Continuous dynamic gesture recognition using surface EMG signals based on blockchain-enabled internet of medical things

Li, Gongfa; Bai, Dongxu; Jiang, Guozhang; Du, Jiang; Yun, Juntong; Yang, Zhiwen; Sun, Ying

doi:10.1016/j.ins.2023.119409

Cited by 14 publications

(3 citation statements)

References 45 publications

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“…[46][47][48][49][50][51] 6D pose estimation based on point can relies on point cloud registration technology, while 3D point cloud registration can generally be divided into two stages: initial registration and fine registration. [52][53][54][55][56][57] Both rough registration and fine registration are important. Rough registration provides approximate pose, while fine registration further optimizes the pose of the object.…”

Section: Related Workmentioning

confidence: 99%

Object pose estimation based on stereo vision with improvedK‐DtreeICPalgorithm

Huang

Wang

Yun

et al. 2023

Concurrency and Computation

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SummaryWith the wide application of stereovision in SLAM, object pose estimation has gradually become one of the research hotspots. This article proposes an object pose estimation for robotic grasping based on stereo vision with improved K‐D tree ICP algorithm. The feature points and feature descriptors of the point cloud of the object to be captured are extracted, and the feature template set is established. The SAC‐IA algorithm is used to carry out initial registration of the point cloud of the target, and the ICP algorithm based on K‐D tree is used for fine registration. The experimental results show that the average coincidence degree of the final registration of the proposed object pose estimation method reaches 94.1%, and the accurate 6D pose of the object to be grasped is obtained.

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Section: Related Workmentioning

confidence: 99%

Object pose estimation based on stereo vision with improvedK‐DtreeICPalgorithm

Huang

Wang

Yun

et al. 2023

Concurrency and Computation

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show abstract

“…A smaller μ enables better but slower convergence and vice versa. [72][73][74][75][76] Considering fitting performance and efficiency, the μ value was taken as 75*efr, where efr was the effective aperture radius.…”

Section: Algorithm For Voltage Calculationmentioning

confidence: 99%

Design of novel deformable mirror with large displacement

Li,

Tian,

Wang

et al. 2023

Concurrency and Computation

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SummaryA stabilized zoom system with deformable mirrors (DMs) was designed for continuous optical zoom. In order to adjust the focal length and expand the field angle, the characteristic surface shapes of the DMs composed of the low‐order and high‐order Zernike polynomials were provided. The maximum peak‐to‐valley (PV) value at the center of the surface shape is 80 μm. This work presents a piezoelectrically‐actuated deformable mirror (PADM) with large displacement for a stabilized zoom system. The COMSOL simulation was conducted to obtain the desired design by matching and optimizing structural parameters. The maximum displacement of PADM was more than 80 μm. The fitting results by the steepest descent algorithm (SD) showed that the RMS values of the residual surface shapes were 1 of 7 to 1 of 4 of their PV values, and the PV values of the residual surface shapes were less than 1 of 10 of the PV values of the target surface shapes.

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“…In this approach, adjacent windows partially overlap, as shown in Figure 4. This sliding window-based segmentation effectively addresses the temporal characteristics of muscle sEMG signals, enhancing the gesture recognition system's accuracy and robustness [21]. Using this technique, we extract relevant temporal information from sEMG signals, improving the system's ability to identify and recognize different gestures.…”

Section: Overlapped Sliding Window Segmentationmentioning

confidence: 99%

Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model

Yu,

Deng,

Bao

et al. 2023

Bioengineering

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Accurate and real-time gesture recognition is required for the autonomous operation of prosthetic hand devices. This study employs a convolutional neural network-enhanced channel attention (CNN-ECA) model to provide a unique approach for surface electromyography (sEMG) gesture recognition. The introduction of the ECA module improves the model’s capacity to extract features and focus on critical information in the sEMG data, thus simultaneously equipping the sEMG-controlled prosthetic hand systems with the characteristics of accurate gesture detection and real-time control. Furthermore, we suggest a preprocessing strategy for extracting envelope signals that incorporates Butterworth low-pass filtering and the fast Hilbert transform (FHT), which can successfully reduce noise interference and capture essential physiological information. Finally, the majority voting window technique is adopted to enhance the prediction results, further improving the accuracy and stability of the model. Overall, our multi-layered convolutional neural network model, in conjunction with envelope signal extraction and attention mechanisms, offers a promising and innovative approach for real-time control systems in prosthetic hands, allowing for precise fine motor actions.

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Continuous dynamic gesture recognition using surface EMG signals based on blockchain-enabled internet of medical things

Cited by 14 publications

References 45 publications

Object pose estimation based on stereo vision with improvedK‐DtreeICPalgorithm

Object pose estimation based on stereo vision with improvedK‐DtreeICPalgorithm

Design of novel deformable mirror with large displacement

Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model

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