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Jin Su Kim, Cheol Ho Song, Jae Myung Kim, Jimin Lee, Yeong-Hyeon Byeon, Jaehyo Jung, Hyun-Sik Choi, Keun-Chang Kwak, Youn Tae Kim, EunSang Bak and Sungbum Pan
Current advancements in biosignal-based user recognition technology are paving the way for a next-generation solution that addresses the limitations of face- and fingerprint-based user recognition methods. However, existing biosignal benchmark databases ...
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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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Nelson Cárdenas-Bolaño, Aura Polo and Carlos Robles-Algarín
This paper presents the implementation of an intelligent real-time single-channel electromyography (EMG) signal classifier based on open-source hardware. The article shows the experimental design, analysis, and implementation of a solution to identify fo...
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Xiufang Yang, Youchao Sun, Zhonglin Wu and Zongpeng Wang
This study aimed to evaluate pilot manipulation comfort in different flight scenarios under different ambient temperatures. To achieve this goal, we designed a test plan to devise the physiological indexes used in the evaluation of pilot manipulation com...
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Dawid Pawus and Szczepan Paszkiel
This article is a continuation and extension of research on a new approach to the classification and recognition of EEG signals. Their goal is to control the mobile robot through mental commands, using a measuring set such as Emotiv Epoc Flex Gel. The he...
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Jae-Myeong Kim, Min-Gu Kim and Sung-Bum Pan
With the spread of the modern media industry, harmful genre contents are indiscriminately disseminated to teenagers. The password identification method used to block sensational and violent genre content has become a problem that teenagers can easily ste...
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Krzysztof Strzecha, Marek Krakós, Boguslaw Wiecek, Piotr Chudzik, Karol Tatar, Grzegorz Lisowski, Volodymyr Mosorov and Dominik Sankowski
This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured E...
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Domenico Buongiorno, Giacomo Donato Cascarano, Cristian Camardella, Irio De Feudis, Antonio Frisoli and Vitoantonio Bevilacqua
The growing interest in wearable robots opens the challenge for developing intuitive and natural control strategies. Among several human?machine interaction approaches, myoelectric control consists of decoding the motor intention from muscular activity (...
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Saraswati Sridhar and Vidya Manian
Electroencephalogram signals are used to assess neurodegenerative diseases and develop sophisticated brain machine interfaces for rehabilitation and gaming. Most of the applications use only motor imagery or evoked potentials. Here, a deep learning netwo...
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Bu Il Jeon, Byung Jun Kang, Hyun Chan Cho and Jongwon Kim
An electromyogram (EMG) is a signal for muscle output that indicates the degree of muscle contraction and relaxation. For these muscle signals to be output, certain signals must be received from the brain. To analyze these relations, electroencephalogram...
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