A Novel PPG-FMG-ACC Wristband for Hand Gesture Recognition

Wang, Hong; Kang, Peiqi; Gao, Qinghua; Jiang, Shuo; Shull, Peter B.

doi:10.1109/jbhi.2022.3194017

Cited by 15 publications

(1 citation statement)

References 56 publications

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“…This means that even better performance can come from combining three. Few researchers combined three modalities for HGR such as EMG + FMG + MMG, [ 88 ] PPG + FMG + ACC, [ 89 ] FMG + EMG + IMU, [ 90 ] and sEMG + MMG + NIRS. [ 91 ] As shown in Figure , the authors reported that the addition of MMG and NIRS to sEMG achieved higher classification of fatigued muscles which typically happened after 1 min sustained muscle contraction.…”

Section: Sensing Modalitiesmentioning

confidence: 99%

A Review of Hand Gesture Recognition Systems Based on Noninvasive Wearable Sensors

Tchantchane,

Zhou,

Zhang

et al. 2023

Advanced Intelligent Systems

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Hand gesture, one of the essential ways for a human to convey information and express intuitive intention, has a significant degree of differentiation, substantial flexibility, and high robustness of information transmission to make hand gesture recognition (HGR) one of the research hotspots in the fields of human–human and human–computer or human–machine interactions. Noninvasive, on‐body sensors can monitor, track, and recognize hand gestures for various applications such as sign language recognition, rehabilitation, myoelectric control for prosthetic hands and human–machine interface (HMI), and many other applications. This article systematically reviews recent achievements from noninvasive upper‐limb sensing techniques for HGR, multimodal sensing fusion to gain additional user information, and wearable gesture recognition algorithms to obtain more reliable and robust performance. Research challenges, progress, and emerging opportunities for sensor‐based HGR systems are also analyzed to provide perspectives for future research and progress.

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Section: Sensing Modalitiesmentioning

confidence: 99%

A Review of Hand Gesture Recognition Systems Based on Noninvasive Wearable Sensors

Tchantchane,

Zhou,

Zhang

et al. 2023

Advanced Intelligent Systems

View full text Add to dashboard Cite

show abstract

The use of CNNs in VR/AR/MR/XR: a systematic literature review

Cortes,

Bermejo,

Juiz

2024

Virtual Reality

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This study offers a systematic literature review on the application of Convolutional Neural Networks in Virtual Reality, Augmented Reality, Mixed Reality, and Extended Reality technologies. We categorise these applications into three primary classifications: interaction, where the networks amplify user engagements with virtual and augmented settings; creation, showcasing the networks’ ability to assist in producing high-quality visual representations; and execution, emphasising the optimisation and adaptability of apps across diverse devices and situations. This research serves as a comprehensive guide for academics, researchers, and professionals in immersive technologies, offering profound insights into the cross-disciplinary realm of network applications in these realities. Additionally, we underscore the notable contributions concerning these realities and their intersection with neural networks.

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