Е-Публикации
Технически университет - София

Цитирания (Citation/s):
1. Ruan, T., Liu, C., Yin, K., Zhou, S. Quantitative evaluation of the scope of application of hand motion recognition based on SVM, Proceedings - 2019 Chinese Automation Congress, CAC 2019, Article number 8997314, DOI: 10.1109/CAC48633.2019.8997314, pp. 4141-4145 - 2019 - в издания, индексирани в Scopus или Web of Science
2. Shivam, P., Kakoty, N.M., Malarvili, M.B., Widiyanti, P. Finger movement recognition based on muscle synergy using electromyogram., IEEE Region 10 Humanitarian Technology Conference, R10-HTC Volume 2019- Article number 9042432 2019 Indonesia, DOI: 10.1109/R10-HTC47129.2019.9042432 - 2019 - в издания, индексирани в Scopus или Web of Science
3. Uthvag, S.a,Vijay Sai, P.a, Dheeraj Kumar, S.a, Muthusamy, H.b, Chanu, O.R.a, Karthik Raj, V.aReal-time EMG Acquisition and Feature Extraction for Rehabilitation and Prosthesis., Biomedical Engineering - Applications, Basis and CommunicationsVolume 31, Issue 5, 1 October 2019, Article number 1950037, https://doi.org/10.4015/S1016237219500376 - 2019 - в издания, индексирани в Scopus или Web of Science
4. Phukan, N.a, Kakoty, N.M.a, Shivam, P.a, Gan, J.Q.b, Finger movements recognition using minimally redundant features of wavelet denoised EMG., Health and Technology, Volume 9, Issue 4, 1 August 2019, https://doi.org/10.1007/s12553-019-00338-z, pp. 579-593 - 2019 - в издания, индексирани в Scopus или Web of Science
5. Bhattachargee, C.K.a, Sikder, N.b,Hasan, M.T.a, Nahid, A.-A.a, Finger Movement Classification Based on Statistical and Frequency Features Extracted from Surface EMG Signals., 15th International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering, IC4ME2 2019July 2019, Article number Category numberCFP19O58-ART; Code 158616, DOI: 10.1109/IC4ME247184.2019.9036671 - 2019 - в издания, индексирани в Scopus или Web of Science
6. Côté-Allard, U.a, Fall, C.L.a, Drouin, A.b, Campeau-Lecours, A.c, Gosselin, C.c, Glette, K.d,e, Laviolette, F.b, Gosselin, B.a Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning., IEEE Transactions on Neural Systems and Rehabilitation EngineeringVolume 27, Issue 4, April 2019, Article number 8630679, DOI: 10.1109/TNSRE.2019.2896269 , pp. 760-771 - 2019 - в издания, индексирани в Scopus или Web of Science
7. Behrenbeck, J.a, Tayeb, Z.b,cBhiri, C.b,Richter, C.b,Rhodes, O.d,Kasabov, N.e,Espinosa-Ramos, J.I.e,Furber, S.d,Cheng, G.c,Conradt, J.bClassification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware., Journal of Neural Engineering, Volume 16, Issue 2, 2019, Article number 026014 - 2019 - в издания, индексирани в Scopus или Web of Science
8. Lu, Z.a,Stampas, A.a, Francisco, G.E.a, Zhou, P.a,bOffline and online myoelectric pattern recognition analysis and real-time control of a robotic hand after spinal cord injury., Journal of Neural Engineering, Volume 16, Issue 3, 2019, Article number 036018 - 2019 - в издания, индексирани в Scopus или Web of Science
9. • Saikia, A., Mazumdar, S.,Sahai, N., Paul, S., Bhatia, D. Performance Analysis of Artificial Neural Network for Hand Movement Detection from EMG Signals, IETE Journal of Research, 2019, https://doi.org/10.1080/03772063.2019.1638316 - 2019 - в издания, индексирани в Scopus или Web of Science
10. De Andrade, F.H.C., Pereira, F.G., Resende, C.Z., Cavalieri, D.C. Improving sEMG-Based Hand Gesture Recognition Using Maximal Overlap Discrete Wavelet Transform and an Autoencoder Neural Network, IFMBE Proceedings, Volume 70, 2019, 26th Brazilian Congress on Biomedical Engineering, CBEB 2018; Armação de Buzios; Brazil; 21 October 2018 through 25 October 2018; Code 226829, https://doi.org/10.1007/978-981-13-2517-5_42, pp.271-279 - 2019 - в издания, индексирани в Scopus или Web of Science
11. Phukan, N.,Kakoty, N.M. Sample entropy based selection of wavelet decomposition level for finger movement recognition using EMG., Advances in Intelligent Systems and Computing, Volume 713, 2019, , 2nd International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2017; Ajmer; India; 23 November 2017 through 25 November 2017; Code 216249, https://doi.org/10.1007/978-981-13-1708-8_6, pp. 61-73 - 2019 - в издания, индексирани в Scopus или Web of Science
12. Shahzaib, M., Shakil, S. Hand electromyography circuit and signals classification using artificial neural network., Article number 860358714th International Conference on Emerging Technologies, ICET 2018; Islamabad; Pakistan; 21 November 2018 through 22 November 2018; DOI: 10.1109/ICET.2018.8603587. - 2019 - в издания, индексирани в Scopus или Web of Science
13. Lu, Z.a, Tong, K.-Y.b, Zhang, X.c, Li, S.a, Zhou, P.d,e Myoelectric pattern recognition for controlling a robotic hand: A feasibility study in stroke., IEEE Transactions on Biomedical Engineering, Volume 66, Issue 2, February 2019, Article number 8365845, DOI: 10.1109/TBME.2018.2840848 , pp. 365-372 - 2019 - в издания, индексирани в Scopus или Web of Science
14. • Bhagwat, S., Mukherji, P. Electromyogram (EMG) based fingers movement recognition using sparse filtering of wavelet packet coefficients., Springer, Sadhana - Academy Proceedings in Engineering Sciences, 45(1),3, Volume 45, Issue 1, 1 December 2020, Article number 3, DOI: 10.1007/s12046-019-1231-9 - 2020 - в издания, индексирани в Scopus или Web of Science
15. • Jia, G., Lam, H.-K., Liao, J., Wang, R. Classification of electromyographic hand gesture signals using machine learning techniques., Neurocomputing, 401, pp. 236-248, Volume 401, 11 August 2020, Pages 236-248, Elsevier B.V., DOI: 10.1016/j.neucom.2020.03.009 - 2020 - в издания, индексирани в Scopus или Web of Science
16. • Bhagwat, S., Mukherji, P. Temporal Feature Extraction for Improving Myoelectric based Recognition of Prosthetic Hand., 2020 International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2020, 9198476, pp. 67-71, 2020August 2020, Article number 9198476, Pages 67-71, IEEE, DOI: 10.1109/WiSPNET48689.2020.9198476 - 2020 - в издания, индексирани в Scopus или Web of Science
17. Jia, G.a, Lam, H.-K.a,Ma, S.a,Yang, Z.b,Xu, Y.a,Xiao, B.cClassification of Electromyographic Hand Gesture Signals Using Modified Fuzzy C-Means Clustering and Two-Step Machine Learning Approach., IEEE Transactions on Neural Systems and Rehabilitation Engineering, Volume 28, Issue 6, June 2020, Article number 9062601, DOI: 10.1109/TNSRE.2020.2986884, pp. 1428-1435 - 2020 - в издания, индексирани в Scopus или Web of Science
18. Shahzaib, M., Shakil, S., Ghuffar, S., Maqsood, M., Bhatti, F.A. Classification of forearm EMG signals for 10 motions using optimum feature-channel combinations., Computer Methods in Biomechanics and Biomedical Engineering., Taylor and Francis Ltd. (Article in press), DOI: 10.1080/10255842.2020.1861256 - 2020 - в издания, индексирани в Scopus или Web of Science
19. Ovur S.E.,Zhou X.,Qi W.,Zhang L.,Hu Y.,Su H.,Ferrigno G.,De Momi E., A novel autonomous learning framework to enhance sEMG-based hand gesture recognition using depth information, Biomedical Signal Processing and Control, Volume 66April 2021 Article number 102444, DOI 10.1016/j.bspc.2021.102444 - 2021 - в издания, индексирани в Scopus или Web of Science
20. Zia ur Rehman, Muhammad, Syed Omer Gilani, Asim Waris, Imran Khan Niazi, Gregory Slabaugh, Dario Farina, and Ernest Nlandu Kamavuako. "Stacked sparse autoencoders for EMG-based classification of hand motions: A comparative multi day analyses between surface and intramuscular EMG." Applied Sciences 8, no. 7 (2018): 1126. - 2018 - в издания, индексирани в Scopus или Web of Science
21. Wu, Yu, Dai Jiang, Xiao Liu, Richard Bayford, and Andreas Demosthenous. "A human–machine interface using electrical impedance tomography for hand prosthesis control." IEEE transactions on biomedical circuits and systems 12, no. 6 (2018): 1322-1333. - 2018 - в издания, индексирани в Scopus или Web of Science
22. Mayor, John Jairo Villarejo, Regina Mamede Costa, Anselmo Frizera, and Teodiano Freire Bastos. "Dexterous hand gestures recognition based on low-density sEMG signals for upper-limb forearm amputees." Research on Biomedical Engineering 33 (2017): 202-217. - 2017 - в издания, индексирани в Scopus или Web of Science
23. Yang, Zhongliang, Yumiao Chen, Jianping Wang, and Hugh Gong. "Recognizing the breathing resistances of wearing respirators from respiratory and sEMG signals with artificial neural networks." International Journal of Industrial Ergonomics 58 (2017): 47-54. - 2017 - в издания, индексирани в Scopus или Web of Science
24. Anam, Khairul, Ahmad Adib Rosyadi, Bambang Sujanarko, and Adel Al-Jumaily. "Myoelectric control systems for hand rehabilitation device: A review." In 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), pp. 1-6. IEEE, 2017. - 2017 - в издания, индексирани в Scopus или Web of Science
25. Vu, Philip P., et al. "The future of upper extremity rehabilitation robotics: research and practice." Muscle & nerve 61.6 (2020): 708-718. - 2020 - в издания, индексирани в Scopus или Web of Science
26. Saikia, A., Kakoty, N. M., Phukan, N., Balakrishnan, M., Sahai, N., Paul, S., & Bhatia, D. (2018). Combination of EMG features and stability index for finger movements recognition. Procedia computer science, 133, 92-98. - 2018 - в издания, индексирани в Scopus или Web of Science
27. Anam, Khairul, Dwiretno Istiyadi Swasono, Aris Zainul Muttaqin, and Faruq Sandi Hanggara. "Finger Movement Regression with Myoelectric Signal and Deep Neural Network." In 2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE), pp. 187-191. IEEE, 2019. - 2019 - в издания, индексирани в Scopus или Web of Science
28. İŞcan, Mehmet, Caner Emeç, and Aydin YeŞİldİrek. "Hand gesture movement classification based on dynamically structured neural network." In 2018 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT), pp. 1-4. IEEE, 2018. - 2018 - в издания, индексирани в Scopus или Web of Science
29. Purushothaman, Geethanjali. "Bio-Inspired Techniques in Rehabilitation Engineering for Control of Assistive Devices." In Computer Vision: Concepts, Methodologies, Tools, and Applications, pp. 2065-2082. IGI Global, 2018. - 2018 - в издания, индексирани в Scopus или Web of Science
30. Zhang, Ruide. "Hardware-Aided Privacy Protection and Cyber Defense for IoT." PhD diss., Virginia Tech, 2020. - 2020 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
31. Vu, Philip. "Restoring Fine Motor Prosthetic Hand Control via Peripheral Neural Technology." PhD diss., 2019. - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
32. Cheng, Wei. "Electromyography (EMG) Based Finger Movement Detection." PhD diss., 2020. - 2020 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
33. Lim, Evon Wan Ting. "Optimized Approach on EMG Signal Classification." PhD diss., Swinburne University of Technology, 2020. - 2020 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
34. Hosseini, Seyedeh Marzieh. "Tremor Suppression in the Human Hand and Forearm." PhD diss., 2019. - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
35. Ibrahim, Marwa Farouk Ibrahim. "Advanced deep learning approaches for biosingnals applications." PhD diss., 2019. - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
36. Reis, Ana Cláudia Fernandes dos. "Extraction of sign language information through biosignals." PhD diss., Universidade de Coimbra, 2017. - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
37. Geethanjali, P. "Bio-Inspired Techniques in Human-Computer Interface for Control of Assistive Devices: Bio-Inspired Techniques in Assistive Devices." In HCI Challenges and Privacy Preservation in Big Data Security, pp. 23-46. IGI Global, 2018. - 2018 - в издания, индексирани в Scopus или Web of Science
38. 伊東和輝, and 田村仁. "不特定多数対象に対応可能な sEMG によるハンドジェスチャの識別手法." In IEICE Conferences Archives. The Institute of Electronics, Information and Communication Engineers, 2019. - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
39. Khushaba, Rami N., Sarath Kodagoda, Maen Takruri, and Gamini Dissanayake. "Toward improved control of prosthetic fingers using surface electromyogram (EMG) signals." Expert Systems with Applications 39, no. 12 (2012): 10731-10738. - 2012 - в издания, индексирани в Scopus или Web of Science
40. Ahsan, Md Rezwanul, Muhammad I. Ibrahimy, and Othman O. Khalifa. "EMG signal classification for human computer interaction: a review." European Journal of Scientific Research 33, no. 3 (2009): 480-501. - 2009 - в издания, индексирани в Scopus или Web of Science
41. Geethanjali, Purushothaman. "Myoelectric control of prosthetic hands: state-of-the-art review." Medical Devices (Auckland, NZ) 9 (2016): 247. - 2016 - в издания, индексирани в Scopus или Web of Science
42. Roche, Aidan D., Hubertus Rehbaum, Dario Farina, and Oskar C. Aszmann. "Prosthetic myoelectric control strategies: a clinical perspective." Current Surgery Reports 2, no. 3 (2014): 1-11. - 2014 - в издания, индексирани в Scopus или Web of Science
43. Ahsan, Md Rezwanul, Muhammad Ibn Ibrahimy, and Othman O. Khalifa. "Electromygraphy (EMG) signal based hand gesture recognition using artificial neural network (ANN)." In 2011 4th international conference on mechatronics (ICOM), pp. 1-6. IEEE, 2011. - 2011 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
44. Chen, Xun, and Z. Jane Wang. "Pattern recognition of number gestures based on a wireless surface EMG system." Biomedical Signal Processing and Control 8, no. 2 (2013): 184-192. - 2013 - в издания, индексирани в Scopus или Web of Science
45. Rossi, Matteo, Simone Benatti, Elisabetta Farella, and Luca Benini. "Hybrid EMG classifier based on HMM and SVM for hand gesture recognition in prosthetics." In 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 1700-1705. IEEE, 2015. - 2015 - в издания, индексирани в Scopus или Web of Science
46. Khushaba, Rami N., and Sarath Kodagoda. "Electromyogram (EMG) feature reduction using mutual components analysis for multifunction prosthetic fingers control." In 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV), pp. 1534-1539. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
47. Ahsan, M. D. R., Muhammad I. Ibrahimy, and Othman O. Khalifa. "Advances in electromyogram signal classification to improve the quality of life for the disabled and aged people." Journal of Computer Science 6, no. 7 (2010): 706. - 2010 - в издания, индексирани в Scopus или Web of Science
48. Kolodner, E.K., Tal, S., Kyriazis, D., Naor, D., Allalouf, M., Bonelli, L., Brand, P., Eckert, A., Elmroth, E., Gogouvitis, S.V. and Harnik, D., 2011, November. A cloud environment for data-intensive storage services. In 2011 IEEE third international conference on cloud computing technology and science (pp. 357-366). IEEE. - 2011 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
49. Ibrahimy, M. Ibn, Md Rezwanul Ahsan, and Othman Omran Khalifa. "Design and optimization of Levenberg-Marquardt based neural network classifier for EMG signals to identify hand motions." Measurement Science Review 13, no. 3 (2013): 142-151. - 2013 - в издания, индексирани в Scopus или Web of Science
50. Khushaba, Rami N., Sarath Kodagoda, Diaki Liu, and Gamini Dissanayake. "Muscle computer interfaces for driver distraction reduction." Computer methods and programs in biomedicine 110, no. 2 (2013): 137-149. - 2013 - в издания, индексирани в Scopus или Web of Science
51. Andrews, Alex, Evelyn Morin, and Linda McLean. "Optimal electrode configurations for finger movement classification using EMG." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2987-2990. IEEE, 2009. - 2009 - в издания, индексирани в Scopus или Web of Science
52. Anam, Khairul, and Adel Al-Jumaily. "Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees." Neural Networks 85 (2017): 51-68. - 2017 - в издания, индексирани в Scopus или Web of Science
53. Sahin, Ugur, and Ferat Sahin. "Pattern recognition with surface EMG signal based wavelet transformation." In 2012 IEEE international conference on systems, man, and cybernetics (SMC), pp. 295-300. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
54. Ahsan, Md R., Muhammad I. Ibrahimy, and Othman O. Khalifa. "Hand motion detection from EMG signals by using ANN based classifier for human computer interaction." In 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization, pp. 1-6. IEEE, 2011. - 2011 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
55. Vu, Philip P., Zachary T. Irwin, Autumn J. Bullard, Shoshana W. Ambani, Ian C. Sando, Melanie G. Urbanchek, Paul S. Cederna, and Cynthia A. Chestek. "Closed-loop continuous hand control via chronic recording of regenerative peripheral nerve interfaces." IEEE Transactions on Neural Systems and Rehabilitation Engineering 26, no. 2 (2017): 515-526. - 2017 - в издания, индексирани в Scopus или Web of Science
56. Ahsan, Md R., M. I. Ibrahimy, and O. O. Khalifa. "Neural network classifier for hand motion detection from EMG signal." In 5th Kuala Lumpur International Conference on Biomedical Engineering 2011, pp. 536-541. Springer, Berlin, Heidelberg, 2011. - 2011 - в издания, индексирани в Scopus или Web of Science
57. Anam, Khairul, Rami N. Khushaba, and Adel Al-Jumaily. "Two-channel surface electromyography for individual and combined finger movements." In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4961-4964. IEEE, 2013. - 2013 - в издания, индексирани в Scopus или Web of Science
58. Naik, Ganesh R., Kerry G. Baker, and Hung T. Nguyen. "Dependence independence measure for posterior and anterior EMG sensors used in simple and complex finger flexion movements: Evaluation using SDICA." IEEE journal of biomedical and health informatics 19, no. 5 (2014): 1689-1696. - 2014 - в издания, индексирани в Scopus или Web of Science
59. Khushaba, Rami N., Sarath Kodagoda, Dikai Liu, and Gamini Dissanayake. "Electromyogram (EMG) based fingers movement recognition using neighborhood preserving analysis with QR-decomposition." In 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 1-105. IEEE, 2011. - 2011 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
60. Chowdhury, Anirban, Rithvik Ramadas, and Sougata Karmakar. "Muscle computer interface: A review." ICoRD'13 (2013): 411-421. - 2013 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
61. Ahsan, Md Rezwanul, Muhammad Ibn Ibrahimy, and Othman Omran Khalifa. "EMG motion pattern classification through design and optimization of neural network." In 2012 International Conference on Biomedical Engineering (ICoBE), pp. 175-179. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
62. Veer, Karan. "Experimental study and characterization of SEMG signals for upper limbs." Fluctuation and Noise Letters 14, no. 03 (2015): 1550028. - 2015 - в издания, индексирани в Scopus или Web of Science
63. Andrews, A. L. E. X. A. N. D. E. R., Evelyn Morin, and Linda McLean. "Finger movement classification using forearm EMG signals." (2008). - 2008 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
64. Ahsan, Md R., Muhammad I. Ibrahimy, and Othman O. Khalifa. "The use of artificial neural network in the classification of emg signals." In 2012 Third FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing, pp. 225-229. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
65. Ju, Zhaojie, Xiangyang Zhu, and Honghai Liu. "Empirical copula-based templates to recognize surface EMG signals of hand motions." International Journal of Humanoid Robotics 8, no. 04 (2011): 725-741. - 2011 - в издания, индексирани в Scopus или Web of Science
66. Baker, Justin J., Dimitri Yatsenko, Jack F. Schorsch, Glenn A. DeMichele, Phil R. Troyk, Douglas T. Hutchinson, Gregory Clark, and Bradley Greger. "Decoding individuated finger flexions with implantable myoelectric sensors." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 193-196. IEEE, 2008. - 2008 - в издания, индексирани в Scopus или Web of Science
67. Kondo, Genta, Ryu Kato, Hiroshi Yokoi, and Tamio Arai. "Classification of individual finger motions hybridizing electromyogram in transient and converged states." In 2010 IEEE International Conference on Robotics and Automation, pp. 2909-2915. IEEE, 2010. - 2010 - в издания, индексирани в Scopus или Web of Science
68. Valentini, Riccardo, Stefano Michieletto, Fabiola Spolaor, Zimi Sawacha, and Enrico Pagello. "Processing of semg signals for online motion of a single robot joint through gmm modelization." In 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 943-949. IEEE, 2015. - 2015 - в издания, индексирани в Scopus или Web of Science
69. Ketenci̇, Seniha, Temel Kayikçioğlu, and Ali Gangal. "Recognition of sign language numbers via electromyography signals." In 2015 23nd Signal Processing and Communications Applications Conference (SIU), pp. 2593-2596. IEEE, 2015. - 2015 - в издания, индексирани в Scopus или Web of Science
70. Hartwell, Adam, Visakan Kadirkamanathan, and Sean Anderson. "Person-specific gesture set selection for optimised movement classification from EMG signals." In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 880-883. IEEE, 2016. - 2016 - в издания, индексирани в Scopus или Web of Science
71. Castiblanco, Carolina, Carlos Parra, and Julian Colorado. "Individual hand motion classification through EMG pattern recognition: Supervise and unsupervised methods." In 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), pp. 1-6. IEEE, 2016. - 2016 - в издания, индексирани в Scopus или Web of Science
72. Ali, Ali Hussian. "An investigation of Electromyographic (EMG) Control of Dextrous Hand Prostheses for Transradial Amputees." (2013). - 2013 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
73. Zhang, Ruide, Ning Zhang, Changlai Du, Wenjing Lou, Y. Thomas Hou, and Yuichi Kawamoto. "AugAuth: Shoulder-surfing resistant authentication for augmented reality." In 2017 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE, 2017. - 2017 - в издания, индексирани в Scopus или Web of Science
74. Alam, Raquib-ul, Shams Rashid Rhivu, and M. A. Haque. "Improved gesture recognition using deep neural networks on sEMG." In 2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST), pp. 1-4. IEEE, 2018. - 2018 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
75. Villarejo, John J., Regina M. Costa, Teodiano Bastos, and Anselmo Frizera. "Identification of low level sEMG signals for individual finger prosthesis." In 5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), pp. 1-6. IEEE, 2014. - 2014 - в издания, индексирани в Scopus или Web of Science
76. Tan, Shiying, Yueying An, Yulun Wu, and Dingguo Zhang. "Electromyography based handwriting recognition system using LM-BP Neural Network." In 2016 9th International Conference on Human System Interactions (HSI), pp. 83-88. IEEE, 2016. - 2016 - в издания, индексирани в Scopus или Web of Science
77. Ozsert, M., O. Yavuz, and L. Durak-Ata. "Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms." Computer methods in biomechanics and biomedical engineering 14, no. 06 (2011): 521-525. - 2011 - в издания, индексирани в Scopus или Web of Science
78. Chen, Yumiao, Zhongliang Yang, Hugh Gong, and Shengze Wang. "Recognition of sketching from surface electromyography." Neural Computing and Applications 30, no. 9 (2018): 2725-2737. - 2018 - в издания, индексирани в Scopus или Web of Science
79. Ding, Qichuan, Ziyou Li, Xingang Zhao, Yongfei Xiao, and Jianda Han. "Real-time myoelectric prosthetic-hand control to reject outlier motion interference using one-class classifier." In 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC), pp. 96-101. IEEE, 2017. - 2017 - в издания, индексирани в Scopus или Web of Science
80. Shuman, Gene, Zoran Durić, Daniel Barbará, Jessica Lin, and Lynn H. Gerber. "Improving the recognition of grips and movements of the hand using myoelectric signals." BMC medical informatics and decision making 16, no. 2 (2016): 65-83. - 2016 - в издания, индексирани в Scopus или Web of Science
81. Anam, Khairul, and Adel Al-Jumaily. "Real-time classification of finger movements using two-channel surface Electromyography." In NEUROTECHNIX 2013-Proceedings of the International Congress on Neurotechnology, Electronics and Informatics. 2013. - 2013 - в издания, индексирани в Scopus или Web of Science
82. Ahsan, Md Rezwanul, Muhammad Ibn Ibrahimy, and Othman Omran Khalifa. "Optimization of neural network for efficient EMG signal classification." In 2012 8th International Symposium on Mechatronics and its Applications, pp. 1-6. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
83. Uvanesh, K. "Linear and non-linear classification of EMG signals for probable applications in designing control system for assistive aids." PhD diss., 2015. - 2015 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
84. Tsujiuchi, Nobutaka, Haruaki Mizuno, Takayuki Koizumi, and Shinya Yamada. "7-Motion discrimination technique for forearms using real-time EMG signals." In 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 441-445. IEEE, 2012. - 2012 - в издания, индексирани в Scopus или Web of Science
85. Shuman, Gene, Zoran Durić, Daniel Barbará, Jessica Lin, and Lynn H. Gerber. "Using myoelectric signals to recognize grips and movements of the hand." In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 388-394. IEEE, 2015. - 2015 - в издания, индексирани в Scopus или Web of Science
86. Veer, Karan, Tanu Sharma, and Ravinder Agarwal. "A neural network-based electromyography motion classifier for upper limb activities." Journal of Innovative Optical Health Sciences 9, no. 06 (2016): 1650025. - 2016 - в издания, индексирани в Scopus или Web of Science
87. Zhang, Ruide, Ning Zhang, Changlai Du, Wenjing Lou, Y. Thomas Hou, and Yuichi Kawamoto. "From electromyogram to password: exploring the privacy impact of wearables in augmented reality." ACM Transactions on Intelligent Systems and Technology (TIST) 9, no. 1 (2017): 1-20. - 2017 - в издания, индексирани в Scopus или Web of Science
88. Kolasa, Marta, Rafał Długosz, and Jolanta Pauk. "A comparative study of different neighborhood topologies in WTM Kohonen self-organizing maps." In Solid State Phenomena, vol. 147, pp. 564-569. Trans Tech Publications Ltd, 2009. - 2009 - в издания, индексирани в Scopus или Web of Science
89. Heydarzadeh, Mehrdad, Javad Birjandtalab, and Mehrdad Nourani. "EMG Spectral Analysis for Prosthetic Finger Control." In 2017 European Conference on Electrical Engineering and Computer Science (EECS), pp. 131-135. IEEE, 2017. - 2017 - в издания, индексирани в Scopus или Web of Science
90. Hosen, Md Rubel, Sabbir Hasan, Md Mehedi Hasan, and Rupak Kumar Das. "Age classification based on EMG signal using Artificial Neural Network." In 2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), pp. 1-5. IEEE, 2015. - 2015 - в издания, индексирани в Scopus или Web of Science
91. Geethanjali, P. "Pattern recognition and robotics." Advances in Secure Computing, Internet Services, and Applications (2014): 35-48. - 2014 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
92. Maheu, Véronique. "Développement des critères d'apprentissage pour le contrôle d'un bras robot manipulateur à 7 DDL par le traitement des signaux EMG chez les blessés médullaires." PhD diss., École de technologie supérieure, 2011. - 2011 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
93. Mayor, John J. Villarejo, Regina Mamede Costa, Anselmo Frizera Neto, and Teodiano Freire Bastos. "Decodificación de Movimientos Individuales de los Dedos y Agarre a Partir de Señales Mioeléctricas de Baja Densidad." Revista Iberoamericana de Automática e Informática industrial 14, no. 2 (2017): 184-192. - 2017 - в издания, индексирани в Scopus или Web of Science
94. "Using biosignals to control the Nao robot." PhD diss., éditeur non identifié, 2013. - 2013 - в издания, индексирани в Scopus или Web of Science
95. Azadbakht, Bakhtiar, Hamidreza Zolata, and Omid Khayat. "An intelligent electromyogram signal characterization method based on neuro-fuzzy model." Journal of Intelligent & Fuzzy Systems 27, no. 5 (2014): 2623-2634. - 2014 - в издания, индексирани в Scopus или Web of Science
96. Villarejo, J., R. Mamede, and T. Bastos. "Movement Identification using weak sEMG signals of low density for upper limb control." Andrade, A., Barbosa, A., Cardoso, A., Lamounier, E. Tecnologias, técnicas e tendências em engenharia biomédica. Canal6 Edi (2014): 280-300. - 2014 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
97. Anam, Khairul. "Bio-driven control system for the rehabilitation hand device: a new approach." PhD diss., 2016. - 2016 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
98. Mayor, J. V., A. F. Rodacki, and T. Bastos. "Classification of dexterous hand movements based on myoelectric signals using neural networks." Anais COBEC-SEB (2007): 302-305. - 2007 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
99. Rzyman, Gustaw, Grzegorz Redlarski, and Marek Krawczuk. "Komputerowo wspomagana klasyfikacja wybranych sygnałów elektromiografii powierzchniowej." Modelowanie Inżynierskie 31 (2017). - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
100. Mayor, John Jairo Villarejo. "Muscle-Computer Interface Based on Pattern Recognition of Myoelectric Signals for Control of Dexterous Hand and Finger Movements of Prostheses for Forearm Amputees." - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
101. Gunjan, Vinit Kumar. "Bita Mokhlesabadifarahani." - 2015 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
102. Maps, Kohonen Self-Organizing. "A Comparative Study of Different Neighborhood Topologies in WTM." (2009). - 2009 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
103. Chen, Xun. "Multimodal biomedical signal processing for corticomuscular coupling analysis." PhD diss., University of British Columbia, 2014. - 2014 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
104. Abbas, Ahmed Majid Abdel, and Muayad Sadik Croock. "Efficient Control System Based on Hand Nerve Signals." (2017). - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
105. Goen, A., and D. C. Tiwari. "Pattern Recognition of Finger Movements of Two Channel based Surface EMG Signals." Journal of Image Processing & Pattern Recognition Progress 3, no. 1 (2016): 7-14. - 2016 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
106. Patil, Reena. "Human Machine Interfaces Using Multichannel Physiological Signals." PhD diss., San Diego State University, 2017. - 2017 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
107. Ju, Zhaojie, and Honghai Liu. "Empirical Copula driven hand motion recognition via surface electromyography based templates." In International Conference on Intelligent Robotics and Applications, pp. 71-80. Springer, Berlin, Heidelberg, 2010. - 2010 - в издания, индексирани в Scopus или Web of Science
108. Shuman, Gene R. "Using myoelectric signals to classify prehensile patterns." PhD diss., George Mason University, 2016. - 2016 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
109. Goen, Anjana, and D. C. Tiwari. "Pattern Recognition of Individual and Combined Fingers Movements Based Prosthesis Control Using Surface EMG Signals." Pattern Recognition 3, no. 4 (2015): 70-78. - 2015 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
110. Lumbier Álvarez, Alejandro. "Métodos de visión artificial para la extracción de la pose de la mano humana y su representación virtual." (2016). - 2016 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
111. Araujo, Guilherme Cancian de. "Estudo de um classificador do tipo Máquina de Vetores de suporte para a classificação de Sinais Miolétricos provenientes do antebraço." (2017). - 2017 - в издания, индексирани в Scopus или Web of Science
112. 伊東和輝, and 田村仁. "不特定多数対象に対応可能な sEMG によるハンドジェスチャの識別手法." In IEICE Conferences Archives. The Institute of Electronics, Information and Communication Engineers, 2019. - 2019 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
113. 12. Chan, B., Saad, I., Bolong, N. and Siew, K.E., 2021, September. Preliminary Design of Portable Electromyography (EMG) System for Clinical Signal Acquisition. In 2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) (pp. 1-5). IEEE. - 2021 - в издания, индексирани в Scopus или Web of Science
114. McDermott, E.J., Zwiener, T., Ziemann, U. and Zrenner, C., 2021. Real-time decoding of 5 finger movements from 2 EMG channels for mixed reality human-computer interaction. bioRxiv. - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
115. Chan, B., Saad, I., Bolong, N. and Kang, E.S., 2021. Design of Portable Electromyography (EMG) System for Clinical Rehabilitation. Transactions on Science and Technology, 8(3-3), pp.519-526. - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
116. 547) Budiarsa, A.P.B., Leu, J.S., Yuen, K.K.F. and Sigalingging, X., 2022. Improved swarm-wavelet based extreme learning machine for myoelectric pattern recognition. Biomedical Signal Processing and Control, 77, p.103737. (Google Scholar) - 2022 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
117. 548) Aljobouri, H.K., 2022. A Virtual EMG Signal Control and Analysis for Optimal Hardware Design. International Journal of Online & Biomedical Engineering, 18(2). (Google Scholar, Scopus, Web of Science) - 2022 - в издания, индексирани в Scopus или Web of Science
118. 550) Hristov, B. and Nadzinski, G., Detection of individual finger flexions using two-channel electromyography, 2021. (Google Scholar) - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
119. 551) BHAGWAT, S. and MUKHERJI, P., Temporal Feature Extraction for Electromyogram (EMG) based Fingers Movement Recognition, 2021. (Google Scholar) - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
120. 552) Chen, X., Liu, A. and Wang, Z.J., Recognition of Chinese Number Gestures Based on A Wireless Surface EMG Recording System, 2021. (Google Scholar) - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
121. 553) Zhang, R., Zhang, N., Du, C., Lou, W., Hou, Y.T. and Kawamoto, Y., CCS Concepts: rSecurity and privacy→ Side-channel analysis and countermeasures; Access control, 2021. (Google Scholar) - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
122. 556) Jia, G., Deep Learning Frameworks with Applications in Medical Signal and Image Classification, 2021. (Google Scholar) - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
123. 655) Teke B., V. Ahmadipour E., Performance Comparison Of Multilayer Perceptron And Radial Basis Function Artificial Neural Networks For Classification Of Hand Motions, 2018 (Google Scholar) - 2018 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
124. Hristov, B., Nadzinski, G., Latkoska, V.O. and Zlatinov, S., 2022, June. “Classification of Individual and Combined Finger Flexions Using Machine Learning Approaches,” In 2022 IEEE 17th International Conference on Control & Automation (ICCA), vol. 2022, (pp. 986-991)., ISBN 978-166549572-1, DOI 10.1109/ICCA54724.2022.9831952 IEEE. (Scopus, Google Scholar) - 2022 - в издания, индексирани в Scopus или Web of Science
125. Akmal, M., Zubair, S., Jochumsen, M., Nlandu Kamavuako, E., Irfan Abid, M. and Niazi, I.K., 2022. Scalable tensor factorization for recovering multiday missing intramuscular electromyography data. Journal of Intelligent & Fuzzy Systems, vol. 43, issue 1, pp.1-11. (Web of Science, Google Scholar), IF 1.737, SJR 0.386 - 2022 - в издания, индексирани в Scopus или Web of Science
126. Ting, E.L.W., Chai, A. and Chin, L.P., 2022. A Review on EMG Signal Classification and Applications. International Journal of Signal Processing Systems, vol. 10, issue (1), pp.1-6. doi: 10.18178/ijsps.10.1.1-6 (Google Scholar) - 2022 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
127. A. M. Elbreki, S. Ramdan, F. Mohamed, K. Alshari, Z. Rajab and B. Elhub, "Practical Design of an Upper Prosthetic Limb Using Three Dimensional Printer with an Artificial Intelligence Based Controller," 2022 International Conference on Engineering & MIS (ICEMIS), 2022, pp. 1-6, doi: 10.1109/ICEMIS56295.2022.9914291. (Scopus, Google Scholar) - 2022 - в издания, индексирани в Scopus или Web of Science
128. Asheghabadi, A.S., Moqadam, S.B. and Xu, J., 2022, July. Classification of Individual Finger Motions Using Single-Site Mechanomyography by Optimized Long Short-Time Memory. In 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) (pp. 585-590). DOI: 10.1109/CYBER55403.2022.9907715 IEEE. (Scopus, Google Scholar) - 2022 - в издания, индексирани в Scopus или Web of Science
129. Шабалдас, В.І., 2023. Конструкція автоматизованої системи протезу руки (Bachelor's thesis, КПІ ім. Ігоря Сікорського). (Google Scholar) - 2023 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
130. Nieuwoudt, L. and Fisher, C., 2023. Investigation of Real-Time Control of Finger Movements Utilising Surface EMG Signals. IEEE Sensors Journal. ISSN 1530437X, DOI 10.1109/JSEN.2023.3299384, pp. 21989 - 21997 (Web of Science, Scopus, Google Scholar) SJR 0.987, IF 4.3 - 2023 - в издания, индексирани в Scopus или Web of Science
131. L. Nieuwoudt and C. Fisher, "Investigation of Real-Time Control of Finger Movements Utilizing Surface EMG Signals," in IEEE Sensors Journal, vol. 23, no. 18, pp. 21989-21997, 15 Sept.15, 2023, ISSN 1530437Xdoi: 10.1109/JSEN.2023.3299384. (Web of Science, Scopus, Google Scholar) SJR 0.987, IF 4.3 - 2023 - в издания, индексирани в Scopus или Web of Science
132. Nieuwoudt, L., 2023. Exploring EMG and EEG Signals for the Development of a Real-Time Control Strategy for a Robotic Hand. Thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering (Electronic) in the Faculty of Engineering at Stellenbosch University, pp. 1-126, (Google Scholar) - 2023 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
133. Hristov, B., Nair, A., Rafajlovski, G., Latkoska, V.O. and Nadžinski, G., 2023. 212. MECHANICAL DESIGN OF A LOW-COST 3D PRINTED ARTIFICIAL FOREARM PROSTHESIS WITH THE ABILITY FOR INDIVIDUAL FINGER CONTROL. Journal of Electrical Engineering and Information Technologies, vol. 8, No 2, pp.109-116. DOI: https://doi.org/10.51466/JEEIT23821, ISSN 2545–4250 (Google Scholar) - 2023 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science
134. X. Molina-Padilla, S. Martinez-Fuerte, E. R. Hernandez-Rios and C. Peñaloza, "Electromyography Acquisition System Via Conductive Fabric For Wearable Skill Transfer Device Focused On Drum-Oriented Activities," 2024 IEEE/SICE International Symposium on System Integration (SII), Ha Long, Vietnam, 2024, pp. 190-195, doi: 10.1109/SII58957.2024.10417562. (Scopus, Google Scholar) - 2024 - в издания, индексирани в Scopus или Web of Science
135. Siani, E. G., Scigliano, L., Bruneo, D., De Vita, F., Tomaselli, V., & Pau, D. (2024, June). “A Numerical Comparison of Deeply Quantized Models for sEMG Hand Gesture Classification on Constrained Devices,” In 2024 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 374-379). IEEE. ISBN 979-835034994-8, DOI 10.1109/SMARTCOMP61445.2024.00084 (Scopus, Google Scholar) - 2024 - в издания, индексирани в Scopus или Web of Science

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