Emerging wearable interfaces and algorithms for hand gesture recognition: A survey

S Jiang, P Kang, X Song, BPL Lo… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
Hands are vital in a wide range of fundamental daily activities, and neurological diseases
that impede hand function can significantly affect quality of life. Wearable hand gesture …

[HTML][HTML] EMG-centered multisensory based technologies for pattern recognition in rehabilitation: state of the art and challenges

C Fang, B He, Y Wang, J Cao, S Gao - Biosensors, 2020 - mdpi.com
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …

[HTML][HTML] Surface EMG-based inter-session gesture recognition enhanced by deep domain adaptation

Y Du, W Jin, W Wei, Y Hu, W Geng - Sensors, 2017 - mdpi.com
High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity
from a restricted area of the skin by using two dimensional arrays of closely spaced …

Feasibility of wrist-worn, real-time hand, and surface gesture recognition via sEMG and IMU sensing

S Jiang, B Lv, W Guo, C Zhang, H Wang… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
While most wearable gesture recognition approaches focus on the forearm or fingers, the
wrist may be a more suitable location for practical use. We present the design and validation …

A novel, co-located EMG-FMG-sensing wearable armband for hand gesture recognition

S Jiang, Q Gao, H Liu, PB Shull - Sensors and Actuators A: Physical, 2020 - Elsevier
Gestures play an important role in human-computer interaction, providing a potentially
intuitive way to bridge the gap between human intention and the control of smart devices …

Toward robust, adaptiveand reliable upper-limb motion estimation using machine learning and deep learning–A survey in myoelectric control

T Bao, SQ Xie, P Yang, P Zhou… - IEEE journal of …, 2022 - ieeexplore.ieee.org
To develop multi-functionalhuman-machine interfaces that can help disabled people
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …

Capband: Battery-free successive capacitance sensing wristband for hand gesture recognition

H Truong, S Zhang, U Muncuk, P Nguyen… - Proceedings of the 16th …, 2018 - dl.acm.org
We present CapBand, a battery-free hand gesture recognition wearable in the form of a
wristband. The key challenges in creating such a system are (1) to sense useful hand …

Hand gesture recognition and finger angle estimation via wrist-worn modified barometric pressure sensing

PB Shull, S Jiang, Y Zhu, X Zhu - IEEE Transactions on Neural …, 2019 - ieeexplore.ieee.org
This paper presents a new approach to wearable hand gesture recognition and finger angle
estimation based on the modified barometric pressure sensing. Barometric pressure sensors …

Back-hand-pose: 3D hand pose estimation for a wrist-worn camera via dorsum deformation network

E Wu, Y Yuan, HS Yeo, A Quigley, H Koike… - Proceedings of the 33rd …, 2020 - dl.acm.org
The automatic recognition of how people use their hands and fingers in natural settings--
without instrumenting the fingers--can be useful for many mobile computing applications. To …

Gesture recognition for transhumeral prosthesis control using EMG and NIR

E Nsugbe, C Phillips, M Fraser… - IET Cyber‐Systems and …, 2020 - Wiley Online Library
A key challenge associated with myoelectric prosthesis limbs is the acquisition of a good
quality gesture intent signal from the residual anatomy of an amputee. In this study, the …