Call for Papers – “Special Issue “Systems, Applications and Services for Smart Health”
Deadline for manuscript submissions: 25 June 2020.
Special Issue Information
Changing infrastructure and new ICT developments are leading to new health services and applications that have the potential to disrupt the way with which we will perceive health care in the near future. Mobile Health solutions and medical Internet of Things (mIoT) devices, together with clinical wearables, personalized health coaching, mobile Apps, fitness trackers, digital diagnostics, and mobile health monitoring, will provide increased levels of data about our health and lifestyle in a continuous manner.
Sensory and quantitative measurements with objective data provide context-rich continuous longitudinal data. Due to the invention of an increasing number of medical-certified mobile devices, health data measurements are shifting from infrequent to frequent information retrieval and providing additional information for medical technology-reported outcomes. It can be foreseen that frequent health measurements (from smart devices) will also lead to a demand for more frequent health service consultations. Extracted digital biomarkers will feed prediction models and will subsequently lead to person-centered and personalized care models.
Prediction models can simulate the short-term and long-term effects of established behavioral interventions (e.g., improvements in dietary behavior, physical activity) in addition to simulating potential new interventions of interest (e.g., the improvement of sleep and smoking cessation). Based on the simulation results of these interventions, current care pathways can be adapted and personalized to specific patient contexts and phenotypic characteristics. As a direct result, instead of curing diseases, new health services can help to maintain health and a healthy lifestyle within a healthy environment.
Dr. Sten Hanke
Prof. Dr. Christopher Nugent
Dr. Mohammad Hossein Zoualfaghari
- Personalized health
- Internet of Things
- Behavior monitoring
- Predictive models