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2021, Number 2

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Revista Cubana de Informática Médica 2021; 13 (2)

EMGSoft - Software for the analysis of the multichannel surface electromiografic signal

Fraga TRA, Montoya PA, Díaz SJR, Castañeda GM

Language: Spanish
References: 11
Page:
PDF size: 756.71 Kb.


ABSTRACT

Due to the lack of automatic processing of multi-channel surface electromyographic signals, software for processing these signals was developed and automatic criteria of expertise were applied for the interpretation of quantitative electromyography, which consists of algorithms for characterize the study of tremor and movement disorders. The system determined, for the resting state, the frequency and amplitude of the contractile activity, the timing of the tremor pattern and, depending on this, the presence of the alternating pattern, and the electromyographic activity bursts (trains) were quantitatively characterized. For the states of voluntary contraction, reciprocal inhibition and coactivation parameters were estimated between pairs of agonist and/or antagonist muscles. A validation process was carried out using a sample of records obtained in healthy and sick subjects (parkinsonian syndromes, Parkinson's disease, tremor and dystonias).


REFERENCES

  1. Trenard E, Pérez R., Montoya A. GRAP-NFM. Sistema informático para emular y extender las funcionalidades del Neuropack Four Mini. Rev Cuba Inform Méd [Internet]. 2014 [citado 3 Oct 2021];6(1):24-33. Disponible en: Disponible en: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1684-18592014000100004

  2. International Federation of Clinical Neurophysiology (IFCN) [Internet]. Definition of Clinical Neurophysiology; 2019 [citado 11 Mar 2019]. Disponible en: Disponible en: http://www.ifcn.info/

  3. Saladin K. Anatomía y Fisiología. La unidad entre forma y función. 6ª Edición. México: McGraw-Hill Interamericana; 2013

  4. Basmajian JV, De Luca CJ. Muscles Alive. Their Function Revealed by Electromyography. Baltimore: Williams Wilkins; 1985

  5. Montoya A. Laboratorio de potenciales evocados, estudios de neuroconducción y EMG. Procedimientos normativos generales. Santiago de Cuba: Hospital General Dr. Juan Bruno Zayas Alfonso; 2012

  6. Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in C. The Art of Scientific Computing. 2nd Edition. New York: Cambridge University Press; 2002

  7. Dokuchaev, N. On sampling theorem with sparse decimated samples: exploring branching spectrum degeneracy. ArXiv [Internet]. 2017 [citado 10 Abr 2019]. Disponible en: Disponible en: https://arxiv.org/abs/1605.00414

  8. Molina I. Capítulo 4. En: Medidas de Proximidad [Internet] ; UC3. Madrid. 2010 [citado 11 May 2019]. Disponible en: Disponible en: http://halweb.uc3m.es/esp/Personal/personas/imolina/MiDocencia/TecnicasInvestigacion0910/

  9. Rorabaugh CB. Digital Filter Designer's Handbook. Featuring C routines. Ohio: McGraw-Hill, Inc; 1993.

  10. Dennis A, Wixom B, Tegarden D. System Analysis & Design. An Object-Oriented Approach with UML. 5th Edition. New Jersey: John Wiley & Sons; 2015.

  11. Devore JL. Probability and Statistics for Engineering and the Sciences. 9th Edition. Boston: Cengage Learning; 2016.




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