We invite researchers, healthcare professionals and technology experts to contribute to a special session focusing on the measurement and analysis of health-related physiological parameters in the home environment. This session aims to explore the opportunities, challenges, and implications of monitoring these parameters outside of clinical settings.
Topics of interest include, but are not limited to:
1. Wearable devices and smart health home technology for real-time data collection.
2. Innovative methods and techniques for analysing vital signs, sleep patterns, and activity levels.
3. Integration of artificial intelligence (AI), including deep and traditional machine learning, and data analytics in home-based monitoring.
4. Personalised health management and early disease detection through continuous data collection.
5. Remote patient monitoring and improved patient outcomes.
6. Technical and methodological aspects of data collection, processing, and analysis in a home environment.
Researchers are encouraged to present their latest findings, methodologies, and innovations in the measurement of health-related physiological parameters at home. We also welcome submissions highlighting both successful and unsuccessful investigations, aiming to identify challenges and explore potential solutions.
Join us to foster interdisciplinary collaboration, knowledge sharing, and innovation in this rapidly evolving field. Together, let’s advance the measurement and analysis of health-related physiological parameters in the home environment.
Important Dates (like the main conference):
– Paper submission deadline (6 pages):
7 July 2023 24 July 2023 (sharp)
– Notification of acceptance: 18 August 2023
Please follow the guidelines provided on the conference website (https://applepies.eu/) for paper formatting and submission instructions. All papers will undergo a peer-review process. Submissions must be made under the “In-Home Measurement and Analysis of Health-Related Physiological Parameters” track (short name: “Physiological Measurements”)
We look forward to your valuable contributions to this special session.
Maksym Gaiduk1, Mostafa Haghi1, Vasileios Skaramagkas2, Ralf Seepold1
1HTWG Konstanz – University of Applied Sciences, Germany
2Electrical and Computer Engineering Department, Hellenic Mediterranean University, Computational Biomedicine Lab, FORTH, Greece