Abstract
Reduction in number of motor units (nMU) and fast fibre ratio (FFR) is associated with disease or atrophy when this is rapid. There is a need to study the effect of nMU and FFR to analyse the association with ageing and disease. This study has developed a mathematical model to investigate the relationship between nMU and FFR on surface electromyogram (sEMG) of the biceps muscles. The model has been validated by comparing the simulation outcomes with experiments comparing the sEMG of physically active younger and older cohort. The results show that there is statistically significant difference between the two groups, and the simulation studies closely model the experimental results. This model can be applied to identify the cause of muscle weakness among the elderly due to factors such as muscle dystrophy or preferential loss of type F muscle fibres.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arjunan SP, Kumar DK (2013) Age-associated changes in muscle activity during isometric contraction. Muscle Nerve 47(4):545–549
Boedine SC (2013) Disuse-induced muscle wasting. Int J Biochem Cell Biol 45:2200–2208
Breit S, Spieker S, Schultz JB, Gasser T (2008) Electromyography based model can distinguish early essential from parkinson tremor. Nat Rev Neurol 255:103–111
Brown WF, Strong MJ, Snow R (1988) Methods for estimating numbers of motor units in biceps-brachialis muscles and losses of motor units with aging. Muscle Nerve 11:423–432
Ciciliot S, Rossi AC, Dyar KA, Blaauw B, Schiaffino S (2013) Muscle type and fiber type specificity in muscle wasting. Int J Biochem Cell Biol 45:2200–2208
Deschenes MR (2004) Effects of aging on muscle fibre type and size. Sports Med 34(12):809–824
Dideriksen JL, Enoka RM, Farina D (2011) A model of surface electromyogram in pathological tremor. IEEE Trans Biomed Eng 58(8):2178–2184
Doherty TJ, Vandervoort AA, Brown WF (1993) Effects of ageing on the motor unit: a brief review. Can J Appl Physiol 18(4):331–358
Farina D, Fosci M, Merletti R (2002) Motor unit recruitment strategies investigated by surface EMG variables. J Appl Physiol 92(1):235–247
Fuglevand AJ, Winter DA, Patla AE (1993) Models of recruitment and rate coding organization in motor-unit pools. J Neurophysiol 70(6):2470–2488
Gydikov A, Kosarov D (1974) Some features of different motor units in human biceps brachii. Pflügers Arch 347(1):75–88
Klein CS, Marsh GD, Petrella RJ, Rice CL (2003) Muscle fiber number in biceps brachii muscle of young and old men. Muscle Nerve 28:62–68
Krogh-Lund C, Jørgensen K (1992) Modification of myo-electric power spectrum in fatigue from 15 % maximal voluntary contraction of human elbow flexor muscles, to limit of endurance: reflection of conduction velocity variation and/or centrally mediated mechanisms? Eur J Appl Physiol 64:359–370
Kukulka CG, Clamann HP (1981) Comparison of the recruitment and discharge properties of motor units in human brachial biceps and adductor pollicis during isometric contractions. Brain Res 219(1):45–55
Lowery MM, Vaughan CL, Nolan PJ, O’Malley MJ (2000) Spectral compression of the electromyographic signal due to decreasing muscle fiber conduction velocity. IEEE Trans Rehabil Eng 8(3):353–361
Manini TM, Clark BC (2012) Dynapenia and aging: an update. J Gerontol Ser A: Biol Sci Med Sci 67(1):28–40
Merletti R, Lo Conte L, Avignone E, Guglielminotti P (1999) Modeling of surface myoelectric signals. I. Model implementation. IEEE Trans Biomed Eng 46(7):810–820
Navallas J, Malanda A, Gila L, Rodríguez J, Rodríguez I (2010) A muscle architecture model offering control over motor unit fiber density distributions. Med Biol Eng Comput 48(9):875–886
Parsaei H, Nezhad FJ, Stashuk DW, Hamilton-Wright A (2011) Validating motor unit firing patterns extracted by EMG signal decomposition. Med Biol Eng Comput 49(6):649–658
Rie M, Terao J (2013) Role of dietary flavonoids in oxidative stress and prevention of muscle atrophy. J Phys Fitness Sports Med 2(4):385–392
Roeleveld K, Blok J, Stegeman D, Van Oosterom A (1997) Volume conduction models for surface EMG; confrontation with measurements. J Electromyogr Kinesiol 7(4):221–232
SENIAM (2009) Surface electromyography for the non invasive assessment of muscles. Accessed from: http://seniam.org/
van Kan GA (2009) Epidemiology and consequences of sarcopenia. J Nutr Health Aging 13(8):708–712
van Veen BK, Wolters H, Wallinga W, Rutten WL, Boom HB (2006) The bioelectrical source in computing single muscle fiber action potentials. Biophys J 64(5):1492–1498
Vandervoort AA (2001) Aging of the human neuromuscular system. Muscle Nerve 25(1):17–25
Wheeler KA, Kumar DK, Shimada H (2010) An accurate bicep muscle model with sEMG and muscle force outputs. J Med Biol Eng 30(6):393–398
Wheeler KA, Shimada H, Kumar DK, Arjunan SP (2010) A sEMG model with experimentally based simulation parameters. In: Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 4258–4261, 31 Aug–4 Sep
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare that they have no competing interests.
Rights and permissions
About this article
Cite this article
Poosapadi Arjunan, S., Kumar, D.K., Wheeler, K. et al. Effect of number of motor units and muscle fibre type on surface electromyogram. Med Biol Eng Comput 54, 575–582 (2016). https://doi.org/10.1007/s11517-015-1344-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-015-1344-1