IEEE-EMBS International Conference on Body Sensor Networks – Sensors and Systems for Digital Health (IEEE BSN) is the premier conference in the areas of sensors and systems for digital health. Celebrating the 20 years of IEEE BSN, the conference will embrace its new branding for “Sensors and Systems for Digital Health.” Sponsored by the IEEE Engineering in Medicine and Biology Society (IEEE-EMBS), the conference will be co-located with the IEEE-EMBS Conference on Healthcare Innovation and Point-of-Care Technologies (IEEE HI-POCT) in Boston.
Importance: IEEE BSN 2023 will accept regular 4-page technical papers, 1-page demo or poster abstracts, and 1-page clinical abstracts. Excellent papers (e.g., Best Paper Award candidates) will be invited to extend their works for rapid review and publication in several partnering journals, such as IEEE Open Journal of Engineering in Medicine and Biology, PLOS Digital Health, Circulation: Cardiovascular Quality and Outcomes, and Frontiers in Digital Health. See Call for Papers for more details.
IEEE BSN will bring together leaders and experts in academia, industry, healthcare, and non-profit organizations and provide a cross-disciplinary, highly selective, and single-track forum for cutting-edge research related to devices and sensors, hardware and software systems, predictive models, and data analytics in the healthcare/medical domains. Areas of interest include but are not limited to:
- Novel digital health solutions (i.e., sensors and algorithms) for diagnosis, disease progress tracking, and self-management.
- Prototyping of novel in-body, on-body, and off-body sensors and systems for digital health, wellness, and sports.
- Conformable decoders: unintrusive, comfortable, self-powered sensors and systems.
- Flexible, stretchable, and imperceptible electronics for sensors and systems.
- Contact-less solutions for human sensing.
- Power-optimization for implantable and wearable sensors and systems.
- Wearable robotics system for digital healthcare.
- Signal processing, machine learning, deep learning, and decision-support algorithms.
- Adaptive, personalized intervention systems by closing the loop between technologies and humans.
- Security, privacy, and trust in digital health technologies.
- Inclusiveness, fairness, and equality for under-represented and under-served communities in digital health technologies and studies.
- Human-centered design for digital healthcare to address real-world stakeholder needs.
