months (exp(β)=1.45, 95% CI 1.09-1.95; exp(β)=1.61, 95% CI 1.17-2.22) and 9 months (exp(β)=1.55, 95% CI 1.14-2.10; exp(β)=1.51, 95% CI 1.15-2.00). Overall dietary behaviors improved at 3 months (exp(β)=1.07, 95% CI 1.03-1.11) and 9 months (exp(β)=1.10, 95% CI 1.05-1.13). The proportion of participants in both groups eating higher-fiber bread and low-fat milk increased at 3 months (exp(β)=2.25, 95% CI 1.29-3.92; exp(β)=1.65, 95% CI 1.07-2.55). Participants in the IT-based arm were less likely to report that 30 minutes of physical activity per day improves health (exp(β)=0.48, 95% CI 0.26-0.90) and more likely to report that vigorous intensity physical activity 3 times per week is essential (exp(β)=1.70, 95% CI 1.02-2.82). The average number of log-ins to the IT platform at 3 and 9 months was 6.99 (SE 0.86) and 9.22 (SE 1.47), respectively. The average number of self-monitoring entries at 3 and 9 months was 16.69 (SE 2.38) and 22.51 (SE 3.79), respectively.

CONCLUSIONS

The ManUp intervention was effective in improving physical activity and dietary behaviors in middle-aged males with no significant differences between IT- and print-based delivery modes.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry: ACTRN12611000081910; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12611000081910 (Archived by WebCite at http://www.webcitation.org/6QHIWad63).

A pilot study of a mobile-phone-based home monitoring system to assist in remote interventions in cases of acute exacerbation of COPD

We conducted a six-month feasibility study of a mobile-phone-based home monitoring system, called M-COPD. Patients with a history of moderate Acute Exacerbation of COPD (AECOPD) were given a mobile phone to record major symptoms (dyspnoea, sputum colour and volume), minor symptoms (cough and wheezing) and vital signs. A care team remotely monitored the recorded data and provided clinical interventions. Eight patients (mean age 65 years) completed the trial. Ten acute exacerbations occurred during the trial and were successfully treated at home. Prior to the AECOPD episode, the combined score of the major symptoms increased significantly (P < 0.05). Following the intervention, it decreased significantly (P < 0.05) within two weeks and returned to the baseline. The score of the minor symptoms also increased significantly (P < 0.05), but the decrease following the intervention was not significant. There were significantly fewer hospital admissions during the trial, fewer ED presentations and fewer GP visits than in a six-month matched period in the preceding year. The results demonstrate the potential of home monitoring for analysing respiratory symptoms for early intervention of AECOPD.

Measuring the lifespace of people with Parkinson's disease using smartphones: proof of principle

BACKGROUND

Lifespace is a multidimensional construct that describes the geographic area in which a person lives and conducts their activities, and reflects mobility, health, and well-being. Traditionally, it has been measured by asking older people to self-report the length and frequency of trips taken and assistance required. Global Positioning System (GPS) sensors on smartphones have been used to measure Lifespace of older people, but not with people with Parkinson's disease (PD).

OBJECTIVE

The objective of this study was to investigate whether GPS data collected via smartphones could be used to indicate the Lifespace of people with PD.

METHODS

The dataset was supplied via the Michael J Fox Foundation Data Challenge and included 9 people with PD and 7 approximately matched controls. Participants carried smartphones with GPS sensors over two months. Data analysis compared the PD group and the control group. The impact of symptom severity on Lifespace was also investigated.

RESULTS

Visualization methods for comparing Lifespace were developed including scatterplots and heatmaps. Lifespace metrics for comparison included average daily distance, percentage of time spent at home, and number of trips into the community. There were no significant differences between the PD and the control groups on Lifespace metrics. Visual representations of Lifespace were organized based on the self-reported severity of symptoms, suggesting a trend of decreasing Lifespace with increasing PD symptoms.

CONCLUSIONS

Lifespace measured by GPS-enabled smartphones may be a useful concept to measure the progression of PD and the impact of various therapies and rehabilitation programs. Directions for future use of GPS-based Lifespace are provided.

Examining participant engagement in an information technology-based physical activity and nutrition intervention for men: the manup randomized controlled trial

BACKGROUND

Males experience a shorter life expectancy and higher rates of chronic diseases compared to their female counterparts. To improve health outcomes among males, interventions specifically developed for males that target their health behaviors are needed. Information technology (IT)-based interventions may be a promising intervention approach in this population group, however, little is known about how to maximize engagement and retention in Web-based programs.

OBJECTIVE

The current study sought to explore attributes hypothesized to influence user engagement among a subsample of participants from the ManUp study, a randomized controlled trial testing the efficacy of an interactive Web-based intervention for promoting physical activity and nutrition among middle-aged males.

METHODS

Semistructured interviews were conducted and audiotaped with 20 of the ManUp participants. Interview questions were based on a conceptual model of engagement and centered on why participants took part in the study, what they liked and did not like about the intervention they received, and how they think the intervention could be improved. Interview recordings were transcribed and coded into themes.

RESULTS

There were five themes that were identified in the study. These themes were: (1) users' motives, (2) users' desired outcomes, (3) users' positive experiences, (4) users' negative emotions, and (5) attributes desired by user.

CONCLUSIONS

There is little research in the field that has explored user experiences in human-computer interactions and how such experiences may relate to engagement, especially among males. Although not conclusive, the current study provides some insight into what personal attributes of middle-aged males (such as their key motives and goals for participating) and attributes of the intervention materials (such as usability, control, and interactivity) may impact on user engagement in this group. These findings will be helpful for informing the design and implementation of future health behavior interventions for males.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry: ACTRN12611000081910; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12611000081910 (Archived by WebCite at http://www.webcitation.org/6M4lBlvCA).

Telehealth for chronic disease management: do we need to RE-AIM?

An increasing number of individuals are living with long term health conditions which they manage most of the time by themselves. This paper evaluates the use of information and communications technology platforms to provide evidence-based programs to help people with chronic disease to self-management these. It describes two different self-management strategies for chronic conditions, and the evaluation of their implementation in clinical trials, specifically in terms of reach, implementation fidelity, adoption and user perceptions. It also discusses the challenges in replicating trial findings in the real world, using the RE-AIM framework.

Determination of Activities of Daily Living of independent living older people using environmentally placed sensors

The rapid increase in the ageing population of most developed countries is presenting significant challenges to policymakers of public healthcare. To address this problem, we propose a Smarter Safer Home solution that enables ageing Australians to live independently longer in their own homes. The primary aim of our approach is to enhance the Quality of Life (QoL) of aged citizens and the Family Quality of Life (FQoL) for the adult children supporting their aged parents. To achieve this, we use environmentally placed sensors for non-intrusive monitoring of human behaviour. The various sensors will detect and gather activity and ambience data which will be fused through specific decision support algorithms to extract Activities of Daily Living (ADLs). Subsequently, these estimated ADLs would be correlated with reported and recorded health events to predicate health decline or critical health situations from the changes in ADLs.

A mobile-health system to manage chronic obstructive pulmonary disease patients at home

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in Australia and globally, and leads to a substantial burden on healthcare services. Effective and timely management of patients with COPD has been essential to alleviate COPD exacerbation, improve the quality of life, and consequently reduce the economic burden. To achieve this, a mobile and internet technologies assisted home care model (M-COPD) was developed to assist clinicians to remotely monitor and manage COPD conditions and events. This paper will focus on the technical aspect of M-COPD system by describing its setup and discussing how the M-COPD could address the clinical needs in monitoring and managing COPD conditions of patients at home.

A mobile phone enabled health promotion program for middle-aged males

The prevalence of chronic diseases among middle aged males outweigh their female counterparts in developed countries. To prevent this, delivery of health promotion programs targeting lifestyle modifications of physical activity and nutrition in middle-aged males has been essential, but often difficult. ManUp health promotion program was a recent initiative that uses current advances in information and communication technology (ICT) to reach the middle-aged males. One of the key components of the ICT approach was the development of smartphone application to enable middle-aged men to uptake the program with their own mobile phone. The smart phone application was aimed at providing varied level of challenges towards physical activity and healthy eating behavior, with interactive and motivational feedback SMS messages. The ManUp program was recently implemented and trialed in a randomized control trial in Gladstone and Rockhampton, Queens. This paper describes the components of the smart phone application integrated within the ManUp health promotion program.

Integrating a mobile health setup in a chronic disease management network

Supporting self management of chronic disease in collaboration with primary healthcare has been a national priority in order to mitigate the emerging disease burden on the already strained healthcare system. However, in practice, the uptake of self-management programs and compliance with clinical guidelines remain poor. Time constraints due to work commitments and lack of efficient monitoring tools have been the major barrier to the uptake and compliance. In this paper, we present a newly integrated mobile health system with a clinical chronic disease management network called cdmNet, which has already been validated to facilitate General Practitioners (GPs) to provide collaborative disease management services. The newly integrated solution takes advantage of the latest mobile web and wireless Bluetooth communication techniques to enable patients to record health data entries through ubiquitous mobile phones, and allows the data to be simultaneously shared by multidisciplinary care teams. This integration would enable patients to self-manage their chronic disease conditions in collaboration with GPs and hence, improve the uptake and compliance. Additionally, the proposed integration will provide a useful framework encouraging the translation of innovative mobile health technologies into highly regulated healthcare systems.

A framework for linking gait characteristics of patients with accelerations of the waist

This paper describes a framework for the analysis of accelerometer data as part of research undertaken in preparation for a clinical trial involving ambulatory monitoring of elderly rehabilitation patients. In particular we examine the response of side-mounted accelerometers to various gait patterns and attempt to establish a relationship with a biomechanical model for human gait. We explore the use of a linear predictive (LP) model as a basis for identifying key harmonic frequencies in the accelerometer response signals and use these harmonics to relate measured data back to harmonic predictions from the biomechanical model.

Effectiveness of a website and mobile phone based physical activity and nutrition intervention for middle-aged males: trial protocol and baseline findings of the ManUp Study

BACKGROUND

Compared to females, males experience higher rates of chronic disease and mortality, yet few health promotion initiatives are specifically aimed at men. Therefore, the aim of the ManUp Study is to examine the effectiveness of an IT-based intervention to increase the physical activity and nutrition behaviour and literacy in middle-aged males (aged 35-54 years).

METHOD/DESIGN

The study design was a two-arm randomised controlled trial, having an IT-based (applying website and mobile phones) and a print-based intervention arm, to deliver intervention materials and to promote self-monitoring of physical activity and nutrition behaviours. Participants (n = 317) were randomised on a 2:1 ratio in favour of the IT-based intervention arm. Both intervention arms completed assessments at baseline, 3, and 9 months. All participants completed self-report assessments of physical activity, sitting time, nutrition behaviours, physical activity and nutrition literacy, perceived health status and socio-demographic characteristics. A randomly selected sub-sample in the IT-based (n = 61) and print-based (n = 30) intervention arms completed objective measures of height, weight, waist circumference, and physical activity as measured by accelerometer (Actigraph GT3X). The average age of participants in the IT-based and print-based intervention arm was 44.2 and 43.8 years respectively. The majority of participants were employed in professional occupations (IT-based 57.6%, Print-based 54.2%) and were overweight or obese (IT-based 90.8%, Print-based 87.3%). At baseline a lower proportion of participants in the IT-based (70.2%) group agreed that 30 minutes of physical activity each day is enough to improve health compared to the print-based (82.3%) group (p = .026). The IT-based group consumed a significantly lower number of serves of red meat in the previous week, compared to the print-based group (p = .017). No other significant between-group differences were observed at baseline.

DISCUSSION

The ManUp Study will examine the effectiveness of an IT-based approach to improve physical activity and nutrition behaviour and literacy. Study outcomes will provide much needed information on the efficacy of this approach in middle aged males, which is important due to the large proportions of males at risk, and the potential reach of IT-based interventions.

TRIAL REGISTRATION

ACTRN12611000081910.

Evaluation of bluetooth low power for physiological monitoring in a home based cardiac rehabilitation program

Cardiovascular disease (CVD) is the leading cause of mortality in Australia, and places large burdens on the healthcare system. To assist patients with CVDs in recovering from cardiac events and mediating cardiac risk factors, a home based cardiac rehabilitation program, known as the Care Assessment Platform (CAP), was developed. In the CAP program, patients are required to manually enter health information into their mobile phones on a daily basis. The manual operation is often subject to human errors and is inconvenient for some elderly patients. To improve this, an automated wireless solution has been desired. The objectives of this paper are to investigate the feasibility of implementing the newly released Bluetooth 4.0 (BT4.0) for the CAP program, and practically evaluate BT4.0 communications between a developed mobile application and some emulated healthcare devices. The study demonstrated that BT4.0 addresses usability, interoperability and security for healthcare applications, reduces the power consumption in wireless communication, and improves the flexibility of interface for software development. This evaluation study provides an essential mobile BT4.0 framework to incorporate a large range of healthcare devices for clinical assessment and intervention in the CAP program, and hence it is useful for similar development and research work of other mobile healthcare solutions.

A mobile phone-based care model for outpatient cardiac rehabilitation: the care assessment platform (CAP)

BACKGROUND

Cardiac rehabilitation programs offer effective means to prevent recurrence of a cardiac event, but poor uptake of current programs have been reported globally. Home based models are considered as a feasible alternative to avoid various barriers related to care centre based programs. This paper sets out the study design for a clinical trial seeking to test the hypothesis that these programs can be better and more efficiently supported with novel Information and Communication Technologies (ICT).

METHODS/DESIGN

We have integrated mobile phones and web services into a comprehensive home- based care model for outpatient cardiac rehabilitation. Mobile phones with a built-in accelerometer sensor are used to measure physical exercise and WellnessDiary software is used to collect information on patients' physiological risk factors and other health information. Video and teleconferencing are used for mentoring sessions aiming at behavioural modifications through goal setting. The mentors use web-portal to facilitate personal goal setting and to assess the progress of each patient in the program. Educational multimedia content are stored or transferred via messaging systems to the patients phone to be viewed on demand. We have designed a randomised controlled trial to compare the health outcomes and cost efficiency of the proposed model with a traditional community based rehabilitation program. The main outcome measure is adherence to physical exercise guidelines.

DISCUSSION

The study will provide evidence on using mobile phones and web services for mentoring and self management in a home-based care model targeting sustainable behavioural modifications in cardiac rehabilitation patients.

TRIAL REGISTRATION

The trial has been registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) with number ACTRN12609000251224.

Automatic detection of respiration rate from ambulatory single-lead ECG

Ambulatory electrocardiography is increasingly being used in clinical practice to detect abnormal electrical behavior of the heart during ordinary daily activities. The utility of this monitoring can be improved by deriving respiration, which previously has been based on overnight apnea studies where patients are stationary, or the use of multilead ECG systems for stress testing. We compared six respiratory measures derived from a single-lead portable ECG monitor with simultaneously measured respiration air flow obtained from an ambulatory nasal cannula respiratory monitor. Ten controlled 1-h recordings were performed covering activities of daily living (lying, sitting, standing, walking, jogging, running, and stair climbing) and six overnight studies. The best method was an average of a 0.2-0.8 Hz bandpass filter and RR technique based on lengthening and shortening of the RR interval. Mean error rates with the reference gold standard were +/-4 breaths per minute (bpm) (all activities), +/-2 bpm (lying and sitting), and +/-1 breath per minute (overnight studies). Statistically similar results were obtained using heart rate information alone (RR technique) compared to the best technique derived from the full ECG waveform that simplifies data collection procedures. The study shows that respiration can be derived under dynamic activities from a single-lead ECG without significant differences from traditional methods.

Simulated fall detection via accelerometers

We have derived a fall detection algorithm with high sensitivity and specificity from a single accelerometer device worn at the hip. A small clinical trial to obtain accelerometer data corresponding with actual falls experienced by elderly patients failed to provide a statistically significant number of fall events from which to develop an algorithm. Consequently, the detection algorithm was based on analysis of acceleration data containing 201 simulated falls. Although simulated, falls were modelled on video data of actual falls recorded in an elderly population. Nineteen different fall types were represented in the simulated data set which is advancement on previous simulation studies.

Quantifying functional mobility progress for chronic disease management

A method for quantifying improvements in functional mobility is presented based on patient-worn accelerometer devices. For patients with cardiovascular, respiratory, or other chronic disease, increasing the amount of functional mobility is a large component of rehabilitation programs. We have conducted an observational trial on the use of accelerometers for quantifying mobility improvements in a small group of chronic disease patients (n=15, 48 - 86 yrs). Cognitive impairments precluded complex instrumentation of patients, and movement data was obtained from a single 2-axis accelerometer device worn at the hip. In our trial, movement data collected from accelerometer devices was classified into Lying vs Sitting/Standing vs Walking/Activity movements. This classification enabled the amount of walking to be quantified and graphically presented to clinicians and carers for feedback on exercise efficacy. Presenting long term trends in this data to patients also provides valuable feedback for self managed care and assisting with compliance.