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Kalyan Chatterjee, M. Raju, N. Selvamuthukumaran, M. Pramod, B. Krishna Kumar, Anjan Bandyopadhyay and Saurav Mallik
According to global data on visual impairment from the World Health Organization in 2010, an estimated 285 million individuals, including 39 million who are blind, face visual impairments. These individuals use non-contact methods such as voice commands ...
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Alvaro A. Teran-Quezada, Victor Lopez-Cabrera, Jose Carlos Rangel and Javier E. Sanchez-Galan
Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long?short-term memory (LSTM) have become a means for providing solutions to problem...
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Rubén E. Nogales and Marco E. Benalcázar
Gesture recognition is widely used to express emotions or to communicate with other people or machines. Hand gesture recognition is a problem of great interest to researchers because it is a high-dimensional pattern recognition problem. The high dimensio...
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Ahmed Eid and Friedhelm Schwenker
Hand gestures are an essential part of human-to-human communication and interaction and, therefore, of technical applications. The aim is increasingly to achieve interaction between humans and computers that is as natural as possible, for example, by mea...
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Wensheng Chen, Yinxi Niu, Zhenhua Gan, Baoping Xiong and Shan Huang
Enhancing information representation in electromyography (EMG) signals is pivotal for interpreting human movement intentions. Traditional methods often concentrate on specific aspects of EMG signals, such as the time or frequency domains, while overlooki...
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Xiao Xu, Xuehan Zhang, Zhongxu Bao, Xiaojie Yu, Yuqing Yin, Xu Yang and Qiang Niu
Hand gesture recognition is an essential Human?Computer Interaction (HCI) mechanism for users to control smart devices. While traditional device-based methods support acceptable recognition performance, the recent advance in wireless sensing could enable...
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Mahmoud Elmezain, Majed M. Alwateer, Rasha El-Agamy, Elsayed Atlam and Hani M. Ibrahim
Automatic key gesture detection and recognition are difficult tasks in Human?Computer Interaction due to the need to spot the start and the end points of the gesture of interest. By integrating Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs),...
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Pablo Sarabia, Alvaro Araujo, Luis Antonio Sarabia and María de la Cruz Ortiz
Surface electromyography (sEMG) plays a crucial role in several applications, such as for prosthetic controls, human?machine interfaces (HMI), rehabilitation, and disease diagnosis. These applications are usually occurring in real-time, so the classifier...
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Christine Dewi, Abbott Po Shun Chen and Henoch Juli Christanto
Hand detection is a key step in the pre-processing stage of many computer vision tasks because human hands are involved in the activity. Some examples of such tasks are hand posture estimation, hand gesture recognition, human activity analysis, and other...
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Rytis Maskeliunas, Robertas Dama?evicius, Vidas Raudonis, Au?ra Adomaviciene, Juozas Raistenskis and Julius Gri?kevicius
One of the most difficult components of stroke therapy is regaining hand mobility. This research describes a preliminary approach to robot-assisted hand motion therapy. Our objectives were twofold: First, we used machine learning approaches to determine ...
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