Simultaneous prediction of wrist/hand motion via wearable ultrasound sensing
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 26097088
- Type
- D - Journal article
- DOI
-
10.1109/TNSRE.2020.2977908
- Title of journal
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Article number
- 0
- First page
- 970
- Volume
- 28
- Issue
- 4
- ISSN
- 1534-4320
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
B - Computational Intelligence
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The first demonstration of A-mode ultrasound for human motion analytics. The method enables wrist, hand and finger motions and gestures to be predicted, leading to improved prostheses. Selected as a highlight article for the world-leading rehabilitation journal, IEEE Transactions on Neural Systems and Rehabilitation. It has been implemented by several research groups worldwide, including Prof. Tommaso Lenzi, University of Utah (for leg prosthetics), Prof. Xinjun Sheng, Shanghai Jiao Tong University (for hand prosthetics), Prof. Naoyuki Kubota, Tokyo Metropolitan University, and Prof. Jian Dai, King’s College London.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -