AIMC Topic: Gestures

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Head Motion and Head Gesture-Based Robot Control: A Usability Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jan 1, 2018
The assistive robot system adaptive head motion control for user-friendly support (AMiCUS) has been developed to increase the autonomy of motion impaired people. The six degrees of freedom robot arm with gripper is controlled with head motion and hea...
Female Young Adult Humans Patient Satisfaction Calibration Healthy Volunteers Head Movements Quadriplegia Self-Help Devices Man-Machine Systems Age Factors Gestures Activities of Daily Living Adult Male Robotics Middle Aged
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Application of support vector machines in detecting hand grasp gestures using a commercially off the shelf wireless myoelectric armband.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
The propose of this study was to assess the feasibility of using support vector machines in analysing myoelectric signals acquired using an off the shelf device, the Myo armband from Thalmic Lab, when performing hand grasp gestures. Participants (n =...
Feasibility Studies Arm Electromyography Pattern Recognition, Automated Support Vector Machine Signal Processing, Computer-Assisted Hand Strength Middle Aged Gestures Male Female Humans Adult Young Adult
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Convolutional neural network-based automatic classification of midsagittal tongue gestural targets using B-mode ultrasound images.

The Journal of the Acoustical Society of America Jun 1, 2017
Tongue gestural target classification is of great interest to researchers in the speech production field. Recently, deep convolutional neural networks (CNN) have shown superiority to standard feature extraction techniques in a variety of domains. In ...
Ultrasonography Tongue Signal Processing, Computer-Assisted Deep Learning Gestures Male Female Pattern Recognition, Automated Speech Acoustics Biomechanical Phenomena Voice Quality Humans Neural Networks, Computer
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Features extraction and multi-classification of sEMG using a GPU-Accelerated GA/MLP hybrid algorithm.

Journal of X-ray science and technology Jan 1, 2017
BACKGROUND: Surface electromyography (sEMG) signal is the combined effect of superficial muscle EMG and neural electrical activity. In recent years, researchers did large amount of human-machine system studies by using the physiological signals as co...
Pattern Recognition, Automated Man-Machine Systems Support Vector Machine Electromyography Algorithms Hand Gestures Humans Signal Processing, Computer-Assisted
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