The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Feature reduction and selection for EMG signal classification
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Citations
Cites
A new strategy for multifunction myoelectric control
Hudgins, B., Parker, P., & Scott, R. N. (1993) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.204774 · Cited by 2,149
Myoelectric control systems—A survey
Asghari Oskoei, M., & Hu, H. (2007) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2007.07.009 · Cited by 1,244
Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb
Oskoei, M. A., & Hu, H. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.919734 · Cited by 829
A wavelet-based continuous classification scheme for multifunction myoelectric control
Englehart, K., Hudgin, B., & Parker, P. A. (2001) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.914793 · Cited by 697
Standards for Reporting EMG Data*
(2000) · Measurement of Human Locomotion · doi:10.1201/9781420036985.ax2 · Cited by 626
Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal
Zecca, M., Micera, S., Carrozza, M. C., & Dario, P. (2002) · Critical Reviews? in Biomedical Engineering · doi:10.1615/critrevbiomedeng.v30.i456.80 · Cited by 606
Study of stability of time-domain features for electromyographic pattern recognition
Tkach, D., Huang, H., & Kuiken, T. A. (2010) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-7-21 · Cited by 582
Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal
Zecca, M., Micera, S., Carrozza, M. C., & Dario, P. (2017) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.v45.i1-6.150 · Cited by 570
EMG feature evaluation for movement control of upper extremity prostheses
Zardoshti-Kermani, M., Wheeler, B. C., Badie, K., & Hashemi, R. M. (1995) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.481972 · Cited by 477
Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses
Li, G., Schultz, A. E., & Kuiken, T. A. (2010) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2039619 · Cited by 443
Research works printed but not linked: 6
- Du, S. (2003). Feature extraction for classification of prehensile electromyography patterns. Master’s Thesis, San Diego State University, San Diego, CA, US.
- Du, 2010, Portable hand motion classifier for multi-channel surface electromyography recognition using grey relational analysis, Expert Systems with Applications, 37, 4283, 10.1016/j.eswa.2009.11.072 · doi:10.1016/j.eswa.2009.11.072
- Miller, C.J. (2008). Real-time feature extraction and classification of prehensile EMG signals. Master’s Thesis, San Diego State University, San Diego, CA, US.
- Pandey, 2009, An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases, Expert Systems with Applications, 36, 9201, 10.1016/j.eswa.2008.12.023 · doi:10.1016/j.eswa.2008.12.023
- Philipson, L. (1987). The electromyographic signal used for control of upper extremity prostheses and for quantification of motor blockade during epidural anaesthesia. Ph.D. Thesis, Linköping University, Linköping, Sweden.
- Phinyomark, A., Limsakul, C., & Phukpattaranont, P. (2009b). EMG feature extraction for tolerance of 50Hz interference. In Proceedings of 4th PSU-UNS International Conference on Engineering Technologies (pp. 289–293).
Cited by
Bi, L., Feleke, A. >., & Guan, C. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.02.011 · Cited by 418
Surface EMG-Based Inter-Session Gesture Recognition Enhanced by Deep Domain Adaptation
Du, Y., Jin, W., Wei, W., Hu, Y., & Geng, W. (2017) · Sensors · doi:10.3390/s17030458 · Cited by 363
EMG Pattern Recognition in the Era of Big Data and Deep Learning
Phinyomark, A., & Scheme, E. (2018) · Big Data and Cognitive Computing · doi:10.3390/bdcc2030021 · Cited by 272
Self-citationSamuel, O. W., Asogbon, M. G., Geng, Y., Al-Timemy, A. H., Pirbhulal, S., Ji, N., Chen, S., Fang, P., & Li, G. (2019) · IEEE Access · doi:10.1109/access.2019.2891350 · Cited by 185
Real-Time Surface EMG Pattern Recognition for Hand Gestures Based on an Artificial Neural Network
Zhang, Z., Yang, K., Qian, J., & Zhang, L. (2019) · Sensors · doi:10.3390/s19143170 · Cited by 165
Metadata
- Authors
- Phinyomark, A., Phukpattaranont, P., & Limsakul, C.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2012-06
- Volume
- 39
- Issue
- 8
- Pages
- 7420-7431
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2044628302
- Cited by
- 1,542
- References
- 35
- FWCI
- 20.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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- Phinyomark, A., Phukpattaranont, P., & Limsakul, C. (2012). Feature reduction and selection for EMG signal classification. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2012.01.102
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
