A5066031569- Chronic Disease Management Strategies
- Emergency and Acute Care Studies
- Balance, Gait, and Falls Prevention
- Physical Activity and Health
- Clinical practice guidelines implementation
- Context-Aware Activity Recognition Systems
- Mobile Health and mHealth Applications
- Stroke Rehabilitation and Recovery
- Electronic Health Records Systems
- Dementia and Cognitive Impairment Research
- Cerebral Palsy and Movement Disorders
- Anomaly Detection Techniques and Applications
- Non-Invasive Vital Sign Monitoring
- Media Influence and Health
- Parkinson's Disease Mechanisms and Treatments
- Gait Recognition and Analysis
- Time Series Analysis and Forecasting
- Human Pose and Action Recognition
- Animal Behavior and Welfare Studies
- Healthcare Policy and Management
- Music and Audio Processing
- Innovative Human-Technology Interaction
- Digital Imaging for Blood Diseases
- Nutritional Studies and Diet
- Face and Expression Recognition
Philips (Netherlands)
2013-2021
NXP (Netherlands)
2020
Philips (India)
2014
Philips (Finland)
2010
Abstract Introduction Falling is among the most serious clinical problems in Parkinson's disease (PD). We used body‐worn sensors (falls detector worn as a necklace) to quantify hazard ratio of falls PD patients real life. Methods matched all 2063 elderly individuals with self‐reported without based on age, gender, comorbidity, and living conditions. analyzed fall events collected at home via wearable sensor. Fall were either automatically using or registered by button push same device....
Stress is a common problem that affects most people with dementia and their caregivers. symptoms for are often measured by answering checklist of questions the clinical staff who work closely person dementia. This process requires lot effort continuous observation over long term. article investigates effectiveness using straightforward method, based on single wristband sensor to classify events "Stressed" "Not stressed" The presented system calculates stress level as an integer value from...
Background: In the transition from a fee-for-service to fee-for-value system, health care organizations (HCOs) are under pressure keep patients healthy through preventive services and population management. Predictive analytics based on past behavior of patient can be used predict future risk decline. Objective: The objective this study was develop robust predictive models impending emergency transports hospital enrollment medical alert pattern data subscribers Personal Emergency Response...
This research motivates and evaluates the notion of similarity awareness as a means to enhance connectedness between remote family members. Similarity refers notifying connected individuals when they are engaged in similar activities. idea is illustrated with design evaluation MatchMaker an application targeting needs young adults who have recently left home their parents, so called 'empty nesters'. The potential affective benefits evaluated laboratory experiment involving 23 pairs parent...
The topic of human activity modeling and recognition still provides many challenges, despite receiving considerable attention. These challenges include the large number sensors often required for accurate recognition, need user-specific training samples. In this paper, an approach is presented activities daily living (ADL) using only a single camera microphone as sensors. Scene analysis techniques are used to classify audio video events, which model set hidden Markov models. Data was...
With a worldwide increase in the elderly population, and an associated health care utilization costs, preventing avoidable emergency department visits hospitalizations is becoming global priority. A personal response system (PERS), consisting of alarm button means to establish live connection center, can help at home longer independently. Individual risk assessment through predictive modeling indicate what PERS subscribers are elevated hospital transport so that early intervention becomes...
<sec> <title>BACKGROUND</title> With a worldwide increase in the elderly population, and an associated health care utilization costs, preventing avoidable emergency department visits hospitalizations is becoming global priority. A personal response system (PERS), consisting of alarm button means to establish live connection center, can help at home longer independently. Individual risk assessment through predictive modeling indicate what PERS subscribers are elevated hospital transport so...
Background Predictive analytics based on data from remote monitoring of elderly via a personal emergency response system (PERS) in the United States can identify subscribers at high risk for hospital transport. These predictions subsequently be used to proactively target interventions and prevent avoidable, costly health care use. It is, however, unknown if PERS-based prediction with targeted could also applied German setting. Objective The objectives were develop validate predictive model...
<sec> <title>BACKGROUND</title> Predictive analytics based on data from remote monitoring of elderly via a personal emergency response system (PERS) in the United States can identify subscribers at high risk for hospital transport. These predictions subsequently be used to proactively target interventions and prevent avoidable, costly health care use. It is, however, unknown if PERS-based prediction with targeted could also applied German setting. </sec> <title>OBJECTIVE</title> The...