Wearable Sensor Systems for Applications in Rehabilitation
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 661
Special Issue Editor
Interests: applications of wearable sensors for objective outcomes in the rehabilitation and remote monitoring of physical capacity and brain health; rehabilitation biomechanics and applications of movement analysis of gait and balance to understand disabilities impacting mobility; analysis and evaluation of assistive technologies, including exoskeletons, prosthetics and orthotics, for mobility restoration
Special Issue Information
Dear Colleagues,
Many of us still remember when the only way to perform objective measurements of rehabilitation outcomes was to tether the patient to a complicated system of bulky, expensive and non-portable technologies in a research laboratory located at a university or research hospital. Today, wearable sensors offer a way to perform objective assessments and gauge outcomes in any environment and therefore have the potential to completely transform how and where we capture measurements relevant to the field of rehabilitation.
Importantly, the field of wearable sensors for rehabilitation crosses paths with many other disciplines, including (but not limited to) biomechanics, electrophysiology, signal processing and machine learning. Despite these recent advances, the penetration of wearable sensors in clinical practice remains limited. This Special Issue aims to provide a platform for addressing this shortcoming and invites authors to submit high-quality manuscripts reporting on advances in sensors and sensor systems for existing and emerging applications in rehabilitation, with a focus on informing the rehabilitation process. The topics include, but are not limited to, the following:
- Novel sensor systems for measuring physical/cognitive/emotional functioning outcomes relevant to rehabilitation.
- Outcome monitoring for adaptive rehabilitation systems.
- Sensor fusion for monitoring complex neurophysiological processes (e.g. neuroplasticity, pain, etc.) during rehabilitation.
- Sensor analytics (e.g. statistical models, machine learning, etc.) for capturing novel rehabilitation outcomes
- Barriers and Enablers to clinical adoption of wearable sensors for rehabilitation
- Translational research for using wearable sensors in rehabilitation practice
Prof. Dr. Chris McGibbon
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Wearable sensors. Rehabilitation
- Outcomes measures
- Real-time monitoring
- Movement
- Physiology
- Cognition
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