Browse > Article

Comparison Analysis of Foot Pressure Characteristics during Walking in Stroke and Normal Elderly  

Jung, NamKyo (고려대학교 전기전자공학부)
Park, Se Jin (한국표준과학연구원 안전융합사업팀)
Kwon, Soon-Hyun (한국전자통신연구원 KSB 융합시스템연구실)
Jun, Jongarm (한국전자통신연구원 KSB 융합시스템연구실)
Yu, Jaehak (한국전자통신연구원 KSB 융합시스템연구실)
Publication Information
Journal of Platform Technology / v.9, no.3, 2021 , pp. 36-43 More about this Journal
Abstract
Stroke disease is one of the leading causes of death worldwide, and in particular, it is the most important causative disease that causes disability in the elderly. Since stroke disease often causes death or serious disability, active primary prevention and early detection of prognostic symptoms are very important. In particular, it is necessary to detect and accurately predict stroke prognostic symptoms in daily life and prompt diagnosis and treatment by medical staff. In recent studies, image analysis such as computed tomography (CT) or magnetic resonance imaging (MRI) is mostly used as a methodology for predicting prognostic symptoms in stroke patients. However, this approach has limitations in terms of long test time and high cost. In this paper, we experimented with clinical data on how stroke disease affects foot pressure in elderly in walking. Experiments have shown that there is a significant difference in * p < .05 in 12 cells between the stroke elderly and the normal elderly during walking. As a result, it is significant that we found a significant difference in the gait patterns in daily life of the stroke elderly and the normal elderly.
Keywords
Stroke Disease Analysis; Foot Pressure; Relative Load of Foot; Health Monitoring; Walking Analysis;
Citations & Related Records
연도 인용수 순위
  • Reference
1 World Health Organization. The top 10 causes of death. Available: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
2 J.H. Jeong, Y.D. Kim, E.J. Kim, S.H. Lee, "The effects of treadmill according to walking direction on the affected side lower limb muscle activity and walking characteristic in stroke patients," Journal of Korean Society for Neurotherapy, Vol. 20, No. 2, pp. 7-15, 2016.
3 Y.S. Kim, "Muscle activation patterns of stair gait in hemiparetic patients using surface electromyography," Journal of Adapted Physical Activity & Exercise, Vol. 14, No. 1, pp. 1-15, 2006.
4 T. Melai, T.H. IJzerman, N.C. Schaper, T.L.H. de Lange, P.J.B. Willemsb, K. Meijerb, A.G. Lieversed, H.H.C.M. Savelbergb, "Calculation of plantar pressure time integral, an alternative approach," Gait & Posture, Vol. 34, pp. 379-383, 2011.   DOI
5 Dynafoot, Techno Concept, https://technoconcept.com/
6 S. Kimmeskamp, E.M. Hennig, "Heel to toe motion characteristics in Parkinson patients during free walking," Clinical Biomechanics, Vol. 16, No. 9, pp. 806-812, 2001.   DOI
7 K.J. Nolan, M. Yarossi, P. Mclaughlin, "Changes in center of pressure displacement with the use of a foot drop stimulator in individuals with stroke," Clinical Biomechanics, Vol. 30, No. 7, pp. 755-761, 2015.   DOI
8 J. Yu, S. Park, S.H. Kwon, C.M.B. Ho, C.S. Pyo, H. Lee, "AI-based stroke disease prediction system using real-time electromyography signals," Applied Sciences, Vol. 10, No. 19, pp. 1-19, 2020.
9 Y. Choi, S.J. Park, J.J. Jun, C.S. Pyo, K.H. Cho, H.S. Lee, J. Yu, "Deep learning-based stroke disease prediction system using real-time bio signals," Sensors, Vol. 21, No. 13, pp. 1-17, 2021.   DOI
10 J.S. Chang, S.Y. Lee, M.H. Lee, Y.W. Choi, H.M. Lee, H.J. Oh, "The Correlations between gait speed and muscle activation or foot pressure in stroke patients," The Journal Korean Society of Physical Therapy, Vol. 21, No. 3, pp. 47-52, 2009.
11 J. Yu, S. Park, H. Lee, C.S. Pyo, Y.S. Lee, "An elderly health monitoring system using machine learning and In-depth analysis techniques on the NIH stroke scale," Mathematics, Vol. 8, No. 7, pp. 1-16, 2020.