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Found 6 papers, 0 papers with code
Classification of Hand Gestures from Wearable IMUs using Deep Neural Network
The predicted outputs are analyzed in the form of classification accuracies which are then compared to the conventional classification schemes of SVM and kNN.
Activity Detection from Wearable Electromyogram Sensors using Hidden Markov Model
Classified outputs are compared with the transition regions in a stimulus given to the subject to perform the activity.
Continuous sign language recognition from wearable IMUs using deep capsule networks and game theory
Sign Language is used by the deaf community all over world.
Dual Stage Classification of Hand Gestures using Surface Electromyogram
The performance of the proposed approach is compared to the conventional single stage classification approach in terms of classification accuracies.
Transfer Learning for sEMG-based Hand Gesture Classification using Deep Learning in a Master-Slave Architecture
Recent advancements in diagnostic learning and development of gesture-based human machine interfaces have driven surface electromyography (sEMG) towards significant importance.
Convolutional Neural Network Array for Sign Language Recognition using Wearable IMUs
The proposed work presents a novel one-dimensional Convolutional Neural Network (CNN) array architecture for recognition of signs from the Indian sign language using signals recorded from a custom designed wearable IMU device.
