Physical Therapy Rehabilitation Science

korean Academy of Physical Therapy Rehabilitation Science (물리치료재활과학회)
권호 표지
DOI QR코드

DOI QR Code

A Novel System with EMG-controlled FES Enhanced Gait Function and Energy Expenditure for Older Adults

  • Jang-hoon Shin (Applied Physical Therapy Lab, Department of Physical Therapy, College of Future Convergence, Sahmyook University) ;
  • Hye-Kang Park (Department of Physical Medicine and Rehabilitation, Rehabilitation Center, National Health Insurance Service Ilsan Hospital) ;
  • Joonyoung Jung (Human Enhancement & Assistive Technology Research Section, Artificial Intelligent Research Laboratory, Electronics and Telecommunications Research Institute) ;
  • Dong-Woo Lee (Wearable Computing Research Section, SW-Contents Basic Technology Research Group, SW-Contents Research Laboratory, Electronics and Telecommunications Research Institute) ;
  • Hyung cheol Shin (Wearable Computing Research Section, SW-Contents Basic Technology Research Group, SW-Contents Research Laboratory, Electronics and Telecommunications Research Institute) ;
  • Hwang-Jae Lee (Bot Fit T/F, New Biz T/F, Samsung Electronics) ;
  • Wan-hee Lee (Applied Physical Therapy Lab, Department of Physical Therapy, College of Future Convergence, Sahmyook University)
  • Received : 2024.04.25
  • Accepted : 2024.05.21
  • Published : 2024.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: This study was conducted to analyze the effect of wearable Electromyography-controlled functional electrical stimulation (EMG-controlled FES) System on Gait Function and cardiopulmonary metabolic efficiency during walking in older adults. Design: Cross-section study Methods: Total 22 older adult participants suitable to selection criteria of this study participated in this study. The EMG-controlled FES System, which functions as a wearable physical activity assist FES system was used. All participations performed randomly assigned two conditions (Non-FES assist [NFA], FES assist [FA]) of walking. In all conditions, spatio-temporal parameters and kinematics and kinetics parameters during walking was collected via 3D motion capture system and 6 minutes walking test (6MWT) and metabolic cost during walking and stairs climbing was collected via a portable metabolic device (COSMED K5, COSMED Srl, Roma, Italy). Results: In Spatio-temporal parameters aspects, The EMG-controlled FES system significantly improved gait functions measurements of older adults with sarcopenia at walking in comparison to the NFA condition (P<0.05). Hip, knee and ankle joint range of motion increased at walking in FA condition compared to the NFA condition (P<0.05). In the FA condition, moment and ground reaction force was changed like normal gait during walking of older adults in comparison to the NFA condition (P<0.05). The EMG-controlled FES system significantly reduced net cardiopulmonary metabolic energy cost, net energy expenditure measurement at stairs climbing (P<0.05). Conclusions: This study demonstrated that EMG-controlled FES is a potentially useful gait-assist system for improving gait function by making joint range of motion and moment properly.

Keywords

Acknowledgement

This study was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2017-0-00050, Development of Human Enhancement Technology for auditory and muscle support) and by a grant from the NRF (NRF-2016R1A6A3A11930931 and NRF-2018R1D1A1B07042870), which is funded by the Korean government.

References

  1. Zampieri, S., et al., Physical exercise in aging: nine weeks of leg press or electrical stimulation training in 70 years old sedentary elderly people. Eur J Transl Myol, 2015. 25(4): p. 237. 
  2. Nomura, T., et al., Assessment of lower extremity muscle mass, muscle strength, and exercise therapy in elderly patients with diabetes mellitus. Environ Health Prev Med, 2018. 23(1): p. 20. 
  3. Ng, T.P., et al., Nutritional, Physical, Cognitive, and Combination Interventions and Frailty Reversal Among Older Adults: A Randomized Controlled Trial. Am J Med, 2015. 128(11): p. 1225-1236.e1. 
  4. Villareal, D.T., et al., Weight loss, exercise, or both and physical function in obese older adults. N Engl J Med, 2011. 364(13): p. 1218-29. 
  5. Kim, H.K., et al., Effects of exercise and amino acid supplementation on body composition and physical function in community-dwelling elderly Japanese sarcopenic women: a randomized controlled trial. J Am Geriatr Soc, 2012. 60(1): p. 16-23. 
  6. Hamed, A., et al., Exercises of dynamic stability under unstable conditions increase muscle strength and balance ability in the elderly. Scand J Med Sci Sports, 2018. 28(3): p. 961-971. 
  7. Langeard, A., et al., Does neuromuscular electrical stimulation training of the lower limb have functional effects on the elderly?: A systematic review. Exp Gerontol, 2017. 91: p. 88-98. 
  8. Sajer, S., G.S. Guardiero, and B.M. Scicchitano, Myokines in Home-Based Functional Electrical Stimulation-Induced Recovery of Skeletal Muscle in Elderly and Permanent Denervation. Eur J Transl Myol, 2018. 28(4): p. 7905. 
  9. Lexell, J., Human aging, muscle mass, and fiber type composition. J Gerontol A Biol Sci Med Sci, 1995. 50 Spec No: p. 11-6. 
  10. Karavidas, A., et al., Functional electrical stimulation is more effective in severe symptomatic heart failure patients and improves their adherence to rehabilitation programs. J Card Fail, 2010. 16(3): p. 244-9. 
  11. Awad, L.N., et al., Reducing The Cost of Transport and Increasing Walking Distance After Stroke: A Randomized Controlled Trial on Fast Locomotor Training Combined With Functional Electrical Stimulation. Neurorehabil Neural Repair, 2016. 30(7): p. 661-70. 
  12. Bauer, P., et al., Functional electrical stimulation-assisted active cycling--therapeutic effects in patients with hemiparesis from 7 days to 6 months after stroke: a randomized controlled pilot study. Arch Phys Med Rehabil, 2015. 96(2): p. 188-96. 
  13. Cho, M.K., et al., Treadmill gait training combined with functional electrical stimulation on hip abductor and ankle dorsiflexor muscles for chronic hemiparesis. Gait Posture, 2015. 42(1): p. 73-8. 
  14. Estigoni, E.H., et al., Evoked EMG and muscle fatigue during isokinetic FES-cycling in individuals with SCI. Neuromodulation, 2011. 14(4): p. 349-55; discussion 355. 
  15. Niu, C.M., et al., Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions. IEEE Trans Neural Syst Rehabil Eng, 2019. 27(2): p. 256-264. 
  16. Park, H.K., et al., A wearable electromyography-controlled functional electrical stimulation system improves balance, gait function, and symmetry in older adults. Technol Health Care, 2021. 
  17. Galle, S., et al., Exoskeleton plantarflexion assistance for elderly. Gait Posture, 2017. 52: p. 183-188. 
  18. Gobbo, M., et al., Muscle motor point identification is essential for optimizing neuromuscular electrical stimulation use. J Neuroeng Rehabil, 2014. 11: p. 17. 
  19. Muyor, J.M., et al., Electromyographic activity in the gluteus medius, gluteus maximus, biceps femoris, vastus lateralis, vastus medialis and rectus femoris during the Monopodal Squat, Forward Lunge and Lateral Step-Up exercises. PLoS One, 2020. 15(4): p. e0230841. 
  20. Hermens, H.J., et al., Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol, 2000. 10(5): p. 361-74. 
  21. Kendall, F.P., et al., Muscles: Testing and function, with posture and pain (Kendall, Muscles). Fifth nort. LWW, 2005. 
  22. Yeom, H. and Y.H. Chang, Autogenic EMG-controlled functional electrical stimulation for ankle dorsiflexion control. J Neurosci Methods, 2010. 193(1): p. 118-25. 
  23. Jung, J., et al., Volitional EMG Estimation Method during Functional Electrical Stimulation by Dual-Channel Surface EMGs. Sensors, 2021. 21(23): p. 8015. 
  24. Jung, J., et al. Volitional EMG Controlled Wearable FES System for Lower Limb Rehabilitation. in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. IEEE. 
  25. DeBlois, J.P., L.E. White, and T.V. Barreira, Reliability and validity of the COSMED K5 portable metabolic system during walking. Eur J Appl Physiol, 2021. 121(1): p. 209-217. 
  26. Raa, A., et al., Validation of a point-of-care capillary lactate measuring device (Lactate Pro 2). Scand J Trauma Resusc Emerg Med, 2020. 28(1): p. 83. 
  27. White, G.E. and G.D. Wells, The effect of on-hill active recovery performed between runs on blood lactate concentration and fatigue in alpine ski racers. J Strength Cond Res, 2015. 29(3): p. 800-6. 
  28. Kadaba, M.P., H.K. Ramakrishnan, and M.E. Wootten, Measurement of lower extremity kinematics during level walking. J Orthop Res, 1990. 8(3): p. 383-92. 
  29. Lee, S.H., et al., Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults. J Neuroeng Rehabil, 2017. 14(1): p. 123. 
  30. Caballero-Garcia, A., et al., Effect of Vitamin D Supplementation on Muscle Status in Old Patients Recovering from COVID-19 Infection. Medicina (Kaunas), 2021. 57(10). 
  31. Wonsetler, E.C. and M.G. Bowden, A systematic review of mechanisms of gait speed change post-stroke. Part 1: spatiotemporal parameters and asymmetry ratios. Top Stroke Rehabil, 2017. 24(6): p. 435-446. 
  32. Lee, H.J., et al., A Wearable Hip Assist Robot Can Improve Gait Function and Cardiopulmonary Metabolic Efficiency in Elderly Adults. IEEE Trans Neural Syst Rehabil Eng, 2017. 25(9): p. 1549-1557. 
  33. Balasubramanian, C.K., et al., Relationship between step length asymmetry and walking performance in subjects with chronic hemiparesis. Arch Phys Med Rehabil, 2007. 88(1): p. 43-9. 
  34. Stenum, J. and J.T. Choi, Step time asymmetry but not step length asymmetry is adapted to optimize energy cost of split-belt treadmill walking. J Physiol, 2020. 598(18): p. 4063-4078. 
  35. Kamide, N., et al., The effect of the interaction between fall-related self-efficacy and gait function on the occurrence of falls in community-dwelling older people. Aging Clin Exp Res, 2021. 33(10): p. 2715-2722. 
  36. Niederer, D., et al., The age-related decline in spatiotemporal gait characteristics is moderated by concerns of falling, history of falls & diseases, and sociodemographic-anthropometric characteristics in 60-94 years old adults. Eur Rev Aging Phys Act, 2021. 18(1): p. 19. 
  37. Martini, E., et al., Gait training using a robotic hip exoskeleton improves metabolic gait efficiency in the elderly. Sci Rep, 2019. 9(1): p. 7157. 
  38. Jin, J.-K., D.-T. Lee, and M.-C. Lee, Exercise and lactate shuttle. Asian J Kinesiol, 2006. 8(2): p. 85-92. 
  39. Spriet, L.L., R.A. Howlett, and G.J. Heigenhauser, An enzymatic approach to lactate production in human skeletal muscle during exercise. Medicine and science in sports and exercise, 2000. 32(4): p. 756-763. 
  40. Katz, S., et al., STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. Jama, 1963. 185: p. 914-9. 
  41. Freeman, C.T., et al., Iterative learning control in health care: Electrical stimulation and robotic-assisted upper-limb stroke rehabilitation. IEEE Control Systems Magazine, 2012. 32(1): p. 18-43. 
  42. Lyons, G.M., et al., A review of portable FES-based neural orthoses for the correction of drop foot. IEEE Transactions on neural systems and rehabilitation engineering, 2002. 10(4): p. 260-279. 
  43. Riener, R. and T. Fuhr, Patient-driven control of FES-supported standing up: a simulation study. IEEE Transactions on rehabilitation engineering, 1998. 6(2): p. 113-124. 
  44. Riener, R., et al., Patient-driven control of FES-supported standing up and sitting down: experimental results. IEEE Transactions on rehabilitation engineering, 2000. 8(4): p. 523-529. 
  45. Ha, K.H., S.A. Murray, and M. Goldfarb, An approach for the cooperative control of FES with a powered exoskeleton during level walking for persons with paraplegia. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2015. 24(4): p. 455-466.