Uso de la actividad muscular del trapecio para determinación de estrés: Una revisión de la literatura

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Isabel M. Vega Rodríguez
Mónica A Vallejo Velásquez
Freddy Bolaños Martínez

Resumen

La electromiografía (EMG) es una técnica para la evaluación y registro de la actividad eléctrica de los músculosesqueléticos. La EMG superficial (sEMG) puede ser detectada por electrodos superficiales en la piel, y representa la suma o mezcla de las contribuciones eléctricas generadas por las unidades motoras de los músculos. Se han reportado estudios en los que se usa la sEMG del músculo trapecio para estimar niveles de estrés. En este artículo se presenta una revisión de diferentes investigaciones realizadas sobre la relación entre estrés y actividad eléctrica del músculo trapecio, bajo dos enfoques: multimodal y unimodal, considerando la actividad eléctrica muscular como único indicador fisiológico para estimar el estrés.

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Vega Rodríguez, I. M., Vallejo Velásquez, M. A., & Bolaños Martínez, F. (2018). Uso de la actividad muscular del trapecio para determinación de estrés: Una revisión de la literatura. Revista De Ciencia Y Tecnología, 29(1), 71–78. Recuperado a partir de https://www.fceqyn.unam.edu.ar/recyt/index.php/recyt/article/view/216
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Baum A., “Stress, intrusive imagery, and chronic distress,” Heal. Psychol., 9(6): 653–675, 1990.

Herman J.P. and Cullinan W.E., “Neurocircuitry of stress: Central control of the hypothalamo- pituitary-adrenocortical axis,” Trends Neurosci., 20 (2):78–84, 1997.

Tsigos C. and Chrousos G.P., “Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress,” J. Psychosom. Res., 53(4):865–871, 2002.

Tasker J.G. and Herman J.P., “HHS Public Access,” Stress, 14(4):398–406, 2011.

Koolhaas J.M., Bartolomucci A., Buwalda B., de Boer S.F., Flügge G., Korte S.M., Meerlo P., Murison R., Olivier B., Palanza P., Richter-Levin G., Sgoifo A., Steimer T., Stiedl O.,van Dijk G., Wöhr M., Fuchs E., “Stress revisited: A critical evaluation of the stress concept,” Neurosci. Biobehav. Rev., 35(5):1291–1301, 2011.

Maruyama Y., Kawano A., Okamoto S., Ando T., Ishitobi Y., Tanaka Y., Inoue A., Imanaga J., Kanehisa M., Higuma H., Ninomiya T., Tsuru J., Hanada H., Akiyoshi J., “Differences in salivary alpha-amylase and cortisol responsiveness following exposure to electrical stimulation versus the trier social stress tests,” PLoS One, 7(7): e39375, 2012.

Watson I.P.B., Brüne M., Bradley A.J., “The evolution of the molecular response to stress and its relevance to trauma and stressor-related disorders,” Neurosci. Biobehav. Rev., 68:134–147, 2016.

Wijsman J., Grundlehner B., Liu H., Hermens H., Penders J., “Towards mental stress detection using wearable physiological sensors.,” in Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society Conference, vol. 2011, pp. 1798–801, 2011.

Saidatul A., Paulraj M.P., Yaacob S., Mohamad Nasir N.F., “Automated system for stress evaluation based on EEG signal: A prospective review,” in 2011 IEEE 7th International Colloquium on Signal Processing and its Applications (CSPA), pp.167–171, 2011.

Wijsman J., Grundlehner B., Penders J., Hermens H., “Trapezius muscle EMG as predictor of mental stress,” in ACM Transactions on Embedded Computing Systems, 12(4):155–163, 2010.

Zheng B.S., Murugappan M., Yaacob S., “Human emotional stress assessment through Heart Rate Detection in a customized protocol experiment,” in ISIEA 2012 - 2012 IEEE Symposium on Industrial Electronics and Applications, pp. 293–298, 2012.

Wijsman J., Vullers R., Polito S., Agell C., Penders J., Hermens H., “Towards Ambulatory Mental Stress Measurement from Physiological Parameters,” in 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction, pp. 564–569, 2013.

Sharma N. and Gedeon T., “Objective measures, sensors and computational techniques for stress recognition and classification: A survey,” Comput. Methods Programs Biomed., 108(3):1287–1301, 2012.

Larsman P., Thorn S., Søgaard K., Sandsjö L., Sjøgaard G., Kadefors R., “Work related perceived stress and muscle activity during standardized computer work among female computer users,” Work, 32(2):189–199, 2009.

Shahidi B., Haight A., Maluf K., “Differential effects of mental concentration and acute psychosocial stress on cervical muscle activity and posture,” J. Electromyogr. Kinesiol., 23(5):1082–1089, 2013.

Rissén D., Melin B., Sandsjö L., Dohns I., Lundberg U., “Surface EMG and psychophysiological stress reactions in women during repetitive work,” Eur. J. Appl. Physiol., 83(2–3):15–222, 2000.

Luijcks R., Hermens H.J., Bodar L., Vossen C.J., Van Os J., Lousberg R., “Experimentally induced stress validated by EMG activity,” PLoS One, 9(4):e95215, 2014.

Lundberg U., Kadefors R., Melin B., Palmerud G., Hassmén P., Engström M., Dohns I.E., “Psychophysiological stress and EMG activity of the trapezius muscle.,” Int. J. Behav. Med., 1(4):354–370, 1994.

Larsson S.E., Larsson R., Zhang Q., Cai H., Oberg P.A., “Effects of psychophysiological stress on trapezius muscles blood flow and electromyography during static load,” Eur. J. Appl. Physiol. Occup. Physiol., 71(6):493–498, 1995.

McLean L. and Urquhart N., “The influence of psychological stressors on myoelectrical signal activity in the shoulder region during a data entry task,” Work Stress, 16(2):138–153, 2002.

Lundberg U., Forsman M., Zachau G., Eklöf M., Palmerud G., Melin B., Kadefors R., “Effects of experimentally induced mental and physical stress on motor unit recruitment in the trapezius muscle,” Work Stress, 16(2):166–178, 2002.

Krantz G., Forsman M., Lundberg U., “Consistency in physiological stress responses and electromyographic activity during induced stress exposure in women and men,” Integr Physiol Behav Sci, 39(2):105–118, 2004.

Flodgren G.M., Crenshaw A.G., Gref M., Fahlström M., “Changes in interstitial noradrenaline, trapezius muscle activity and oxygen saturation during low-load work and recovery,” Eur. J. Appl. Physiol., 107(1):31–42, 2009.

Lundberg U., Dohns I.E., Melin B., Sandsjö L., Palmerud G., Kadefors R., Ekström M., Parr D., “Psychophysiological stress responses, muscle tension, and neck and shoulder pain among supermarket cashiers.,” J. Occup. Health Psychol., 4(3):245–255, 1999.

Lundberg U., “Psychophysiology of work: Stress, gender, endocrine response, and work-related upper extremity disorders,” Am. J. Ind. Med., 41(5):383–392, 2002.

Rissén D., Melin B., Sandsjö L., Dohns I., Lundberg U., “Psychophysiological stress reactions, trapezius muscle activity, and neck and shoulder pain among female cashiers before and after introduction of job rotation,” Work Stress, 16(2):127–137, 2002.

Westgaard R.H., Mork P.J., Lorås H.W., Riva R., Lundberg U., “Trapezius activity of fibromyalgia patients is enhanced in stressful situations, but is similar to healthy controls in a quiet naturalistic setting: a case-control study.,” BMC Musculoskelet. Disord., 14: 97, 2013.

Bansevicius D., Westgaard R.H., Jensen C., “Mental stress of long duration: EMG activity, perceived tension, fatigue, and pain development in pain-free subjects,” Headache, 37(8):499–510, 1997.

Noteboom J.T., Barnholt K.R., Enoka R.M., “Activation of the arousal response and impairment of performance increase with anxiety and stressor intensity,” J. Appl. Physiol., 91(5):2093–2101, 2001.

Blangsted A.K., Søgaard K., Christensen H., Sjøgaard G., “The effect of physical and psychosocial loads on the trapezius muscle activity during computer keying tasks and rest periods,” Eur. J. Appl. Physiol., 91(2–3):253–258, 2004.

Zheng B.S., Murugappan M., Yaacob S., aMurugappan S., “Human emotional stress analysis through time domain electromyogram features,” in 2013 IEEE Symposium on Industrial Electronics & Applications, pp. 172–177, 2013.

Scalisi R.G., Paleari M., Favetto A., Stoppa M., Ariano P., Pandolfi P., Chiolerio A., “Inkjet printed flexible electrodes for surface electromyography,” Org. Electron. physics, Mater. Appl., 18: 89–94, 2015.

Goen A., “Classification of EMG Signals for Assessment of Neuromuscular Disorders,” Int. J. Electron. Electr. Eng., 2(3):242–248, 2014.

Biagetti G., Crippa P., Curzi A., Orcioni S., Turchetti C., “Analysis of the EMG Signal during Cyclic Movements Using Multicomponent AM-FM Decomposition,” IEEE J. Biomed. Heal. Informatics, 19(5):1672–1681, 2015.

Jamaluddin F.N., Ahmad S.A., Noor S.B.M., Hassan W.Z.W., Yaakob A., Adam Y., Ali S.H.M., “Amplitude and frequency changes in surface EMG of biceps femoris during five days Bruce Protocol treadmill test,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2015–Novem, pp. 6219–6222, 2015.

Nicoletti C., Spengler C.M., Läubli T., “Physical workload, trapezius muscle activity, and neck pain in nurses’ night and day shifts: A physiological evaluation,” Appl. Ergon., 45(3):741–746, 2014.

Ahsan M., “Electromygraphy (EMG) signal based hand gesture recognition using artificial neural network (ANN),” in 2011 4th International Conference on Mechatronics (ICOM), pp. 17–19, May 2011.

Wurth S.M. and Hargrove L.J., “Real-time comparison of conventional direct control and pattern recognition myoelectric control in a two-dimensional Fitts’ law style test,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 3630–3633, 2013.

Ceseracciu E., Reggiani M., Sawacha Z., Sartori M., Spolaor F., Cobelli C., Pagello E., “SVM classification of locomotion modes using surface electromyography for applications in rehabilitation robotics,” in Proceedings - IEEE International Workshop on Robot and Human Interactive Communication, pp. 165–170, 2010.

Khushaba R.N., Kodagoda S., Takruri M., Dissanayake G., “Toward improved control of prosthetic fingers using surface electromyogram (EMG) signals,” Expert Syst. Appl., 39(12):10731–10738, 2012.

Hahne J.M., Graimann B., Muller K.R., “Spatial filtering for robust myoelectric control,” IEEE Trans. Biomed. Eng., 59(5):1436–1443, 2012.

Fiorucci E., Bucci G., Ciancetta F., Monaco A., “Measurement and analysis of surface electromyographic signals on patients wearing eyeglasses,” in MeMeA 2011 - 2011 IEEE International Symposium on Medical Measurements and Applications, Proceedings, pp. 1–7, 2011.

Fairley J.A., Georgoulas G., Mehta N.A., Gray A.G., Bliwise D.L., “Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep,” Biomed. Signal Process. Control, 7(6):606–615, 2012.

Larsman P., Kadefors R., Sandsjö L., “Psychosocial work conditions, perceived stress, perceived muscular tension, and neck/shoulder symptoms among medical secretaries,” Int. Arch. Occup. Environ. Health, 86(1):57–63, 2013.

Mehta R.K. and Agnew M.J., “Influence of mental workload on muscle endurance, fatigue, and recovery during intermittent static work,” Eur. J. Appl. Physiol., 112(8):2891–2902, 2012.

Choi J., Member S., Ahmed B., “Ambulatory Stress Monitoring with Minimally-Invasive Wearable Sensors,” in Department of Computer Science and Engineering, Texas A&M University, Technical Report tamu-cs-tr-2011-11-1, pp. 1–8, 2010.

Kendell C., Lemaire E.D., Losier Y., Wilson A., Chan A., Hudgins B., “A novel approach to surface electromyography: an exploratory study of electrode-pair selection based on signal characteristics,” J. Neuroeng. Rehabil., 9(1):24, 2012.

Almanji A. and Chang J.Y., “Feature extraction of surface electromyography signals with continuous wavelet entropy transform,” Microsyst. Technol., 17(5):1187–1196, 2011.

Merletti R., “Standards for reporting EMG data,” J. Electromyogr. Kinesiol., 9(1):3-4, 1999.

De Luca C.J., Adam A., Wotiz R., Gilmore L.D., Nawab S.H., “Decomposition of surface EMG signals,” J. Neurophysiol., 96(3):1646–1657, 2006.

Sarda A.R., “Computational Intelligence Techniques for Electro-Physiological Data Analysis,” Starlab Barcelona S.L. - Universitat de Barcelona, 2012.

Karthikeyan P., Murugappan M.,Yaacob S., “A review on stress inducement stimuli for assessing human stress using physiological signals,” in Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011, pp. 420–425, 2011.

Bhuvaneswari P. and Kumar J.S., “Classification of Electromyography Signal using Wavelet Decomposition Method,” in 2014 IEEE International Conference on Computational Intelligence and Computing Research, pp. 1–4, 2014.

Reaz M.B.I., Hussain M.S., Mohd-Yasin F., “Techniques of EMG signal analysis: detection, processing, classification and applications (Correction).,” Biol. Proced. Online, 8(1):11–35, 2006.

De Luca C.J., Donald Gilmore L., Kuznetsov M., Roy S.H., “Filtering the surface EMG signal: Movement artifact and baseline noise contamination,” J. Biomech., 43(8):1573–1579, 2010.

Al-qaisi S. and Aghazadeh F., “Electromyography analysis : Comparison of maximum voluntary contraction methods for anterior deltoid and trapezius muscles,” Procedia Manuf., 3:4578–4583, 2015.

Park S.Y. and Yoo W.G., “Comparison of exercises inducing maximum voluntary isometric contraction for the latissimus dorsi using surface electromyography,” J. Electromyogr. Kinesiol., 23(5):1106–1110, 2013.

Naik G.R., Suviseshamuthu S.E., Gobbo M., Acharyya A., Nguyen H.T., “Principal Component Analysis Applied to Surface Electromyography: A Comprehensive Review,” IEEE Access, 4(c):1–17, 2016.

Mahaphonchaikul K., Sueaseenak D., Pintavirooj C., Sangworasil M., Tungjitkusolmun S., “EMG signal feature extraction based on wavelet transform,” in The 2010 ECTI International Conference on Electrical Engineering/Electronics Computer Telecommunications and Information Technology (ECTI-CON2010), pp. 327–331, 2010.

Gligorijević I., Van Dijk J.P., Mijović B., Van Huffel S., Blok J.H., De Vos M., “A new and fast approach towards sEMG decomposition,” Med. Biol. Eng. Comput., 51(5):593–605, 2013.

Akazawa J. and Okuno R., “A method for quantitative SEMG decomposition and MUAP classification during voluntary isovelocity elbow flexion,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 6776–6779, 2013.

Zhao H. and Xu G., “The research on surface electromyography signal effective feature extraction,” in Proceedings of the 6th International Forum on Strategic Technology, IFOST 2011, 2:1195–1198, 2011.

Parsaei H., Gangeh M.J., Stashuk D.W., Kamel M.S., “Augmenting the decomposition of EMG signals using supervised feature extraction techniques.,” Conf Proc IEEE Eng Med Biol Soc., 2012: 2615–2618, 2012.

Wang F., Peng Y., Yang Y., Zhang P., “Automated Discrimination of Gait Patterns Based on sEMG Recognition Using Neural Networks,” in The 4th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, pp. 225–230, 2014.

Chan F.H.Y., Lam F.K., Parker P.A., “Fuzzy EMG classification for prosthesis control,” IEEE Trans. Rehabil. Eng., 8(3):305–311, 2000.

Chowdhury R.H., Reaz M.B., Ali M.A., Bakar A.A., Chellappan K., Chang T.G., “Surface electromyography signal processing and classification techniques”,Sensors (Basel), 13(9):12431–12466, 2013.

Alkan A. and Günay M., “Identification of EMG signals using discriminant analysis and SVM classifier,” Expert Syst. Appl., 39(1):44–47, 2012.

Choi J., Ahmed B., Gutierrez-Osuna R., “Development and evaluation of an ambulatory stress monitor based on wearable sensors BT - Special Issue of Emerging Technologies for Patient-specific Healthcare,” IEEE Trans. Inf. Technol. Biomed.,16(2): 279–286, 2012.

Schleifer L.M., Spalding T.W., Kerick S.E., Cram J.R., Ley R., Hatfield B.D., “Mental stress and trapezius muscle activation under psychomotor challenge: A focus on EMG gaps during computer work,” Psychophysiology, 45(3):356–365, 2008.

Roman-Liu D., Grabarek I., Bartuzi P., Choromański W., “The influence of mental load on muscle tension.,” Ergonomics, 56(7):1125–33, 2013.

Gemperle F., Kasabach C., Stivoric J., Bauer M., Martin R., “Design for wearability,” in Digest of Papers. Second International Symposium on Wearable Computers (Cat.No.98EX215), pp. 116–122, 1998.

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