Uptake of a technology-assisted home-care cardiac rehabilitation program.

The prevalence of cardiovascular disease, a major cause of disease burden in Australia and other developed countries, is increasing due to a rapidly ageing population and environmental, biomedical and modifiable lifestyle factors. Although cardiac rehabilitation (CR) programs have been shown to be beneficial and effective, rates of referral, uptake and utilisation of traditional hospital or community centre programs are poor. Home-based CR programs have been shown to be as effective as centre-based programs, and recent advances in information and communication technologies (ICT) can be used to enhance the delivery of such programs. The Care Assessment Platform (CAP) is an integrated home-based CR model incorporating ICT (including a mobile phone and the internet) and providing all the core components of traditional CR (education, physical activity, exercise training, behaviour modification strategies and psychological counselling). The mobile phone given to patients has an integrated accelerometer and diary application for recording exercise and health information. A central database, with access to these data, allows mentors to assess patients' progress, assist in setting goals, revise targets and give weekly personal feedback. Mentors find the mobile-phone modalities practical and easy to use, and preliminary results show high usage rates and acceptance of ICT by participants. The provision of ICT-supported home-based CR programs may enable more patients in both metropolitan and remote settings to benefit from CR.

Care assessment platform: an ICT-enabled home care model for secondary prevention of cardiovascular diseases.

BACKGROUND: Cardiovascular disease (CVD) is the leading chronic diseases affecting developed countries. Traditional approach to secondary prevention of CVD through hospital-based cardiac rehabilitation (CR) is hampered by the lack of uptake and adherence.

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.

Empowering citizens for well-being and chronic disease management with wellness diary.

Chronic conditions closely related to lifestyles are the major cause of disability and death in the developed world. Behavior change is the key to managing well-being and preventing and managing chronic diseases. Wellness diary (WD) is a mobile application designed to support citizens in learning about their behavior, and both making and maintaining behavior changes. WD has been found acceptable, useful, and suitable for long-term use as a part of an intervention. When used independently, however, it does not seem to have enough engaging and motivating features to support adoption and long-term commitment. The main improvement needs identified based on a review of WD-related studies were: personalization of the application to individual needs, increasing motivation during early use, maintaining motivation, and aiding in relapse recovery in long-term use. We present concepts to improve the personalization of WD as well as improvements to the feedback and interpretation of the self-observation data. We also present usage models on how this type of mobile application could be utilized.

Service and business model for technology enabled and home-based cardiac rehabilitation programs.

Cardiac rehabilitation programs are comprehensive life-style programs aimed at preventing recurrence of a cardiac event. However, the current programs have globally significantly low levels of uptake. Home-based model can be a viable alternative to hospital-based programs. We developed and analysed a service and business model for home based cardiac rehabilitation based on personal mentoring using mobile phones and web services. We analysed the different organizational and economical aspects of setting up and running the home based program and propose a potential business model for a sustainable and viable service. The model can be extended to management of other chronic conditions to enable transition from hospital and care centre based treatments to sustainable home-based care.

Mobile tools for home-based cardiac rehabilitation based on heart rate and movement activity analysis.

Cardiac rehabilitation programs are traditionally carried out in hospitals and health centers under the direct personal supervision of mentoring clinicians. Patient barriers, such as time constraints and distance from treatment centers, have lead to poor uptake of programs among eligible patients. To overcome these barriers, home-based care models have been proposed as a viable alternative to hospital-based cardiac rehabilitation programs. We have developed a measurement system and software tools on a mobile phone platform enabling patients to participate in a home-based cardiac rehabilitation exercise program. A mobile application, TuneWalk, gives guidance to the patients during home exercises using heart rate and physical activity analysis and also stores long-term information about their progress during the weeks of the rehabilitation program. The measured data are also sent to a server for remote exercise performance analysis and consultation by the patient's personal mentor.

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.

Physiological state characterization by clustering heart rate, heart rate variability and movement activity information.

The objective is to identify whether it is possible to discriminate between normal and abnormal physiological state based on heart rate (HR), heart rate variability (HRV) and movement activity information in subjects with cardiovascular complications. HR, HRV and movement information were obtained from cardiac patients over a period of 6 weeks using an ambulatory activity and single lead ECG monitor. By applying k-means clustering on HR, HRV and movement information obtained from cardiac patients, we obtained 3 clusters in inactive state and one cluster in active state. Two clusters in inactive state characterized by - a) high HR and low HRV b) low HRV and low HR, could be inferred as pathological with abnormal autonomic function. Further, activity information was significant in differentiating between the normal cluster found in active and an abnormal cluster found in inactive states, both with low HRV. This indicates that the activity information must be taken into account while interpreting HR and HRV information.

Wavelet based approach for posture transition estimation using a waist worn accelerometer.

The ability to rise from a chair is considered to be important to achieve functional independence and quality of life. This sit-to-stand task is also a good indicator to assess condition of patients with chronic diseases. We developed a wavelet based algorithm for detecting and calculating the durations of sit-to-stand and stand-to-sit transitions from the signal vector magnitude of the measured acceleration signal. The algorithm was tested on waist worn accelerometer data collected from young subjects as well as geriatric patients. The test demonstrates that both transitions can be detected by using wavelet transformation applied to signal magnitude vector. Wavelet analysis produces an estimate of the transition pattern that can be used to calculate the transition duration that further gives clinically significant information on the patients condition. The method can be applied in a real life ambulatory monitoring system for assessing the condition of a patient living at home.

Circadian activity rhythm in demented and non-demented nursing-home residents measured by telemetric actigraphy.

There is a need to develop unobtrusive methods for long-term monitoring of sleep/wake and circadian activity patterns in the elderly both in nursing homes and at home settings as sleep is important for health and well-being. The IST Vivago WristCare is an active social alarm system, which provides continuous telemetric monitoring of the user's activity. We examined how the activity signal measured by IST Vivago differed between demented and non-demented subjects living in a nursing home, and how it correlated with the subjective assessment of sleep quality and daytime alertness. The activity signal data together with subjective assessments of sleep quality and daytime vigilance were collected from 42 volunteers (aged 56-97 years; 23 demented and 19 non-demented) for at least 10 days. The demented subjects had lower daytime activity and higher nocturnal activity than the non-demented subjects. Correlations between the activity parameters and self-assessments were weak but statistically significant. We also found correlation between functional ability and diurnal activity. The results are in line with previous studies with demented and non-demented elderly subjects and suggest that the IST Vivago system provides a valid instrument for unobtrusive continuous long-term monitoring of the circadian rhythm and sleep/wake patterns in the elderly.