Advances in Sensors and Biosignal Processing for Wearable Technologies (SBPW)

Workshop Chair: Prof. Ivo Fridolin

Scope:

Wearable devices such as bracelets, activity trackers, smartwatches, and smartphones have becoming a natural part of our everyday life. This has led to the concept of self-tracking aiming to promote health activities via monitoring and increasing self-awareness. The advent of wearable technologies in our modern era has not only made data collection cheaper and more convenient but is allowing us to quantify biometrics we never knew existed. Through increased contact, connections and context, wearables will soon become an integral part into how individuals, organizations, and governments will shape decisions and drive innovation.
However, several challenges exist hampering to exploit the full potential of wearable devices like those associated with sensor design, performance, accuracy, signal analysis and algorithms connected closely with interpretation for the benefit of patients with specific diseases/disorders and of individuals for healthier, proactive lifestyle.
The aim of this session is to initiate discussions among technologists, engineers, and clinicians to synergize their efforts in producing low-cost, high-performance, highly efficient, deployable, clinically- intelligent sensors and signal processing methods for wearable technologies in modern lifestyle and healthcare systems.
The special session invites multidisciplinary contributors from academic and industrial researchers in the field of sensors and signal processing aiming ubiquitous biomedical measurements to identify and present technical challenges and recent results related to the wearable healthcare technologies.

Topics covered (but not limited to):

Wearable biomedical sensors
Novel sensor design and smart embodiment
Unobtrusive sensing
Flexible and stretchable sensors and devices
Predictive algorithms and biofeedback
Ambulatory human motion/activity monitoring
Data processing and data fusion
Intelligent and multiscale data processing
Medical and sensor data stream processing
Integration of sensor technologies
Body sensor networks

Paper submission:

Papers should be submitted through EAI ‘Confy’ system at Confy, and have to comply with the Springer format (see Author’s kit section).

Publication:

All accepted papers will be published together with the proceedings of MobiHealth 2017 by Springer and made available through SpringerLink Digital Library, one of the world’s largest scientific libraries.

Proceedings are submitted for inclusion to the leading indexing services: DBLP, Google Scholar, Thomson Scientific ISI Proceedings, EI Elsevier Engineering Index, CrossRef, Scopus, as well as EAI’s own EU Digital Library (EUDL).

Accepted Authors will be invited to submit an extended version of their work to Special Issue in the: