Abnormal synergistic gait mitigation in acute stroke using an innovative ankle-knee-hip interlimb humanoid robot: a preliminary randomized controlled trial

Chanhee Park, Mooyeon Oh-Park, Amy Bialek, Kathleen Friel, Dylan Edwards, Joshua Sung H You, Chanhee Park, Mooyeon Oh-Park, Amy Bialek, Kathleen Friel, Dylan Edwards, Joshua Sung H You

Abstract

Abnormal spasticity and associated synergistic patterns are the most common neuromuscular impairments affecting ankle-knee-hip interlimb coordinated gait kinematics and kinetics in patients with hemiparetic stroke. Although patients with hemiparetic stroke undergo various treatments to improve gait and movement, it remains unknown how spasticity and associated synergistic patterns change after robot-assisted and conventional treatment. We developed an innovative ankle-knee-hip interlimb coordinated humanoid robot (ICT) to mitigate abnormal spasticity and synergistic patterns. The objective of the preliminary clinical trial was to compare the effects of ICT combined with conventional physical therapy (ICT-C) and conventional physical therapy and gait training (CPT-G) on abnormal spasticity and synergistic gait patterns in 20 patients with acute hemiparesis. We performed secondary analyses aimed at elucidating the biomechanical effects of Walkbot ICT on kinematic (spatiotemporal parameters and angles) and kinetic (active force, resistive force, and stiffness) gait parameters before and after ICT in the ICT-C group. The intervention for this group comprised 60-min conventional physical therapy plus 30-min robot-assisted training, 7 days/week, for 2 weeks. Significant biomechanical effects in knee joint kinematics; hip, knee, and ankle active forces; hip, knee, and ankle resistive forces; and hip, knee, and ankle stiffness were associated with ICT-C. Our novel findings provide promising evidence for conventional therapy supplemented by robot-assisted therapy for abnormal spasticity, synergistic, and altered biomechanical gait impairments in patients in the acute post-stroke recovery phase.Trial Registration: Clinical Trials.gov identifier NCT03554642 (14/01/2020).

Conflict of interest statement

The authors declare no competing interests.

© 2021. The Author(s).

Figures

Figure 1
Figure 1
The control scheme of the position-based impedance control for gait rehabilitation. ROB reaction torque observer.
Figure 2
Figure 2
Lower-extremity kinematic joint angle calculation in ICT system. ICT innovative ankle–knee–hip interlimb coordinated humanoid robot.
Figure 3
Figure 3
Flow chart. CPT-G conventional physical therapy and gait training, ICT-C ankle–knee–hip interlimb coordinated humanoid robot combined with conventional physical therapy.
Figure 4
Figure 4
Paretic hip and knee angle kinematics in ICT-C group (unit: degree). ICT-C ankle–knee–hip interlimb coordinated humanoid robot combined with conventional physical therapy; *Denotes significance at P < 0.05; Number, mean; Bar, standard deviation.

References

    1. Kim HY, Park GL, Shin JH, You SH. Neuroplastic effects of end-effector robotic gait training for hemiparetic stroke: A randomised controlled trial. Sci. Rep. 2020;10:12461. doi: 10.1038/s41598-020-69367-3.
    1. Morone G, et al. Rehabilitative devices for a top-down approach. Expert Rev. Med. Devices. 2019;16:187–195. doi: 10.1080/17434440.2019.1574567.
    1. Morone G, et al. Robot-assisted gait training for stroke patients: Current state of the art and perspectives of robotics. Neuropsychiatr. Dis. Treat. 2017;13:1303–1311. doi: 10.2147/ndt.S114102.
    1. Cheng PY, Lai PY. Comparison of Exoskeleton Robots and End-Effector Robots on Training Methods and Gait Biomechanics. Springer; 2013. pp. 258–266.
    1. Mehrholz J, Pohl M. Electromechanical-assisted gait training after stroke: A systematic review comparing end-effector and exoskeleton devices. J. Rehabil. Med. 2012;44:193–199. doi: 10.2340/16501977-0943.
    1. Molteni F, et al. Gait recovery with an overground powered exoskeleton: A randomized controlled trial on subacute stroke subjects. Brain Sci. 2021 doi: 10.3390/brainsci11010104.
    1. Karunakaran KK, et al. Effect of robotic exoskeleton gait training during acute stroke on functional ambulation. NeuroRehabilitation. 2021;46:493–503. doi: 10.3233/NRE-210010.
    1. Turner DL, Ramos-Murguialday A, Birbaumer N, Hoffmann U, Luft A. Neurophysiology of robot-mediated training and therapy: A perspective for future use in clinical populations. Front. Neurol. 2013;4:184. doi: 10.3389/fneur.2013.00184.
    1. Park CH, Hwang JS, You JSH. Comparative effectiveness of robot-interactive gait training with and without ankle robotic control in patients with brain damage. J. Mech. Med. Biol. 2021;1:2140035. doi: 10.1142/S0219519421400352.
    1. Mooney LM, Herr HM. Biomechanical walking mechanisms underlying the metabolic reduction caused by an autonomous exoskeleton. J. Neuroeng. Rehabil. 2016;13:4. doi: 10.1186/s12984-016-0111-3.
    1. Calabrò RS, et al. Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now? Neurol. Sci. 2016;37:503–514. doi: 10.1007/s10072-016-2474-4.
    1. Barroso FO, et al. Combining muscle synergies and biomechanical analysis to assess gait in stroke patients. J. Biomech. 2017;63:98–103. doi: 10.1016/j.jbiomech.2017.08.006.
    1. Boudarham J, et al. Variations in kinematics during clinical gait analysis in stroke patients. PLoS ONE. 2013;8:e66421. doi: 10.1371/journal.pone.0066421.
    1. Li S, Francisco GE, Zhou P. Post-stroke hemiplegic gait: New perspective and insights. Front. Physiol. 2018;9:1021. doi: 10.3389/fphys.2018.01021.
    1. Olney SJ, Richards C. Hemiparetic gait following stroke. Part I: Characteristics. Gait Posture. 1996;4:136–148. doi: 10.1016/0966-6362(96)01063-6.
    1. Yelnik A, Albert T, Bonan I, Laffont I. A clinical guide to assess the role of lower limb extensor overactivity in hemiplegic gait disorders. Stroke. 1999;30:580–585. doi: 10.1161/01.str.30.3.580.
    1. von Schroeder HP, Coutts RD, Lyden PD, Billings E, Jr, Nickel VL. Gait parameters following stroke: A practical assessment. J. Rehabil. Res. Dev. 1995;32:25–31.
    1. Duval K, Luttin K, Lam T. Neuromuscular strategies in the paretic leg during curved walking in individuals post-stroke. J. Neurophysiol. 2011;106:280–290. doi: 10.1152/jn.00657.2010.
    1. Balaban B, Tok F. Gait disturbances in patients with stroke. PM&R. 2014;6:635–642. doi: 10.1016/j.pmrj.2013.12.017.
    1. Cruz-Montecinos C, et al. Changes in muscle activity patterns and joint kinematics during gait in hemophilic arthropathy. Front. Physiol. 2020 doi: 10.3389/fphys.2019.01575.
    1. Fregly BJ, Boninger ML, Reinkensmeyer DJ. Personalized neuromusculoskeletal modeling to improve treatment of mobility impairments: A perspective from european research sites. J. Neuroeng. Rehabil. 2012;9:18. doi: 10.1186/1743-0003-9-18.
    1. Patten C, Lexell J, Brown HE. Weakness and strength training in persons with poststroke hemiplegia: Rationale, method, and efficacy. J. Rehabil. Res. Dev. 2004;41:293–312. doi: 10.1682/jrrd.2004.03.0293.
    1. Kim CM, Eng JJ. Magnitude and pattern of 3D kinematic and kinetic gait profiles in persons with stroke: Relationship to walking speed. Gait Posture. 2004;20:140–146. doi: 10.1016/j.gaitpost.2003.07.002.
    1. van Kammen K, Boonstra AM, van der Woude LHV, Reinders-Messelink HA, den Otter R. Differences in muscle activity and temporal step parameters between Lokomat guided walking and treadmill walking in post-stroke hemiparetic patients and healthy walkers. J. Neuroeng. Rehabil. 2017;14:32. doi: 10.1186/s12984-017-0244-z.
    1. Lünenburger L, Colombo G, Riener R. Biofeedback for robotic gait rehabilitation. J. Neuroeng. Rehabil. 2007;4:1. doi: 10.1186/1743-0003-4-1.
    1. Park CH, et al. Effects of innovative hip-knee-ankle interlimb coordinated robot training on ambulation, cardiopulmonary function, depression, and fall confidence in acute hemiplegia. NeuroRehabilitation. 2020;46:577–587. doi: 10.3233/nre-203086.
    1. Goffredo M, et al. Stroke gait rehabilitation: A comparison of end-effector, overground exoskeleton, and conventional gait training. Appl. Sci. 2019;9:2627. doi: 10.3390/app9132627.
    1. Molteni F, Gasperini G, Cannaviello G, Guanziroli E. Exoskeleton and end-effector robots for upper and lower limbs rehabilitation: Narrative review. PM&R. 2018;10:S174–S188. doi: 10.1016/j.pmrj.2018.06.005.
    1. De Luca A, et al. Recovery and compensation after robotic assisted gait training in chronic stroke survivors. Disabil. Rehabil. Assist. Technol. 2019;14:826–838. doi: 10.1080/17483107.2018.1466926.
    1. Park IJ, et al. Comparative effects of different assistance force during robot-assisted gait training on locomotor functions in patients with subacute stroke: An assessor-blind, randomized controlled trial. Am. J. Phys. Med. Rehabil. 2019;98:58–64. doi: 10.1097/phm.0000000000001027.
    1. Park JH, Shin YI, You JSH, Park MS. Comparative effects of robotic-assisted gait training combined with conventional physical therapy on paretic hip joint stiffness and kinematics between subacute and chronic hemiparetic stroke. NeuroRehabilitation. 2018;42:181–190. doi: 10.3233/nre-172234.
    1. Kim SY, et al. Effects of innovative walkbot robotic-assisted locomotor training on balance and gait recovery in hemiparetic stroke: A prospective, randomized, experimenter blinded case control study with a four-week follow-up. IEEE Trans. Neural Syst. Rehabil. Eng. 2015;23:636–642. doi: 10.1109/tnsre.2015.2404936.
    1. Yang HE, et al. Structural and functional improvements due to robot-assisted gait training in the stroke-injured brain. Neurosci. Lett. 2017;637:114–119. doi: 10.1016/j.neulet.2016.11.039.
    1. Jung JH, Lee NG, You JH, Lee DC. Validity and feasibility of intelligent Walkbot system. Electron. Lett. 2009;45:1016–1017. doi: 10.1049/el.2009.0879.
    1. Lerner ZF, Damiano DL, Bulea TC. A lower-extremity exoskeleton improves knee extension in children with crouch gait from cerebral palsy. Sci. Transl. Med. 2017 doi: 10.1126/scitranslmed.aam9145.
    1. Alcobendas MM, et al. Lokomat robotic-assisted versus overground training within 3 to 6 months of incomplete spinal cord lesion: Randomized controlled trial. Neurorehabil. Neural Repair. 2012;26:1058–1063. doi: 10.1177/1545968312448232.
    1. Jin LH, Yang SS, Choi JY, Sohn MK. The effect of robot-assisted gait training on Locomotor function and functional capability for daily activities in children with cerebral palsy: A single-blinded, randomized cross-over trial. Brain Sci. 2020;10:801. doi: 10.3390/brainsci10110801.
    1. Van, T. Q., Kim, S. H., Lee, K. H., Kang, S. C. & Ryu, J. H. in 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). 652–657 (IEEE).
    1. Duschau-Wicke A, Caprez A, Riener R. Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training. J. Neuroeng. Rehabil. 2010;7:1–13. doi: 10.1186/1743-0003-7-43.
    1. Arene N, Hidler J. Understanding motor impairment in the paretic lower limb after a stroke: A review of the literature. Top Stroke Rehabil. 2009;16:346–356. doi: 10.1310/tsr1605-346.
    1. Winter DA. Biomechanics and Motor Control of Human Movement. Wiley; 2009.
    1. Gregson JM, et al. Reliability of the tone assessment scale and the modified Ashworth scale as clinical tools for assessing poststroke spasticity. Arch. Phys. Med. Rehabil. 1999;80:1013–1016. doi: 10.1016/S0003-9993(99)90053-9.
    1. Ghotbi N, Ansari NN, Naghdi S, Hasson S. Measurement of lower-limb muscle spasticity: Intrarater reliability of modified modified Ashworth scale. J. Rehabil. Res. Dev. 2011;48:83–88. doi: 10.1682/JRRD.2010.02.0020.
    1. Sullivan KJ, et al. Fugl-Meyer assessment of sensorimotor function after stroke: Standardized training procedure for clinical practice and clinical trials. Stroke. 2011;42:427–432. doi: 10.1161/STROKEAHA.110.592766.
    1. Bonnyaud C, et al. Effect of a robotic restraint gait training versus robotic conventional gait training on gait parameters in stroke patients. Exp. Brain Res. 2014;232:31–42. doi: 10.1007/s00221-013-3717-8.
    1. Naro A, et al. Breakthroughs in the spasticity management: Are non-pharmacological treatments the future? J. Clin. Neurosci. 2017;39:16–27. doi: 10.1016/j.jocn.2017.02.044.
    1. Little VL, McGuirk TE, Patten C. Impaired limb shortening following stroke: What's in a name? PLoS ONE. 2014;9:e110140. doi: 10.1371/journal.pone.0110140.
    1. Hyngstrom A, Onushko T, Chua M, Schmit BD. Abnormal volitional hip torque phasing and hip impairments in gait post stroke. J. Neurophysiol. 2010;103:1557–1568. doi: 10.1152/jn.00528.2009.
    1. Akbas, T. Delineating abnormal coordination patterns in post-stroke gait: a multidisciplinary approach Ph.D thesis, The University of Texas at Austion, (2019).
    1. Roy, A., Krebs, H. I., Barton, J. E., Macko, R. F. & Forrester, L. W. M., R. M. in 2013 IEEE International Conference on Robotics and Automation. 2175–2182 (IEEE).
    1. Swaminathan, K. & Krebs, H. I. in 2015 IEEE International Conference on Rehabilitation Robotics (ICORR). 555–558 (IEEE).
    1. Kim CM, Eng JJ. The relationship of lower-extremity muscle torque to locomotor performance in people with stroke. Phys. Ther. 2003;83:49–57. doi: 10.1093/ptj/83.1.49.
    1. Al-Chalabi, M. & Alsalman, I. Neuroanatomy, posterior column (dorsal column). (2018).
    1. Niu J, et al. Modality-based organization of ascending somatosensory axons in the direct dorsal column pathway. J. Neurosci. 2013;33:17691–17709. doi: 10.1523/JNEUROSCI.3429-13.2013.
    1. Grillner S. Biological pattern generation: The cellular and computational logic of networks in motion. Neuron. 2006;52:751–766. doi: 10.1016/j.neuron.2006.11.008.
    1. Jahn K, et al. Supraspinal locomotor control in quadrupeds and humans. Prog. Brain Res. 2008;171:353–362. doi: 10.1016/S0079-6123(08)00652-3.
    1. Gassert R, Dietz V. Rehabilitation robots for the treatment of sensorimotor deficits: A neurophysiological perspective. J. Neuroeng. Rehabil. 2018;15:1–15. doi: 10.1186/s12984-018-0383-x.
    1. Brunnstrom S. Motor testing procedures in hemiplegia: Based on sequential recovery stages. Phys. Ther. 1966;46:357–375. doi: 10.1093/ptj/46.4.357.
    1. Peng Q, et al. Quantitative evaluations of ankle spasticity and stiffness in neurological disorders using manual spasticity evaluator. J. Rehabil. Res. Dev. 2011;48:473. doi: 10.1682/JRRD.2010.04.0053.
    1. You SH, et al. Virtual reality–induced cortical reorganization and associated locomotor recovery in chronic stroke: An experimenter-blind randomized study. Stroke. 2005;36:1166–1171. doi: 10.1161/01.STR.0000162715.43417.91.

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