AIMC Topic: Hand

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Visualizing Worklog Based on Human Working Activity Recognition Using Unsupervised Activity Pattern Encoding.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Wearable motion sensor-based complex activity recognition during working hours has recently been studied to evaluate and thereby improve worker productivity. In the application of this technique to practical fields, one of the biggest challenges is p...
Hand Workload Motion Movement Humans Machine Learning Human Activities
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Regression of Hand Movements from sEMG Data 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 Jul 1, 2020
Most wearable human-machine interfaces concerning hand movements only focus on classifying a limited number of hand gestures. With the introduction of deep learning, surface electromyography based hand gesture classification systems improved drastica...
Hand Neural Networks, Computer Electromyography Gestures Humans Movement
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Investigating muscle synergies changes after rehabilitation robotics training on stroke survivors: a pilot study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
The current knowledge about muscle synergies does not clearly explain how both rehabilitation and brain plasticity act on the way they evolve after a cortical stroke. In this preliminary study, the authors analyzed the correlation between healthy and...
Stroke Survivors Robotics Hand Humans Pilot Projects
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Dexterous Force Estimation during Finger Flexion and Extension Using Motor Unit Discharge Information.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
With the development of advanced robotic hands, a reliable neural-machine interface is essential to take full advantage of the functional dexterity of the robots. In this preliminary study, we developed a novel method to estimate isometric forces of ...
Patient Discharge Fingers Humans Robotics Hand Electromyography
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Patient-Specific Robot-Assisted Stroke Rehabilitation Guided by EEG - A Feasibility Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Multi-session robot-assisted stroke rehabilitation program requires patients to perform repetitive tasks. It is challenging for the patient to maintain concentration during training sessions. A novel intervention strategy using Electroencephalography...
Humans Robotics Feasibility Studies Stroke Rehabilitation Electroencephalography Hand
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Pose Estimation from Electromyographical Data using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
This work demonstrates the effectiveness of Convolutional Neural Networks in the task of pose estimation from Electromyographical (EMG) data. The Ninapro DB5 dataset was used to train the model to predict the hand pose from EMG data. The models predi...
Accelerometry Hand Electromyography Humans Neural Networks, Computer
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An Improved Performance of Deep Learning Based on Convolution Neural Network to Classify the Hand Motion by Evaluating Hyper Parameter.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 1, 2020
High accuracy in pattern recognition based on electromyography(EMG) contributes to the effectiveness of prosthetics hand development. This study aimed to improve performance and simplify the deep learning pre-processing based on the convolution neura...
Hand Electromyography Neural Networks, Computer Machine Learning Deep Learning
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Gesture Classification for a Hand Controller Device Using Neural Networks.

Studies in health technology and informatics Jun 16, 2020
This paper presents a convolutional neural network-based classification of the hand flexion and extension gestures used in wrist recovery after injury. The hand gesture recognition device used in our study is the Leap Motion controller. The Leap Moti...
Hand Motion Humans Gestures Wrist Neural Networks, Computer Databases, Factual
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Factors affecting the usability of an assistive soft robotic glove after stroke or multiple sclerosis.

Journal of rehabilitation medicine Mar 18, 2020
OBJECTIVE: To explore the usability and effects of an assistive soft robotic glove in the home setting after stroke or multiple sclerosis.
Robotics Self-Help Devices Adult Hand Multiple Sclerosis Stroke Humans Male Stroke Rehabilitation Activities of Daily Living Female
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Hand motion analysis during robot-aided rehabilitation in chronic stroke.

Journal of biological regulators and homeostatic agents Jan 1, 2020
A high percentage of post-stroke patients reports spasticity and no functional use of the upper limb. To adapt the therapy in the most patient-specific manner, it is of paramount importance to objectively assess motor improvement during rehabilitatio...
Humans Chronic Disease Stroke Range of Motion, Articular Stroke Rehabilitation Robotics Hand
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