References
- Östlund N. Yu J. Roeleveld K. Karlsson JS. Adaptive spatial filtering of multichannel surface electromyogram signals. Med. Biol. Eng. Comput 2004; 42(6): 825–831.
- Farina D. Merletti R. A novel approach for precise simulation of the EMG signal detected by surface electrodes. IEEE. Trans. Biomed. Eng 2001; 48 (6): 637–646.
- Mesin L. Farina D. Simulation of surface EMG signals generated by muscle tissues with inhomogeneity due to fiber pinnation. IEEE. Trans. Biomed. Eng 2004; 51 (9): 1521–1529.
- Mesin L. Simulation of surface EMG signals for a multilayer volume conductor with triangular model of the muscle tissue. IEEE. Trans. Biomed. Eng 2006; 53(11): 2177–2184.
- Fuglevand AJ. Winter DA. Patla AE. Models of recruitment and rate coding organization in motor-unit pools. J. Neurophysiol 1993; 70 (6): 2470–2488.
- Stashuk DW. Simulation of electromyographic signals. J. Electromyogra. Kinesiol 1993 3 (3): 157–173.
- Wang W. Stefano Ade. Allen R. A simulation model of the surface EMG signal for analysis of muscle activity during the gait cycle. Comput. Biol. Med 2006; 36 (6): 601–618.
- Keenan KG. Farina D. Meyer FG. Merletti R. Enoka RM. Sensitivity of the cross-correlation between simulated surface EMGs for two muscles to detect motor unit synchronization. J. Appl. Physiol 2007 102 (3): 1193–1201.
- Merletti R. Lo Conte L. Avignone E. Guglielminotti P. Modelling of surface myoelectric signals – part I: model implementation. IEEE. Trans. Biomed. Eng 1999; 46 (7): 810–820.
- Farina D. Alberto R. Compensation of the effect of sub-cutaneous tissue layers on surface EMG : a simulation study. Med. Eng. Physics 1999; 21 (6–7): 487–497.
- Mesin L. Farina F. A model for surface EMG generation in volume conductors with spherical inhomogeneties. IEEE. Trans. Biomed. Eng 2005; 52 (12): 1984–1993.
- Mesin L. Farina D. An analytical model for surface EMG generation in volume conductors with smooth conductivity variations. IEEE. Trans. Biomed. Eng 2006; 53 (5): 773–779.
- Dimitrov GV. Dimitrova N.A. Precise and fast calculation of the motor unit potentials detected by a point and rectangular plate electrode. Med. Eng. Phys 1998; 20 (5): 374–381.
- Farina D. Mesin L. Martina S. Advances in surface EMG signal simulation with analytical and numerical descriptions of the volume conductor. Med. Biol. Eng. Comput 2004; 42 (4): 467–476.
- Lowery MM. Stoykov NS. Taflove A. Kuiken TA. A multiple-layer finite-element model of the surface EMG signal, IEEE. Trans. Biomed. Eng 2002; 49 (5): 446–454.
- Mesin L. Joubert M. Hanekom T. Merletti R. Farina D. A Finite Element Model for Describing the Effect of Muscle Shortening on Surface EMG. IEEE. Trans. Biomed. Eng 2005; 53 (4): 593–600.
- Farina D. Mesin L. Martina S. Merletti R. A surface EMG generation model with multilayer cylindrical description of the volume conductor. IEEE. Trans. Biomed. Eng 2004; 51 (3): 415–426.
- Blok JH. Stegeman DF. Van Oosterom A. Three-layer volume conductor model and software package for applications in surface electromyography. Ann. Biomed. Eng 2002; 30 (4): 566–577.
- Gootzen TH. Stegeman DF. Van Oosterom A. Finite limb dimensions and finite muscle length in a model for the generation of electromyographic signals, Electroencephalogr. Clin. Neurophysiol 1991; 81 (2): 152–162.
- Mesin L. Simulation of surface EMG signals for a multilayer volume conductor with a superficial bone or blood vessel, IEEE. Trans. Biomed. Eng 2008; 55 (6): 1647–1657.
- Messaoudi N. Bekka RE. Philippe R. Harba R. Assessment of the non-Gaussianity and non-linearity levels of simulated sEMG signals on stationary segments, J. Electromyogr. Kinesiol 2017; 32 (Feb): 70–82.
- Rosenfalck P. Intra and extracellular fields of active nerve and muscle fibres: A physico-mathematical analysis of different models. Acta. Physiol. Scand 1969; 321: 1–168.
- Messaoudi N. Bekka RE. Belkacem S. Effects of detection system parameters on cross-correlations between MUAPs generated from parallel and inclined muscle fibers. Polish. J. Med. Phys. Eng 2021; 27 (1): 87–97.
- Messaoudi N. Belkacem S. Bekka RE. Ability of spatial filters to distinguish between two MUAPs generated from MUs with different locations, sizes and fibers pennation. J. Instrument, 2023; 18 (3): P03041.
- Enoka RM. Motor Unit. Wiley Encyclopedia of Biomedical Engineering, 2006.
- Hu X. Rymer WZ. Suresh N. Motor unit firing rate patterns during voluntary muscle force generation: a simulation study. J. Neural. Eng 2014; 11 (2): 026015.
- De Luca CJ. Hostage EC. Relationship between firing rate and recruitment threshold of motoneurons in voluntary isometric contractions. J. Neurophysiol 2010; 104 (2) 1034–1046.
- Hu X. Rymer WZ. Suresh NL. Motor unit pool organization examined via spike-triggered averaging of the surface Electromyogram. J. Neurophysiol 2013; 110 (5): 1205–1220.
- Messaoudi N. Bekka R.E. (2015). From Single Fiber Action Potential to Surface Electromyographic Signal: A Simulation Study. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2015. Lecture Notes in Computer Science, vol 9043. Springer, Cham. https://doi.org/10.1007/978-3-319-16483-0_32.
- Messaoudi N. Bekka RE. Belkacem S. Cross-Correlation Coefficient as a Means for Estimating the Effect of MVC level According to the Fibres Inclination. The Fifth International Conference on Electrical Engineering, ICEE2017, Boumerdes, Algeria, Proceedings, IEEE Xplore (2017b).
- Messaoudi N. Bekka RE. Belkacem S. Classification of the systems used in surface electromyographic signals detection according to the degree of isotropy. Adv. Biomed. Eng 2018; 7 (1): 107–116.
- Belkacem S. Bekka RE. Messaoudi N. Influence of MVC on Temporal and Spectral Features of Simulated Surface Electromyographic Signals. Critical. Reviews. Biomed. Eng 2019; 47 (5): 409–418.
- Messaoudi N. Bekka RE. Belkacem S. Influence of Fibers Inclination on the Degree of Gaussianity of Simulated Surface EMG Signals. ICBBT 2020, May 22–24, 2020, Xi’an, China.
- Merletti R. Temporiti F. Gatti R. Gupta S. Sandrini G. Serrao M. Translation of surface electromyography to clinical and motor rehabilitation applications: The need for new clinical figures. Translatio. Neurosci 2023; 14 (1): 1 20220279.
- Campanini I. Merlo A. Disselhorst-Klug C. Mesin L. Muceli S. Merletti R. Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors. Sensors 2022; 22 (11) 4150.