Wim Stut

WWICE : An architecture for in-home digital networks

The transition to digital information and networking of new digital devices lead to considerable changes in the consumer electronic industry. New applications will arise, offering more entertainment, comfort and flexibility. To achieve this, complex problems in communication and distributed systems need to be solved. High requirements on stability, usability, quality and price call for new solutions. This paper describes the concept of In-Home Digital Networks and will then in detail address the WWICE system. This new architecture provides a coherent system environment for the home. It focuses on services and applications, which can easily be accessed and controlled by the user. Application framework and middleware services of the layered software architecture efficiently support development of IHDN applications as well as flexible application control at runtime.

Clinical and cost-effectiveness of home-based cardiac rehabilitation compared to conventional, centre-based cardiac rehabilitation: Results of the FIT@Home study:

Aim Although cardiac rehabilitation improves physical fitness after a cardiac event, many eligible patients do not participate in cardiac rehabilitation and the beneficial effects of cardiac rehabilitation are often not maintained over time. Home-based training with telemonitoring guidance could improve participation rates and enhance long-term effectiveness. Methods and results We randomised 90 low-to-moderate cardiac risk patients entering cardiac rehabilitation to three months of either home-based training with telemonitoring guidance or centre-based training. Although training adherence was similar between groups, satisfaction was higher in the home-based group (p = 0.02). Physical fitness improved at discharge (p < 0.01) and at one-year follow-up (p < 0.01) in both groups, without differences between groups (home-based p = 0.31 and centre-based p = 0.87). Physical activity levels did not change during the one-year study period (centre-based p = 0.38, home-based p = 0.80). Healthcare costs were statistically non-significantly lower in the home-based group (€437 per patient, 95% confidence interval –562 to 1436, p = 0.39). From a societal perspective, a statistically non-significant difference of €3160 per patient in favour of the home-based group was found (95% confidence interval –460 to 6780, p = 0.09) and the probability that it was more cost-effective varied between 97% and 75% (willingness-to-pay of €0 and €100,000 per quality-adjusted life-years, respectively). Conclusion We found no differences between home-based training with telemonitoring guidance and centre-based training on physical fitness, physical activity level or health-related quality of life. However, home-based training was associated with a higher patient satisfaction and appears to be more cost-effective than centre-based training. We conclude that home-based training with telemonitoring guidance can be used as an alternative to centre-based training for low-to-moderate cardiac risk patients entering cardiac rehabilitation.

Adherence to self-care in patients with heart failure in the HeartCycle study.

Purpose The purpose of this study was to evaluate a novel online education and coaching program to promote self-care among patients with heart failure. In this program, education and coaching content is automatically tailored to the knowledge and behavior of the patient. Patients and methods The evaluation of the program took place within the scope of the HeartCycle study. This multi-center, observational study examined the ability of a third generation telehealth system to enhance the management of patients recently (<60 days) admitted to the hospital for worsening heart failure or outpatients with persistent New York Heart Association (NYHA) Functional Classification III/IV symptoms. Self-reported self-care behavior was assessed at baseline and study-end by means of the 9-item European Heart Failure Self-care Behavior scale. Adherence to daily weighing, blood pressure monitoring, and reporting of symptoms was determined by analyzing the system’s database. Results Of 123 patients enrolled, the mean age was 66±12 years, 66% were in NYHA III and 79% were men. Self-reported self-care behavior scores (n=101) improved during the study for daily weighing, low-salt diet, physical activity (P<0.001), and fluid restriction (P<0.05). Average adherence (n=120) to measuring weight was 90%±16%, to measuring blood pressure was 89%±17% and to symptom reporting was 66%±32%. Conclusion Self-reported self-care behavior scores improved significantly during the period of observation, and the objective evidence of adherence to daily weight and blood pressure measurements was high and remained stable over time. However, adherence to daily reporting of symptoms was lower and declined in the long-term.

Energy expenditure estimation in beta-blocker-medicated cardiac patients by combining heart rate and body movement data:

Background Accurate assessment of energy expenditure provides an opportunity to monitor physical activity during cardiac rehabilitation. However, the available assessment methods, based on the combination of heart rate (HR) and body movement data, are not applicable for patients using beta-blocker medication. Therefore, we developed an energy expenditure prediction model for beta-blocker-medicated cardiac rehabilitation patients. Methods Sixteen male cardiac rehabilitation patients (age: 55.8 ± 7.3 years, weight: 93.1 ± 11.8 kg) underwent a physical activity protocol with 11 low- to moderate-intensity common daily life activities. Energy expenditure was assessed using a portable indirect calorimeter. HR and body movement data were recorded during the protocol using unobtrusive wearable devices. In addition, patients underwent a symptom-limited exercise test and resting metabolic rate assessment. Energy expenditure estimation models were developed using multivariate regression analyses based on HR and body movement data and/or patient characteristics. In addition, a HR-flex model was developed. Results The model combining HR and body movement data and patient characteristics showed the highest correlation and lowest error (r2 = 0.84, root mean squared error = 0.834 kcal/minute) with total energy expenditure. The method based on individual calibration data (HR-flex) showed lower accuracy (i2 = 0.83, root mean squared error = 0.992 kcal/minute). Conclusions Our results show that combining HR and body movement data improves the accuracy of energy expenditure prediction models in cardiac patients, similar to methods that have been developed for healthy subjects. The proposed methodology does not require individual calibration and is based on the data that are available in clinical practice.

An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise:

Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping “desired behaviours” into specific system’s specifications, borrowing concepts from Fogg’s Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications.

Design and Usage of the HeartCycle Education and Coaching Program for Patients With Heart Failure.

BACKGROUND Heart failure (HF) is common, and it is associated with high rates of hospital readmission and mortality. It is generally assumed that appropriate self-care can improve outcomes in patients with HF, but patient adherence to many self-care behaviors is poor. OBJECTIVE The objective of our study was to develop and test an intervention to increase self-care in patients with HF using a novel, online, automated education and coaching program. METHODS The online automated program was developed using a well-established, face-to-face, home-based cardiac rehabilitation approach. Education is tailored to the behaviors and knowledge of the individual patient, and the system supports patients in adopting self-care behaviors. Patients are guided through a goal-setting process that they conduct at their own pace through the support of the system, and they record their progress in an electronic diary such that the system can provide appropriate feedback. Only in challenging situations do HF nurses intervene to offer help. The program was evaluated in the HeartCycle study, a multicenter, observational trial with randomized components in which researchers investigated the ability of a third-generation telehealth system to enhance the management of patients with HF who had a recent (<60 days) admission to the hospital for symptoms or signs of HF (either new onset or recurrent) or were outpatients with persistent New York Heart Association (NYHA) functional class III/IV symptoms despite treatment with diuretic agents. The patients were enrolled from January 2012 through February 2013 at 3 hospital sites within the United Kingdom, Germany, and Spain. RESULTS Of 123 patients enrolled (mean age 66 years (SD 12), 66% NYHA III, 79% men), 50 patients (41%) reported that they were not physically active, 56 patients (46%) did not follow a low-salt diet, 6 patients (5%) did not restrict their fluid intake, and 6 patients (5%) did not take their medication as prescribed. About 80% of the patients who started the coaching program for physical activity and low-salt diet became adherent by achieving their personal goals for 2 consecutive weeks. After becoming adherent, 61% continued physical activity coaching, but only 36% continued low-salt diet coaching. CONCLUSIONS The HeartCycle education and coaching program helped most nonadherent patients with HF to adopt recommended self-care behaviors. Automated coaching worked well for most patients who started the coaching program, and many patients who achieved their goals continued to use the program. For many patients who did not engage in the automated coaching program, their choice was appropriate rather than a failure of the program.

Predicting energy expenditure from photo-plethysmographic measurements of heart rate under beta blocker therapy: Data driven personalization strategies based on mixed models

Energy expenditure have been often estimated using computational models based on heart rate (HR) and appropriate personalization strategies to account for users cardio-respiratory characteristics. However, medications like beta blockers which are prescribed to treat several cardiac conditions have a direct influence on the cardiovascular system and may impact the relationship between HR and energy expenditure during physical activity (AEE). This study proposes to estimate AEE from HR using mixed models (MIX-REG) by introducing a novel method to personalize the prediction equation. We selected as features to represent the individual random effect in the MIX-REG model those subject characteristics which minimized both estimation error (RMSE) and between-subjects error bias variability. Data from 17 patients post-myocardial infarction were collected during a laboratory protocol. AEE was measured using indirect calorimetry and HR using an innovative wrist worn activity monitor equipped with the Philips Cardio and Motion Monitoring Module (CM3-Generation-1), which is an integrated module including a photo-plethysmographic and accelerometer sensor. The presented method showed large AEE estimation accuracy (RMSE = 1.35 kcal/min) which was comparable to that of models personalized using data from laboratory calibration protocols (HR-FLEX) and was superior to multi-linear regression and MIX-REG models trained using a stepwise features selection procedure.

The Explanations People Give for Going to Bed Late: A Qualitative Study of the Varieties of Bedtime Procrastination

ABSTRACT Background/Objective: Bedtime procrastination is a prevalent cause of sleep deprivation, but little is known about why people delay their bedtimes. In the present research, we conducted a qualitative study with bedtime procrastinators to classify their self-reported reasons for later-than-intended bedtime. Participants: Participants (N = 17) were selected who frequently engaged in bedtime procrastination, but whose sleep was not otherwise affected by diagnosed sleep disorders or shift work. Method: We conducted in-depth, semistructured interviews and used thematic analysis to identify commonly recurring themes in the interviews. Results and conclusions: Three emerging themes were identified: deliberate procrastination, mindless procrastination, and strategic delay. For the form of procrastination we classified as deliberate procrastination, participants typically reported wilfully delaying their bedtime because they felt they deserved some time for themselves. For the category of mindless procrastination, a paradigmatic aspect was that participants lost track of the time due to being immersed in their evening activities. Finally, participants who engaged in strategic delay reported going to bed late because they felt they needed to in order to fall asleep (more quickly), which suggests that despite describing themselves as “procrastinating,” their bedtime delay may actually be linked to undiagnosed insomnia. The conceptual distinctions drawn in this paper deepen our understanding of bedtime delay and may be helpful for designing effective interventions.

Proof of concept of a 45-second cardiorespiratory fitness self-test for coronary artery disease patients based on accelerometry

Cardiorespiratory fitness (CRF) provides important diagnostic and prognostic information. It is measured directly via laboratory maximal testing or indirectly via submaximal protocols making use of predictor parameters such as submaximal V˙O2, heart rate, workload, and perceived exertion. We have established an innovative methodology, which can provide CRF prediction based only on body motion during a periodic movement. Thirty healthy subjects (40% females, 31.3 ± 7.8 yrs, 25.1 ± 3.2 BMI) and eighteen male coronary artery disease (CAD) (56.6 ± 7.4 yrs, 28.7 ± 4.0 BMI) patients performed a V˙O2peak test on a cycle ergometer as well as a 45 second squatting protocol at a fixed tempo (80 bpm). A tri-axial accelerometer was used to monitor movements during the squat exercise test. Three regression models were developed to predict CRF based on subject characteristics and a new accelerometer-derived feature describing motion decay. For each model, the Pearson correlation coefficient and the root mean squared error percentage were calculated using the leave-one-subject-out cross-validation method (rcv, RMSEcv). The model built with all healthy individuals’ data showed an rcv = 0.68 and an RMSEcv = 16.7%. The CRF prediction improved when only healthy individuals with normal to lower fitness (CRF<40 ml/min/kg) were included, showing an rcv = 0.91 and RMSEcv = 8.7%. Finally, our accelerometry-based CRF prediction CAD patients, the majority of whom taking β-blockers, still showed high accuracy (rcv = 0.91; RMSEcv = 9.6%). In conclusion, motion decay and subject characteristics could be used to predict CRF in healthy people as well as in CAD patients taking β-blockers, accurately. This method could represent a valid alternative for patients taking β-blockers, but needs to be further validated in a larger population.

Potential role for clinical calibration to increase engagement with and application of home telemonitoring: a report from the HeartCycle programme

There is a need for alternative strategies that might avoid recurrent admissions in patients with heart failure. home telemonitoring (HTM) to monitor patients symptoms from a distance may be useful. This study attempts to assess changes in HTM vital signs in response to daily life activities (variations in medication, salt intake, exercise, and stress) and to establish which variations affect weight, blood pressure, and heart rate.