IEEE-EMBS International Conference on Body Sensor Networks
October 10–12, 2026 · Porto, Portugal
The IEEE-EMBS International Conference on Body Sensor Networks (BSN 2026) is the premier forum for research in wearable sensing, mobile health, and computational medicine, bringing together experts from academia, industry, and clinical practice. In 2026, BSN comes to Porto, Portugal, a vibrant Atlantic city known for its innovation ecosystem, stunning architecture, and world-class culture, providing an inspiring setting for scientific exchange and new collaborations.
Theme
From Lab to Life: Scaling Intelligent Sensors for Personalized Health Ecosystems
This year’s theme highlights the transformative journey of body sensor networks from research prototypes to real-world healthcare solutions. It calls on the community to go beyond proof-of-concept studies and confront the practical challenges of scalability, ranging from design robustness and manufacturing to regulatory compliance and user acceptance. By focusing on translation, this theme emphasizes that innovation in health sensing is not complete until intelligent sensors thrive in the complexity of daily life, enabling truly personalized and connected health ecosystems.
Submission Tracks
- Full Technical Papers (4 pages)
- Technical Abstracts (1 page)
- Clinical Abstracts (1 page)
- Demos
- Workshops
Accepted Papers and Abstracts will be presented in oral and poster sessions.
In-person participation is expected for all accepted contributions; virtual presentations will not be accepted.
More Information / Submission Portal
Join us in Porto for BSN 2026 — where the BSN community meets cutting-edge science in one of Europe’s most unforgettable cities.
Questions? Contact: [email protected]
Key Dates:
| May 1, 2026 Workshop & Demo Proposal Deadline |
| June 1, 2026 Workshop & Demo Acceptance Notification |
| June 1, 2026 Full Paper Submission Deadline |
| June 1, 2026 Abstract Submission Deadline |
| Jul 15, 2026 Paper Acceptance Notification |
| Jul 15, 2026 Abstract Acceptance Notification |
| Aug 8, 2026 Camera-Ready and Early Bird Registration Deadline |
| Aug 8, 2026 Late Breaking Abstract Deadline |
| Sep 7, 2026 Late Breaking Abstract Notification |
| Oct 1, 2026 Registration Deadline |
| Oct 10-12, 2026 Conference venue: Alfândega do Porto |
All deadlines are 11:59 pm AoE
Conference Details
IEEE-EMBS BSN 2026 will accept regular 4-page technical papers and 1-page abstracts (technical or clinical). Excellent papers (e.g., Best Paper Award candidates) will be invited to extend their works for rapid review and publication in partnering journal IEEE Open Journal of Engineering in Medicine and Biology.
IEEE-EMBS BSN 2026 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. Topics of Interest included but are not limited to:
- Novel digital health solutions (i.e., sensors and algorithms) for diagnosis, disease progress tracking, and self-management.
- Sensors and systems for digital health, wellness, and athletics.
- 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.
- Optimization and personalization for digital health technologies and outcomes.
- Human-centered design for digital healthcare to address real-world stakeholder needs.
- Emerging topics such as Agentic AI and LLMs for computational health.