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Electromyography

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Multimodal Emotion Evaluation: A Physiological Model for Cost-Effective Emotion Classification.

Sensors (Basel, Switzerland)
Emotional responses are associated with distinct body alterations and are crucial to foster adaptive responses, well-being, and survival. Emotion identification may improve peoples' emotion regulation strategies and interaction with multiple life con...

Machine-Learning-Based Muscle Control of a 3D-Printed Bionic Arm.

Sensors (Basel, Switzerland)
In this paper, a customizable wearable 3D-printed bionic arm is designed, fabricated, and optimized for a right arm amputee. An experimental test has been conducted for the user, where control of the artificial bionic hand is accomplished successfull...

Adaptive robot mediated upper limb training using electromyogram-based muscle fatigue indicators.

PloS one
Studies on improving the adaptability of upper limb rehabilitation training do not often consider the implications of muscle fatigue sufficiently. In this study, electromyogram features were used as fatigue indicators in the context of human-robot in...

Pilot study: can machine learning analyses of movement discriminate between leg movements in sleep (LMS) with vs. without cortical arousals?

Sleep & breathing = Schlaf & Atmung
PURPOSE: Clinical and animal studies indicate frequent small micro-arousals (McA) fragment sleep leading to health complications. McA in humans is defined by changes in EEG and EMG during sleep. Complex EEG recordings during the night are usually req...

Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.

NeuroImage
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer-interfaces (BCI) or biomarker development and is facilitated by supervised machine learning. Yet, m...

Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning.

Ergonomics
This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work composed of mental arithmetic tasks with different levels of difficulty was designed and used in the experi...

Parkinson's Disease EMG Data Augmentation and Simulation with DCGANs and Style Transfer.

Sensors (Basel, Switzerland)
This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson's Disease (PD) electromyography (EMG) signals. The experimental results indicate...

Accurate recognition of lower limb ambulation mode based on surface electromyography and motion data using machine learning.

Computer methods and programs in biomedicine
Background and Objective The lower limb activity of recognition of the elderly, the weak, the disabled and the sick is an irreplaceable role in the caring of daily life. The main purpose of this study is to assess the feasibility of using the surface...

Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review.

Sensors (Basel, Switzerland)
Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human-Computer Interaction (HCI) has been developed to overcome the communication barriers bet...

Identification of Upper-Limb Movements Based on Muscle Shape Change Signals for Human-Robot Interaction.

Computational and mathematical methods in medicine
Towards providing efficient human-robot interaction, surface electromyogram (EMG) signals have been widely adopted for the identification of different limb movement intentions. Since the available EMG signal sensors are highly susceptible to external...