AI Medical Compendium Topic:
Electromyography

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Optimizing Input for Gesture Recognition using Convolutional Networks on HD-sEMG Instantaneous Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hand gesture recognition using high-density surface electromyography (HD-sEMG) has gained increasing attention recently due its advantages of high spatio-temporal resolution. Convolutional neural networks (CNN) have also recently been implemented to ...

sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work takes a step towards a better biosignal based hand gesture recognition by investigating the strategies for a reliable prediction of hand joint angles. Those strategies are especially important for medical applications in order to achieve e....

Deep Learning-based User Authentication with Surface EMG Images of Hand Gestures.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
User authentication is an important security mechanism to prevent unauthorized accesses to systems or devices. In this paper, we propose a new user authentication method based on surface electromyogram (sEMG) images of hand gestures and deep anomaly ...

Channel Synergy-based Human-Robot Interface for a Lower Limb Walking Assistance Exoskeleton.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The human-robot interface (HRI) based on surface electromyography(sEMG) can realize the natural interaction between human and robot. It has been widely used in exoskeleton robots recently to help predict the wearer's movement. The sEMG signal of the ...

Estimation of Joint Angle From sEMG and Inertial Measurements Based on Deep Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Continuous kinematics estimation from surface electromyography (sEMG) allows more natural and intuitive human-machine collaboration. Recent research has suggested the use of multimodal inputs (sEMG signals and inertial measurements) to improve estima...

Electromyography Signal Analysis and Classification using Time-Frequency Representations and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Analysis and classification of electromyography (EMG) signals are crucial for rehabilitation and motor control. This study investigates electromyogram (EMG) time-frequency representations and then creates conventional and deep learning models for EMG...

Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer Mapping.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Motion recognition based on surface electromyogram (sEMG) recorded from the forearm is attracting attention for its applicability because it easily integrates with wearable devices and has a high signal-to-noise ratio. Inter-subject variability and i...

Assessment of Muscle Activation of Caregivers Performing Dependent Transfers With a Novel Robotic-Assisted Transfer Device Compared With the Hoyer Advance.

American journal of physical medicine & rehabilitation
OBJECTIVE: The purpose of this study was to compare muscle activity in caregivers while using a novel robotic-assisted transfer device (Strong Arm) to a clinical standard of care (Hoyer Advance).

Emotion Recognition Using Spectral Feature from Facial Electromygraphy Signals for Human-Machine Interface.

Studies in health technology and informatics
Recognition of the emotions demonstrated by human beings plays a crucial role in healthcare and human-machine interface. This paper reports an attempt to classify emotions using a spectral feature from facial electromyography (facial EMG) signals in ...

[Mirror-type rehabilitation training with dynamic adjustment and assistance for shoulder joint].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The real physical image of the affected limb, which is difficult to move in the traditional mirror training, can be realized easily by the rehabilitation robots. During this training, the affected limb is often in a passive state. However, with the g...