Comparison of tibialis anterior and gastrocnemius muscles activation on balance training devices and hoverboard

Authors

  • Khairiyah Abdul Rahman Universiti Teknologi Malaysia
  • Aizreena Azaman Universiti Teknologi Malaysia
  • Hadafi Fitri Mohd Latip Universiti Teknologi Malaysia
  • Mohd Azuwan Mat Dzahir Universiti Teknologi Malaysia
  • Malarvili Balakrishnan Universiti Teknologi Malaysia

DOI:

https://doi.org/10.11113/mjfas.v13n4-2.820

Keywords:

Muscle activity, electromyography, balance training device

Abstract

Balance training devices such as wobble board, basu ball and balance cushion are the tool use in balance training exercise programme in order to improve muscle strength and restore posture balance due degeneration of body function or injury. Recently, self-balancing scooter such as Segway and hover board showed a positive effects on rehabilitation. However, it is less known how these devices affect muscle physiological properties. This study aims to to measure ankle muscles activation on  difference balance training devices and hover board. Besides, a comparison between these device will be done in order to identify if hover board has a promising feature to be an alternative balance training device. In this research, surface EMG (sEMG) was used to record tibialis anterior and gastrocnemius muscle activities. Seventeen healthy subjects were required to stand on three different types of balance training device such as wobble board, balance cushion, bosu ball and a hover board. They were asked to maintain their standing position on each devices for two minutes. Both time domain and frequency domain analysis were used to identify the features of the EMG signal. Time domain analysis measurement involved average rectified value (ARV) and root mean square (RMS), meanwhile for frequency domain, median frequency (MDF) of the signal were measured. The results shows that, the RMS is differed significantly between the balance training devices (p<0.05) for tibialis anterior muscle but not gastrocnemius muscle. Meanwhile, no significant difference between the devices in the ARV and the MDF value (p>0.05). Besides, less stable devices increased muscle activity were observed. There is not much difference between hover board and the other devices in term of physiological effects of both tibialis anterior and gastrochemious muscle. It is also suggested that hover board offers a promising feature to be an alternative device for balance training device.

Author Biographies

Khairiyah Abdul Rahman, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

Aizreena Azaman, Universiti Teknologi Malaysia

Senior lecturer at Faculty Bioscience and Medical Engineering. Research interest includes gait and posture analysis, biomechanics, and biosignal processing.

Hadafi Fitri Mohd Latip, Universiti Teknologi Malaysia

Department of Clinical Science, Faculty of Biosciences and Medical Engineering

Mohd Azuwan Mat Dzahir, Universiti Teknologi Malaysia

Deparment of Applied Mechanics and Design, Faculty of Mechanical Engineering

Malarvili Balakrishnan, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

References

Amtmann, J., Loch, K., Todd, C. S., & Spath, W. (2013). Heart Rate Effects of Longboard Skateboarding. Intermountain Journal of Sciences, 19(1-4), 22-27.

Azaman, A., & Yamamoto, S. i. (2014). Balance process during repeated surface perturbation: Adaptation response of joint stiffness and muscle activation. Paper presented at the 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES), Miri, Sarawak, Malaysia.

Bandzar, S., Bandzar, A., Gupta, S., & Atallah, H. (2016). 158 Epidemiology of Hoverboard Injuries Requiring Emergency Care. Annals of Emergency Medicine, 68(4), S62-S63. doi:10.1016/j.annemergmed.2016.08.171

Cifrek, M., Medved, V., Tonković, S., & Ostojić, S. (2009). Surface EMG based muscle fatigue evaluation in biomechanics. Clinical Biomechanics, 24(4), 327-340. doi:10.1016/j.clinbiomech.2009.01.010

Cimadoro, G., Paizis, C., Alberti, G., & Babault, N. (2013). Effects of different unstable supports on EMG activity and balance. Neuroscience Letters, 548(Supplement C), 228-232. doi:10.1016/j.neulet.2013.05.025

De Luca, C., & C Hostage, E. (2010). Relationship Between Firing Rate and Recruitment Threshold of Motoneurons in Voluntary Isometric Contractions. Journal of Neurophysiology, 104(2), 1034-1046. doi:10.1152/jn.01018.2009

Fogg, B. (December, 2002). Persuasive technology: Using computers to change what we think and do. Ubiquity, Article No. 5. doi: 10.1145/764008. 763957

Fukuda, T. Y., Rossetto, F. M., Magalhães, E., Bryk, F. F., Lucareli, P. R. G., & Carvalho, N. A. D. A. (2010). Short-Term Effects of Hip Abductors and Lateral Rotators Strengthening in Females With Patellofemoral Pain Syndrome: A Randomized Controlled Clinical Trial. Journal of Orthopaedic & Sports Physical Therapy, 40(11), 736-742. doi:10.2519/jospt.2010.3246

Goh, D. H.-L., & Razikin, K. (2015). Is Gamification Effective in Motivating Exercise? In M. Kurosu (Ed.), Human-Computer Interaction: Interaction Technologies: 17th International Conference, HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings, Part II (pp. 608-617). Cham: Springer International Publishing.

Hinman, M. R. (2002). Comparison of Two Short-term Balance Training Programs for Community-dwelling Older Adults. Journal of Geriatric Physical Therapy, 25(3), 10-15.

Kang, J. H., & Hyong, I. H. (2012). Analysis of electromyographic activities of ankle muscles at different levels of instability of unstable surfaces. Journal of Physical Therapy Science, 24(12), 1333-1335.

Karashanov, A., Manolova, A., & Neshov, N. (2016). Application for hand rehabilitation using leap motion sensor based on a gamification approach. International Journal of Advance Research in Science and Engineering, 5(2), 61-69.

Kerr, J., Sallis, J. F., Saelens, B. E., Cain, K. L., Conway, T. L., Frank, L. D., & King, A. C. (2012). Outdoor physical activity and self rated health in older adults living in two regions of the U.S. The International Journal of Behavioral Nutrition and Physical Activity, 9, 89. doi:10.1186/1479-5868-9-89

Konrad, P. (2005). The ABC of EMG: A practical introduction to kinesiological electromyography. USA: Noraxon.

Latip, H. F. M., Omar, A. H., Shahrom, A., Azmi, F., & Ridhwan. (2015). A Novel hybrid rehabilitation device for neuromuscular control exercise and rehabilitation training. Procedia Computer Science, 76(Supplement C), 368-375. doi:10.1016/j.procs.2015.12.311

Lee, J.-W., Yoon, S.-W., Kim, J.-H., Kim, Y.-P., & Kim, Y.-N. (2012). The Effect of ankle range of motion on balance performance of elderly people. Journal of Physical Therapy Science, 24(10), 991-994. doi:10.1589/jpts.24.991

Nieratko, C. (2010, June 23). A perfect fit. Retrieved from http://www.espn.com/action/skateboarding/news/story?id=5301983

Oinas-Kukkonen, H., & Harjumaa, M. (2008). A systematic

framework for designing and evaluating persuasive systems. In

H. Oinas-Kukkonen, P. Hasle, M. Harjumaa, K. Segerståhl, & P. Øhrstrøm (Eds.), Persuasive Technology: Third International Conference, PERSUASIVE 2008, Oulu, Finland, June 4-6, 2008. Proceedings (pp. 164-176). Berlin, Heidelberg: Springer Berlin Heidelberg.

Pfusterschmied, J., Lindinger, S., Buchecker, M., Stöggl, T., Wagner, H., & Müller, E. (2013). Effect of Instability Training Equipment on Lower Limb Kinematics and Muscle Activity. [Auswirkung instabiler Trainingsgeräte auf die Kinematik und

Muskelaktivität unterer Extremitäten]. Sportverletz Sportschaden, 27(01), 28-33. doi:10.1055/s-0032-1330725

Phinyomark, A., Thongpanja, S., Hu, H., Phukpattaranont, P., & Limsakul, C. (2012). The usefulness of mean and median frequencies in electromyography analysis. In G. R. Naik (Ed.), Computational Intelligence in Electromyography Analysis - A Perspective on Current Applications and Future Challenges (pp. Ch. 08). Rijeka: InTech.

Robinson, T., Agarwal, M., Chaudhary, S., Costello, B. E., & Simon, H. K. (2016). Pediatric hoverboard injuries: A need for enhanced safety measures and public awareness. Clinical Pediatrics, 55(11), 1078-1080. doi:10.1177/0009922816664066

Schwartz, F. P., Bottaro, M., Celes, R. S., Pereira, M. C., Rocha Júnior, V. d. A., & Nascimento, F. A. d. O. (2014). Study of muscle fatigue in isokinetic exercise with estimated conduction velocity and traditional electromyographic indicators. Revista Brasileira de Engenharia Biomédica, 30, 312-321.

Stirn, I., Jarm, T., Kapus, V. P., & Strojnik, V. (2013). Evaluation of mean power spectral frequency of EMG signal during 100 metre crawl. European Journal of Sport Science, 13(2), 164-173. doi:10.1080/17461391.2011.630100

van der Woude, L. H. V., de Groot, S., Bijker, K. E., Dekker, R., Th van Aanholt, P. C., Hoekstra, F., . . . Houdijk, H. (2010). 4th International State-of-the-art-congress ‘Rehabilitation: Mobility, Exercise & Sports’. Disability and Rehabilitation, 32(26), 2149-2154. doi:10.3109/09638288.2010.525289

Wolburg, T., Rapp, W., Rieger, J., & Horstmann, T. (2016). Muscle activity of leg muscles during unipedal stance on therapy devices with different stability properties. Physical Therapy in Sport, 17(Supplement C), 58-62. doi:10.1016/j.ptsp.2015.05.001

Yoon, S.-W. (2017). Analysis of the muscular activities of the tibialis anterior and gastrocnemius muscles in functional reach. Journal of Physical Therapy Science, 29(5), 851-853. doi:10.1589/jpts.29.851

Zuckerman, O., & Gal-Oz, A. (2014). Deconstructing gamification: Evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity. Personal and Ubiquitous Computing, 18(7), 1705-1719. doi:10.1007/s00779-014-0783-2

Downloads

Published

17-12-2017