Robotic-based ACTive somatoSENSory (Act.Sens) retraining on upper limb functions with chronic stroke survivors: study protocol for a pilot randomised controlled trial

Ananda Sidarta, Yu Chin Lim, Christopher Wee Keong Kuah, Yong Joo Loh, Wei Tech Ang, Ananda Sidarta, Yu Chin Lim, Christopher Wee Keong Kuah, Yong Joo Loh, Wei Tech Ang

Abstract

Background: Prior studies have established that senses of the limb position in space (proprioception and kinaesthesia) are important for motor control and learning. Although nearly one-half of stroke patients have impairment in the ability to sense their movements, somatosensory retraining focusing on proprioception and kinaesthesia is often overlooked. Interventions that simultaneously target motor and somatosensory components are thought to be useful for relearning somatosensory functions while increasing mobility of the affected limb. For over a decade, robotic technology has been incorporated in stroke rehabilitation for more controlled therapy intensity, duration, and frequency. This pilot randomised controlled trial introduces a compact robotic-based upper-limb reaching task that retrains proprioception and kinaesthesia concurrently.

Methods: Thirty first-ever chronic stroke survivors (> 6-month post-stroke) will be randomly assigned to either a treatment or a control group. Over a 5-week period, the treatment group will receive 15 training sessions for about an hour per session. Robot-generated haptic guidance will be provided along the movement path as somatosensory cues while moving. Audio-visual feedback will appear following every successful movement as a reward. For the same duration, the control group will complete similar robotic training but without the vision occluded and robot-generated cues. Baseline, post-day 1, and post-day 30 assessments will be performed, where the last two sessions will be conducted after the last training session. Robotic-based performance indices and clinical assessments of upper limb functions after stroke will be used to acquire primary and secondary outcome measures respectively. This work will provide insights into the feasibility of such robot-assisted training clinically.

Discussion: The current work presents a study protocol to retrain upper-limb somatosensory and motor functions using robot-based rehabilitation for community-dwelling stroke survivors. The training promotes active use of the affected arm while at the same time enhances somatosensory input through augmented feedback. The outcomes of this study will provide preliminary data and help inform the clinicians on the feasibility and practicality of the proposed exercise.

Trial registration: ClinicalTrials.gov NCT04490655 . Registered 29 July 2020.

Keywords: Haptic guidance; Kinaesthesia; Proprioception; Reward feedback; Robot-assisted training.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Diagram of study flow
Fig. 2
Fig. 2
SPIRIT diagram of the schedule of enrolment, interventions, and outcome measures. Abbreviations: FMA-UE Fugl-Meyer Assessment for Upper Extremity, WMFT streamlined Wolf Motor Function Test, EmNSA Erasmus MC modifications to the Nottingham Sensory Assessment, MAS modified Ashworth scale of spasticity
Fig. 3
Fig. 3
Experimental setup used in the study. a A compact table-top rehabilitation robotic device with the rectangular box covering the view of the affected arm. An example of feedback shown on the LCD display following a successful trial (b) and unsuccessful trial (c), respectively. Note: the person depicted is not a patient, but a study team member

References

    1. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study. J Am Coll Cardiol. 2020;76(25):2982–3021.
    1. Veerbeek JM, Kwakkel G, van Wegen EE, Ket JC, Heymans MW. Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke. 2011;42(5):1482–1488.
    1. Delavaran H, Aked J, Sjunnesson H, Lindvall O, Norrving B, Kokaia Z, et al. Spontaneous Recovery of upper extremity motor impairment after ischemic stroke: implications for stem cell-based therapeutic approaches. Transl Stroke Res. 2017;8(4):351–361.
    1. Meyer S, Karttunen AH, Thijs V, Feys H, Verheyden G. How do somatosensory deficits in the arm and hand relate to upper limb impairment, activity, and participation problems after stroke? A systematic review. Phys Ther. 2014;94(9):1220–1231.
    1. Hughes CM, Tommasino P, Budhota A, Campolo D. Upper extremity proprioception in healthy aging and stroke populations, and the effects of therapist- and robot-based rehabilitation therapies on proprioceptive function. Front Hum Neurosci. 2015;9:120.
    1. Findlater SE, Dukelow SP. Upper extremity proprioception after stroke: bridging the gap between neuroscience and rehabilitation. J Mot Behav. 2017;49(1):27–34.
    1. Carey LM, Matyas TA, Baum C. Effects of somatosensory impairment on participation after stroke. Am J Occup Ther. 2018;72(3):7203205100p1–720320510p10.
    1. Bird T, Choi S, Goodman L, Schmalbrock P, Nichols-Larsen DS. Sensorimotor training induced neural reorganization after stroke: a case series. J Neurol Phys Ther. 2013;37(1):27.
    1. Gopaul U, Carey L, Callister R, Nilsson M, van Vliet P. Combined somatosensory and motor training to improve upper limb function following stroke: a systematic scoping review. Phys Ther Rev. 2018;23(6):355–375.
    1. Gopaul U, van Vliet P, Callister R, Nilsson M, Carey L. COMbined Physical and somatoSEnsory training after stroke: development and description of a novel intervention to improve upper limb function. Physiother Res Int. 2019;24(1):e1748.
    1. Scalha TB, Miyasaki E, Lima NM, Borges G. Correlations between motor and sensory functions in upper limb chronic hemiparetics after stroke. Arq Neuropsiquiatr. 2011;69(4):624–629.
    1. de Diego C, Puig S, Navarro X. A sensorimotor stimulation program for rehabilitation of chronic stroke patients. Restor Neurol Neurosci. 2013;31(4):361–371.
    1. Wong JD, Kistemaker DA, Chin A, Gribble PL. Can proprioceptive training improve motor learning? J Neurophysiol. 2012;108(12):3313–3321.
    1. Darainy M, Vahdat S, Ostry DJ. Perceptual learning in sensorimotor adaptation. J Neurophysiol. 2013;110(9):2152–2162.
    1. Bernardi NF, Darainy M, Ostry DJ. Somatosensory contribution to the initial stages of human motor learning. J Neurosci. 2015;35(42):14316–14326.
    1. Sidarta A, Vahdat S, Bernardi NF, Ostry DJ. Somatic and reinforcement-based plasticity in the initial stages of human motor learning. J Neurosci. 2016;36(46):11682–11692.
    1. Vidoni ED, Boyd LA. Preserved motor learning after stroke is related to the degree of proprioceptive deficit. Behav Brain Funct. 2009;5:36.
    1. Cherpin A, Kager S, Budhota A, Contu S, Vishwanath D, Kuah CW, et al. A preliminary study on the relationship between proprioceptive deficits and motor functions in chronic stroke patients. IEEE Int Conf Rehabil Robot. 2019;2019:465–470.
    1. Abela E, Missimer J, Wiest R, Federspiel A, Hess C, Sturzenegger M, et al. Lesions to primary sensory and posterior parietal cortices impair recovery from hand paresis after stroke. PLoS One. 2012;7(2):e31275.
    1. Carey L, Macdonell R, Matyas TA. SENSe: Study of the effectiveness of neurorehabilitation on sensation: a randomized controlled trial. Neurorehabil Neural Repair. 2011;25(4):304–313.
    1. Carey LM, Matyas TA. Training of somatosensory discrimination after stroke: facilitation of stimulus generalization. Am J Phys Med Rehabil. 2005;84(6):428–442.
    1. Krebs HI, Hogan N, Aisen ML, Volpe BT. Robot-aided neurorehabilitation. IEEE Trans Rehabil Eng. 1998;6(1):75–87.
    1. Hogan N, Krebs HI. Physically interactive robotic technology for neuromotor rehabilitation. Prog Brain Res. 2011;192:59–68.
    1. Dukelow SP, Herter TM, Moore KD, Demers MJ, Glasgow JI, Bagg SD, et al. Quantitative assessment of limb position sense following stroke. Neurorehabil Neural Repair. 2010;24(2):178–187.
    1. Cappello L, Elangovan N, Contu S, Khosravani S, Konczak J, Masia L. Robot-aided assessment of wrist proprioception. Front Hum Neurosci. 2015;9:198.
    1. Contu S, Hussain A, Kager S, Budhota A, Deshmukh VA, Kuah CWK, et al. Proprioceptive assessment in clinical settings: evaluation of joint position sense in upper limb post-stroke using a robotic manipulator. PLoS One. 2017;12(11):e0183257.
    1. Semrau JA, Herter TM, Scott SH, Dukelow SP. Robotic identification of kinesthetic deficits after stroke. Stroke. 2013;44(12):3414–3421.
    1. De Santis D, Zenzeri J, Casadio M, Masia L, Riva A, Morasso P, et al. Robot-assisted training of the kinesthetic sense: enhancing proprioception after stroke. Front Hum Neurosci. 2014;8:1037.
    1. Vahdat S, Darainy M, Thiel A, Ostry DJ. A single session of robot-controlled proprioceptive training modulates functional connectivity of sensory motor networks and improves reaching accuracy in chronic stroke. Neurorehabil Neural Repair. 2019;33(1):70–81.
    1. Campolo D, Tommasino P, Gamage K, Klein J, Hughes CM, Masia L. H-Man: a planar, H-shape cabled differential robotic manipulandum for experiments on human motor control. J Neurosci Methods. 2014;235:285–297.
    1. Flash T, Hogan N. The coordination of arm movements: an experimentally confirmed mathematical model. J Neurosci. 1985;5(7):1688–1703.
    1. Goble DJ. Proprioceptive acuity assessment via joint position matching: from basic science to general practice. Phys Ther. 2010;90(8):1176–1184.
    1. Fugl-Meyer AR, Jääskö L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand J Rehabil Med. 1975;7(1):13.
    1. Bogard K, Wolf S, Zhang Q, Thompson P, Morris D, Nichols-Larsen D. Can the Wolf Motor Function Test be streamlined? Neurorehabil Neural Repair. 2009;23(5):422–428.
    1. Stolk-Hornsveld F, Crow JL, Hendriks EP, van der Baan R, Harmeling-van der Wel BC. The Erasmus MC modifications to the (revised) Nottingham Sensory Assessment: a reliable somatosensory assessment measure for patients with intracranial disorders. Clin Rehabil. 2006;20(2):160–172.
    1. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67(2):206–207.
    1. Downie WW, Leatham PA, Rhind VM, Wright V, Branco JA, Anderson JA. Studies with pain rating scales. Ann Rheum Dis. 1978;37(4):378–381.
    1. Halligan PW, Marshall JC, Wade DT. Visuospatial neglect: underlying factors and test sensitivity. Lancet. 1989;2(8668):908–911.
    1. Wulf G, Shea C, Lewthwaite R. Motor skill learning and performance: a review of influential factors. Med Educ. 2010;44(1):75–84.
    1. Bhaskar S, Stanwell P, Bivard A, Spratt N, Walker R, Kitsos GH, et al. The influence of initial stroke severity on mortality, overall functional outcome and in-hospital placement at 90 days following acute ischemic stroke: a tertiary hospital stroke register study. Neurol India. 2017;65(6):1252–1259.
    1. Byblow WD, Stinear CM, Barber PA, Petoe MA, Ackerley SJ. Proportional recovery after stroke depends on corticomotor integrity. Ann Neurol. 2015;78(6):848–859.
    1. Winters C, van Wegen EE, Daffertshofer A, Kwakkel G. Generalizability of the proportional recovery model for the upper extremity after an ischemic stroke. Neurorehabil Neural Repair. 2015;29(7):614–622.

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