EXPLORATION OF VIBROTACTILE BIOFEEDBACK STRATEGIES TO INDUCE STANCE TIME ASYMMETRIES

Rafael Escamilla-Nunez; Harry  Sivasambu; Jan Andrysek

doi:10.33137/cpoj.v5i1.36744

Authors

Rafael Escamilla-Nunez 1) Institute of Biomedical Engineering, University of Toronto, Toronto, Canada; 2) Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada. https://orcid.org/0000-0002-2739-878X
Harry Sivasambu Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada. https://orcid.org/0000-0002-1205-8811
Jan Andrysek 1) Institute of Biomedical Engineering, University of Toronto, Toronto, Canada; 2) Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada. https://orcid.org/0000-0002-4976-1228

DOI:

https://doi.org/10.33137/cpoj.v5i1.36744

Keywords:

Gait, Human Movement, Biofeedback, Learning Effect, Motor Control, Rehabilitation, Short-term Retention, Symmetry Ratio, Vibrotactile Feedback, Wearable Systems

Abstract

BACKGROUND: Gait symmetry is the degree of equality of biomechanical parameters between limbs within a gait cycle. Human gait is highly symmetrical; however, in the presence of pathology, gait often lacks symmetry. Biofeedback (BFB) systems have demonstrated the potential to reduce gait asymmetry, improve gait function, and benefit overall long-term musculoskeletal health.

OBJECTIVE(S): The aim of this study was to develop a BFB system and evaluate three unique BFB strategies, including bidirectional control – constant vibration (BC), bidirectional control – variable vibration (BV), and unidirectional control – variable vibration (UV) relevant to gait symmetry. The assessed feedback strategies were a combination of vibration frequency/amplitude levels, vibration thresholds, and vibrotactile stimuli from one and two vibrating motors (tactors). Learning effect and short-term retention were also assessed.

METHODOLOGY: Testing was performed using a custom BFB system that induces stance time asymmetries to modulate temporal gait symmetry. The BFB system continuously monitors specific gait events (heel-strike and toe-off) and calculates the symmetry ratio, based on the stance time of both limbs to provide real-time biomechanical information via the vibrating motors. Overall walking performance of ten (n=10) able-bodied individuals (age 24.8 ± 4.4 years) was assessed via metrics of symmetry ratio, symmetry ratio error, walking speed, and motor's vibration percentages.

FINDINGS: All participants utilized BFB somatosensory information to modulate their symmetry ratio. UV feedback produced a greater change in symmetry ratio, and it came closer to the targeted symmetry ratio. Learning or short-term retention effects were minimal. Walking speeds were reduced with feedback compared to no feedback; however, UV walking speeds were significantly faster compared to BV and BC.

CONCLUSION: The outcomes of this study provide new insights into the development and implementation of feedback strategies for gait retraining BFB systems that may ultimately benefit individuals with pathological gait. Future work should assess longer-term use and long-term learning and retention effects of BFB systems in the populations of interest.

Layman's Abstract

Healthy walking is usually highly symmetrical with the same movements occurring on both sides of the body. However, certain disorders can cause abnormal and asymmetrical walking movements. Biofeedback can improve the movements during walking. This study used a custom biofeedback system to test three ways of applying biofeedback including having one and two motors that vibrated in unique ways. The biofeedback system was set up to guide participants to change their normal walking pattern to be less symmetrical. Walking movements of ten young able-bodied individuals were measured while walking with the biofeedback system. The results showed a change in walking symmetry for all participants. Using a single vibrating motor resulted in the greatest changes in walking symmetry. The changes in walking symmetry occurred only when using biofeedback, and walking patterns quickly returned to normal when the biofeedback was turned off. Overall, all feedback methods caused the users to walk slower than their typical walking speed. These findings provide important new information about the changes in walking caused by different biofeedback methods. Future work should evaluate long-term effects of biofeedback methods in the populations of interest.

Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/36744/28677

How To Cite: Escamilla-Nunez R, Sivasambu H, Andrysek J. Exploration of vibrotactile biofeedback strategies to induce stance time asymmetries. Canadian Prosthetics & Orthotics Journal. 2022; Volume 5, Issue 1, No.2. https://doi.org/10.33137/cpoj.v5i1.36744

Corresponding Author: Rafael Escamilla-Nunez,
Institute of Biomedical Engineering, University of Toronto, Toronto, Canada.
E-Mail: rafael.escamilla@mail.utoronto.ca
ORCID ID: https://orcid.org/0000-0002-2739-878X

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References

Kaas JH, Merzenich MM, Killackey HP. The reorganization of somatosensory cortex following peripheral nerve damage in adult and developing mammals. Annu Rev Neurosci. 1983;6:325–56. DOI:10.1146/annurev.ne.06.030183.001545 DOI: https://doi.org/10.1146/annurev.ne.06.030183.001545

Eshraghi A., Andrysek J. (2018) Influence of Prosthetic Socket Design and Fitting on Gait. In: Müller B., Wolf S. (eds) Handbook of Human Motion. Springer, Cham. Pages 1383-1406. DOI: 10.1007/ 978-3-319-14418-4_76 DOI: https://doi.org/10.1007/978-3-319-14418-4_76

Guertin PA. Central pattern generator for locomotion: anatomical, physiological, and pathophysiological considerations. Front Neurol. 2013;3:1–15. DOI:10.3389/fneur.2012.00183 DOI: https://doi.org/10.3389/fneur.2012.00183

Sadeghi H, Allard P, Prince F, Labelle H. Symmetry and limb dominance in able-bodied gait: a review. Gait Posture. 2000;12:34–45. DOI:10.1016/S0966-6362(00)00070-9 DOI: https://doi.org/10.1016/S0966-6362(00)00070-9

Shen X, Mak MKY. Balance and gait training with augmented feedback improves balance confidence in people with parkinson’s disease. Neurorehabil Neural Repair. 2014;28:524–35. DOI:10.1177/1545968313517752 DOI: https://doi.org/10.1177/1545968313517752

MacIntosh A, Lam E, Vigneron V, Vignais N, Biddiss E. Biofeedback interventions for individuals with cerebral palsy: a systematic review. Disabil Rehabil. 2019;41:2369–91. DOI: 10.1080/09638288.2018.1468933 DOI: https://doi.org/10.1080/09638288.2018.1468933

Afzal MR, Pyo S, Oh M-K, Park YS, Lee B-C, Yoon J. Haptic based gait rehabilitation system for stroke patients. In 2016 IEEE/RSJ Int Conf Intell Robot Syst. 2016;3198–203. DOI:10.1109/IROS.2016.7759494 DOI: https://doi.org/10.1109/IROS.2016.7759494

Thrasher TA, Flett HM, Popovic MR. Gait training regimen for incomplete spinal cord injury using functional electrical stimulation. Spinal Cord. 2006;44:357–61. DOI:10.1038/sj.sc.3101864 DOI: https://doi.org/10.1038/sj.sc.3101864

Sagawa Y, Turcot K, Armand S, Thevenon A, Vuillerme N, Watelain E. Biomechanics and physiological parameters during gait in lower-limb amputees: a systematic review. Gait Posture. 2011;33:511–26. DOI:10.1016/j.gaitpost.2011.02.003 DOI: https://doi.org/10.1016/j.gaitpost.2011.02.003

Nolan L, Wit A, Dudziñski K, Lees A, Lake M, Wychowañski M. Adjustments in gait symmetry with walking speed in trans-femoral and trans-tibial amputees. Gait Posture. 2003;17:142–51. DOI:10.1016/S0966-6362(02)00066-8 DOI: https://doi.org/10.1016/S0966-6362(02)00066-8

Miller WC, Deathe AB, Speechley M, Koval J. The influence of falling, fear of falling, and balance confidence on prosthetic mobility and social activity among individuals with a lower extremity amputation. Arch Phys Med Rehabil. 2001;82:1238–44. DOI: 10.1053/apmr.2001.25079 DOI: https://doi.org/10.1053/apmr.2001.25079

Seymour R. Prosthetics and orthotics: lower limb and spinal. Lippincott Williams & Wilkins; 2002.

Staiano AE, Flynn R. Therapeutic uses of active videogames: a systematic review. Games Health J. 2014;3:351–65. DOI:10.1089/ g4h.2013.0100 DOI: https://doi.org/10.1089/g4h.2013.0100

Darter BJ, Wilken JM. Gait training with virtual reality–based real-time feedback: improving gait performance following transfemoral amputation. Phys Ther. 2011;91:1385–94. DOI:10.2522/ptj.20100360 DOI: https://doi.org/10.2522/ptj.20100360

Van Gelder LMA, Barnes A, Wheat JS, Heller BW. The use of biofeedback for gait retraining: A mapping review. Clin Biomech. 2018;59:159–66. DOI:10.1016/j.clinbiomech.2018.09.020 DOI: https://doi.org/10.1016/j.clinbiomech.2018.09.020

Escamilla-Nunez R, Michelini A, Andrysek J. Biofeedback systems for gait rehabilitation of individuals with lower-limb amputation: a systematic review. Sensors. 2020;20:1628. DOI:10.3390/s20061628 DOI: https://doi.org/10.3390/s20061628

Giggins OM, Persson U, Caulfield B. Biofeedback in rehabilitation. J Neuroeng Rehabil. 2013;10:60. DOI:10.1186/1743-0003-10-60 DOI: https://doi.org/10.1186/1743-0003-10-60

Shull PB, Damian DD. Haptic wearables as sensory replacement, sensory augmentation and trainer – a review. J Neuroeng Rehabil. 2015;12:59. DOI:10.1186/s12984-015-0055-z DOI: https://doi.org/10.1186/s12984-015-0055-z

Lee B-C, Fung A, Thrasher TA. The effects of coding schemes on vibrotactile biofeedback for dynamic balance training in parkinson’s disease and healthy elderly individuals. IEEE Trans Neural Syst Rehabil Eng. 2018;26:153–60. DOI:10.1109/ TNSRE.2017.2762239 DOI: https://doi.org/10.1109/TNSRE.2017.2762239

Chamorro-Moriana G, Moreno A, Sevillano J. Technology-based feedback and its efficacy in improving gait parameters in patients with abnormal gait: a systematic review. Sensors. 2018;18:142. DOI:10.3390/s18010142 DOI: https://doi.org/10.3390/s18010142

Shi S, Leineweber MJ, Andrysek J. Exploring the tactor configurations of vibrotactile feedback systems for use in lower-limb prostheses. J Vib Acoust. 2019;141. DOI:10.1115/1.4043610 DOI: https://doi.org/10.1115/1.4043610

Sharma A, Leineweber MJ, Andrysek J. Effects of cognitive load and prosthetic liner on volitional response times to vibrotactile feedback. J Rehabil Res Dev. 2016;53:473–82. DOI:10.1682/ JRRD.2015.04.0060 DOI: https://doi.org/10.1682/JRRD.2016.04.0060

Sharma A, Torres-Moreno R, Zabjek K, Andrysek J. Toward an artificial sensory feedback system for prosthetic mobility rehabilitation: examination of sensorimotor responses. J Rehabil Res Dev. 2014;51:907–17. DOI:10.1682/JRRD.2013.07.0164 DOI: https://doi.org/10.1682/JRRD.2013.07.0164

Leineweber MJ, Shi S, Andrysek J. A Method for evaluating timeliness and accuracy of volitional motor responses to vibrotactile stimuli. J Vis Exp. 2016;2016. DOI:10.3791/54223 DOI: https://doi.org/10.3791/54223

Afzal MR, Lee H, Eizad A, Lee CH, Oh M-K, Yoon J. Evaluation of novel vibrotactile biofeedback coding schemes for gait symmetry training. 2019 2nd IEEE Int Conf Soft Robot. 2019, 540–5. DOI:10.1109/ROBOSOFT.2019.8722751 DOI: https://doi.org/10.1109/ROBOSOFT.2019.8722751

Lee B-C, Thrasher TA, Fisher SP, Layne CS. The effects of different sensory augmentation on weight-shifting balance exercises in Parkinson’s disease and healthy elderly people: a proof-of-concept study. J Neuroeng Rehabil. 2015;12:75. DOI:10.1186/s12984-015-0064-y DOI: https://doi.org/10.1186/s12984-015-0064-y

Crea S, Edin BB, Knaepen K, Meeusen R, Vitiello N. Time-discrete vibrotactile feedback contributes to improved gait symmetry in patients with lower limb amputations: case series. Phys Ther. 2017;97:198–207. DOI:10.2522/ptj.20150441 DOI: https://doi.org/10.2522/ptj.20150441

Lopez-Meyer P, Fulk GD, Sazonov ES. Automatic detection of temporal gait parameters in poststroke individuals. IEEE Trans Inf Technol Biomed. 2011; 15:594–601. DOI:10.1109/TITB.2011. 2112773 DOI: https://doi.org/10.1109/TITB.2011.2112773

Patterson KK, Gage WH, Brooks D, Black SE, McIlroy WE. Evaluation of gait symmetry after stroke: a comparison of current methods and recommendations for standardization. Gait Posture. 2010;31:241–6. DOI:10.1016/j.gaitpost.2009.10.014 DOI: https://doi.org/10.1016/j.gaitpost.2009.10.014

Redd CB, Bamberg SJM. A wireless sensory feedback device for real-time gait feedback and training. IEEE/ASME Trans Mechatronics. 2012;17:425–33. DOI:10.1109/TMECH.2012. 2189014 DOI: https://doi.org/10.1109/TMECH.2012.2189014

Pagel A, Arieta AH, Riener R, Vallery H. Effects of sensory augmentation on postural control and gait symmetry of transfemoral amputees: a case description. Med Biol Eng Comput. 2016;54:1579–89. DOI:10.1007/s11517-015-1432-2 DOI: https://doi.org/10.1007/s11517-015-1432-2

Plauche A, Villarreal D, Gregg RD. A haptic feedback system for phase-based sensory restoration in above-knee prosthetic leg users. IEEE Trans Haptics. 2016;9:421–6. DOI:10.1109/ TOH.2016.2580507 DOI: https://doi.org/10.1109/TOH.2016.2580507

Maldonado-Contreras J, Marayong P, Khoo I-H, Rivera R, Ruhe B, Wu W. Proprioceptive improvements of lower-limb amputees under training with a vibrotactile device — a pilot study. 2017 IEEE Healthc Innov Point Care Technol. 2017;229–32. DOI: 10.1109/HIC.2017.8227626 DOI: https://doi.org/10.1109/HIC.2017.8227626

Crea S, Cipriani C, Donati M, Carrozza MC, Vitiello N. Providing time-discrete gait information by wearable feedback apparatus for lower-limb amputees: usability and functional validation. IEEE Trans Neural Syst Rehabil Eng. 2015;23:250–7. DOI: 10.1109/TNSRE.2014.2365548 DOI: https://doi.org/10.1109/TNSRE.2014.2365548

Kitago TO, Krakauer JW. Motor learning principles for neurorehabilitation. Handb Clin Neurol. 2013;110:93-103. DOI: 10.1016/B978-0-444-52901-5.00008-3 DOI: https://doi.org/10.1016/B978-0-444-52901-5.00008-3

Cech DJ, Martin S “Tink.” Functional Movement Development Across the Life Span. Third Edition. Elsevier. 2012; p. 68–87. DOI:10.1016/B978-1-4160-4978-4.00004-1 DOI: https://doi.org/10.1016/B978-1-4160-4978-4.00004-1

Martini E, Cesini I, D’Abbraccio J, Arnetoli G, Doronzio S, Giffone A, et al. Increased symmetry of lower-limb amputees walking with concurrent bilateral vibrotactile feedback. IEEE Trans Neural Syst Rehabil Eng. 2021;29:74–84. DOI:10.1109/ TNSRE.2020.3034521 DOI: https://doi.org/10.1109/TNSRE.2020.3034521

Gopalai AA, Lan BL, Gouwanda D. Stochastic resonance for enhancing sensory perception: An emerging trend for ADL rehabilitation. TENCON 2015 - 2015 IEEE Region 10 Conference, 2015, pp. 1-5. DOI:10.1109/TENCON.2015.7373098 DOI: https://doi.org/10.1109/TENCON.2015.7373098

Collins JJ, Priplata AA, Gravelle DC, Niemi J, Harry J, Lipsitz LA. Noise-enhanced human sensorimotor function. IEEE Eng Med Biol Mag. 2003;22:76–83. DOI:10.1109/MEMB.2003.1195700 DOI: https://doi.org/10.1109/MEMB.2003.1195700

Cochrane DJ. The potential neural mechanisms of acute indirect vibration. J Sports Sci Med. 2011;10:19–30.