000			02681nam a22003855i 4500
999			_c103363 _d103363 _x1
001			103363
003			DE-He213
005			20230102113127.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			150210s2015 si | s |||| 0|eng d
020			_a9789812873200
024	7		_a10.1007/978-981-287-320-0 _2doi
040			_bspa _dES-MaUEC
050		4	_aTK5102.9 _b2015 EB
100	1		_aMokhlesabadifarahani, Bita. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aEMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction _cby Bita Mokhlesabadifarahani, Vinit Kumar Gunjan.
264		1	_aSingapore _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XV, 35 páginas 17 ilustraciones, 13 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aSpringerBriefs in Forensic and Medical Bioinformatics, _x2196-8845
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction to EMG Technique and Feature Extraction -- Methodology for  working with EMG dataset -- Results -- Conclusions and Inferences of Present Study.
520	3		_aNeuro-muscular and musculoskeletal disorders and injuries highly affect the life style and the motion abilities of an individual. This brief highlights a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. The neuro-fuzzy system is trained with 70 percent of the recorded Electromyography (EMG) cut off window and then used for classification and modeling purposes. The neuro-fuzzy classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.
988			_aEBSPRINGER_2018
650		7	_aProcesadores digitales de señal _2embne _9162764
700	1		_aGunjan, Vinit Kumar. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/n2015182000 _1http://viaf.org/viaf/315177857/
776	0	8	_iEdición impresa: _z9789812873217
776	0	8	_iEdición impresa: _z9789812873194
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-287-320-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2019 _dz _zSI _eIG