333 related articles for article (PubMed ID: 25571959)
1. A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.
Xie HB; Huang H; Wu J; Liu L
Physiol Meas; 2015 Feb; 36(2):191-206. PubMed ID: 25571959
[TBL] [Abstract][Full Text] [Related]
2. Fuzzy support vector machine for classification of EEG signals using wavelet-based features.
Xu Q; Zhou H; Wang Y; Huang J
Med Eng Phys; 2009 Sep; 31(7):858-65. PubMed ID: 19487151
[TBL] [Abstract][Full Text] [Related]
3. Medical decision support system for diagnosis of neuromuscular disorders using DWT and fuzzy support vector machines.
Subasi A
Comput Biol Med; 2012 Aug; 42(8):806-15. PubMed ID: 22763356
[TBL] [Abstract][Full Text] [Related]
4. Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.
Zhang Y; Zhang X; Liu W; Luo Y; Yu E; Zou K; Liu X
J Healthc Eng; 2014; 5(4):505-20. PubMed ID: 25516130
[TBL] [Abstract][Full Text] [Related]
5. Robust support vector machine-trained fuzzy system.
Forghani Y; Yazdi HS
Neural Netw; 2014 Feb; 50():154-65. PubMed ID: 24316676
[TBL] [Abstract][Full Text] [Related]
6. [Pattern recognition of surface electromyography signal based on multi-scale fuzzy entropy].
Zou X; Lei M
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2012 Dec; 29(6):1184-8. PubMed ID: 23469553
[TBL] [Abstract][Full Text] [Related]
7. Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders.
Subasi A
Comput Biol Med; 2013 Jun; 43(5):576-86. PubMed ID: 23453053
[TBL] [Abstract][Full Text] [Related]
8. A machine learning approach to identify hand actions from single-channel sEMG signals.
Savithri CN; Priya E; Rajasekar K
Biomed Tech (Berl); 2022 Apr; 67(2):89-103. PubMed ID: 35191277
[TBL] [Abstract][Full Text] [Related]
9. Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees.
Anam K; Al-Jumaily A
Neural Netw; 2017 Jan; 85():51-68. PubMed ID: 27814466
[TBL] [Abstract][Full Text] [Related]
10. Physical activities recognition from ambulatory ECG signals using neuro-fuzzy classifiers and support vector machines.
Kher R; Pawar T; Thakar V; Shah H
J Med Eng Technol; 2015 Feb; 39(2):138-52. PubMed ID: 25641014
[TBL] [Abstract][Full Text] [Related]
11. A two-dimensional matrix image based feature extraction method for classification of sEMG: A comparative analysis based on SVM, KNN and RBF-NN.
Wen T; Zhang Z; Qiu M; Zeng M; Luo W
J Xray Sci Technol; 2017; 25(2):287-300. PubMed ID: 28269818
[TBL] [Abstract][Full Text] [Related]
12. Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement.
Guo S; Pang M; Gao B; Hirata H; Ishihara H
Sensors (Basel); 2015 Apr; 15(4):9022-38. PubMed ID: 25894941
[TBL] [Abstract][Full Text] [Related]
13. Fuzzy support vector machine with joint optimization of genetic algorithm and fuzzy c-means.
Li MA; Wang RT; Wei LN
Technol Health Care; 2021; 29(5):921-937. PubMed ID: 33459673
[TBL] [Abstract][Full Text] [Related]
14. The relevance sample-feature machine: a sparse Bayesian learning approach to joint feature-sample selection.
Mohsenzadeh Y; Sheikhzadeh H; Reza AM; Bathaee N; Kalayeh MM
IEEE Trans Cybern; 2013 Dec; 43(6):2241-54. PubMed ID: 23782842
[TBL] [Abstract][Full Text] [Related]
15. An approach to estimating product design time based on fuzzy v-support vector machine.
Yan HS; Xu D
IEEE Trans Neural Netw; 2007 May; 18(3):721-31. PubMed ID: 17526339
[TBL] [Abstract][Full Text] [Related]
16. Joint application of rough set-based feature reduction and Fuzzy LS-SVM classifier in motion classification.
Yan Z; Wang Z; Xie H
Med Biol Eng Comput; 2008 Jun; 46(6):519-27. PubMed ID: 18087744
[TBL] [Abstract][Full Text] [Related]
17. Ant colony optimization-based feature selection method for surface electromyography signals classification.
Huang H; Xie HB; Guo JY; Chen HJ
Comput Biol Med; 2012 Jan; 42(1):30-8. PubMed ID: 22074763
[TBL] [Abstract][Full Text] [Related]
18. Multiclass cancer classification by using fuzzy support vector machine and binary decision tree with gene selection.
Mao Y; Zhou X; Pi D; Sun Y; Wong ST
J Biomed Biotechnol; 2005 Jun; 2005(2):160-71. PubMed ID: 16046822
[TBL] [Abstract][Full Text] [Related]
19. NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation.
Dellacasa Bellingegni A; Gruppioni E; Colazzo G; Davalli A; Sacchetti R; Guglielmelli E; Zollo L
J Neuroeng Rehabil; 2017 Aug; 14(1):82. PubMed ID: 28807038
[TBL] [Abstract][Full Text] [Related]
20. A novel fuzzy approach for automatic Brunnstrom stage classification using surface electromyography.
Liparulo L; Zhang Z; Panella M; Gu X; Fang Q
Med Biol Eng Comput; 2017 Aug; 55(8):1367-1378. PubMed ID: 27909939
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
