RObotic-Assisted Rehabilitation for balance and gait in Stroke patients (ROAR-S): study protocol for a preliminary randomized controlled trial

Silvia Giovannini, Chiara Iacovelli, Fabrizio Brau, Claudia Loreti, Augusto Fusco, Pietro Caliandro, Lorenzo Biscotti, Luca Padua, Roberto Bernabei, Letizia Castelli, Silvia Giovannini, Chiara Iacovelli, Fabrizio Brau, Claudia Loreti, Augusto Fusco, Pietro Caliandro, Lorenzo Biscotti, Luca Padua, Roberto Bernabei, Letizia Castelli

Abstract

Background: Stroke, the incidence of which increases with age, has a negative impact on motor and cognitive performance, quality of life, and the independence of the person and his or her family, leading to a number of direct and indirect costs. Motor recovery is essential, especially in elderly patients, to enable the patient to be independent in activities of daily living and to prevent falls. Several studies have shown how robotic training associated with physical therapy influenced functional and motor outcomes of walking after stroke by improving endurance and walking strategies. Considering data from previous studies and patients' needs in gait and balance control, we hypothesized that robot-assisted balance treatment associated with physical therapy may be more effective than usual therapy performed by a physical therapist in terms of improving static, dynamic balance and gait, on fatigue and cognitive performance.

Methods: This is an interventional, single-blinded, preliminary randomized control trial. Twenty-four patients of both sexes will be recruited, evaluated, and treated at the UOC Rehabilitation and Physical Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome from January to December 2022. Patients will be randomized into two groups: the experimental group will perform specific rehabilitation for balance disorder using the Hunova® robotic platform (Movendo Technology srl, Genoa, IT) for 3 times a week, for 4 weeks (12 total sessions), and for 45 min of treatment, in addition to conventional treatment, while the conventional group (GC) will perform only conventional treatment as per daily routine. All patients will undergo clinical and instrumental evaluation at the beginning and end of the 4 weeks of treatment.

Conclusions: The study aims to evaluate the improvement in balance, fatigue, quality of life, and motor and cognitive performance after combined conventional and robotic balance treatment with Hunova® (Movendo Technology srl, Genoa, IT) compared with conventional therapy alone. Robotic assessment to identify the most appropriate and individualized rehabilitation treatment may allow reducing disability and improving quality of life in the frail population. This would reduce direct and indirect social costs of care and treatment for the National Health Service and caregivers.

Trial registration: ClinicalTrials.gov NCT05280587. Registered on March 15, 2022.

Keywords: Elderly; Falls; Older adults; Rehabilitation; Technology.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Study design with Group randomization
Fig. 2
Fig. 2
Robotic platform Hunova® (Movendo Technology srl, Genova, Italy) in our laboratory
Fig. 3
Fig. 3
The study flowchart

References

    1. Feigin VL, Forouzanfar MH, Krishnamurthi R, Mensah GA, Connor M, Bennett DA, et al. Global and regional burden of stroke during 1990–2010: findings from the Global Burden of Disease Study 2010. Lancet. 2014;383:245–255. doi: 10.1016/S0140-6736(13)61953-4.
    1. Gresham GE, Fitzpatrick TE, Wolf PA, McNamara PM, Kannel WB, Dawber TR. Residual disability in survivors of stroke–the Framingham study. N Engl J Med. 1975;293:954–6. doi: 10.1056/NEJM197511062931903.
    1. Fattore G, Torbica A, Susi A, Giovanni A, Benelli G, Gozzo M, et al. The social and economic burden of stroke survivors in Italy: a prospective, incidence-based, multi-centre cost of illness study. BMC Neurol BioMed Central. 2012;12:1–11.
    1. Hatem SM, Saussez G, della Faille M, Prist V, Zhang X, Dispa D, , et al. Rehabilitation of motor function after stroke: a multiple systematic review focused on techniques to stimulate upper extremity recovery. Front Hum Neurosci. 2016;10:442. doi: 10.3389/fnhum.2016.00442.
    1. Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol. 2009;8:741–754. doi: 10.1016/S1474-4422(09)70150-4.
    1. Selves C, Stoquart G, Lejeune T. Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions. Acta Neurol Belg Acta Neurol Belg. 2020;120:783–790. doi: 10.1007/s13760-020-01320-7.
    1. Biscetti F, Giovannini S, Straface G, Bertucci F, Angelini F, Porreca C, et al. RANK/RANKL/OPG pathway: genetic association with history of ischemic stroke in Italian population. Eur Rev Med Pharmacol Sci. 2016;20:4574–4580.
    1. Giovannini S, Brau F, Galluzzo V, Santagada DA, Loreti C, Biscotti L, et al. Falls among older adults: screening, identification, rehabilitation, and management. Appl Sci. 2022;12:7934.
    1. Giovannini S, Onder G, Leeuwenburgh C, Carter C, Marzetti E, Russo A, et al. Myeloperoxidase levels and mortality in frail community-living elderly individuals. J Gerontol A Biol Sci Med Sci. 2010;65:369–76. doi: 10.1093/gerona/glp183.
    1. Onder G, Giovannini S, Sganga F, Manes-Gravina E, Topinkova E, Finne-Soveri H, et al. Interactions between drugs and geriatric syndromes in nursing home and home care: results from Shelter and IBenC projects. Aging Clin Exp Res. 2018;30:1015–21.
    1. Laudisio A, Antonelli Incalzi R, Gemma A, Giovannini S, lo Monaco MR, Vetrano DL, et al. Use of proton-pump inhibitors is associated with depression: a population-based study. Int Psychogeriatr. 2018;30:153–9.
    1. Mehrholz J, Thomas S, Kugler J, Pohl M, Elsner B. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. John Wiley and Sons Ltd. 2020;10(10):CD006185. 10.1002/14651858.CD006185.pub5.
    1. Aprile I, Iacovelli C, Padua L, Galafate D, Criscuolo S, Gabbani D, et al. Efficacy of robotic-assisted gait training in chronic stroke patients: preliminary results of an Italian bi-centre study. NeuroRehabilitation. 2017;41:775–782. doi: 10.3233/NRE-172156.
    1. Aprile I, Iacovelli C, Goffredo M, Cruciani A, Galli M, Simbolotti C, et al. Efficacy of end-effector robot-assisted gait training in subacute stroke patients: clinical and gait outcomes from a pilot bi-centre study. NeuroRehabilitation. 2019;45:201–212. doi: 10.3233/NRE-192778.
    1. Aprile I, Guardati G, Cipollini V, Papadopoulou D, Mastrorosa A, Castelli L, et al. Robotic rehabilitation: an opportunity to improve cognitive functions in subjects with stroke. an explorative study. Front Neurol. 2020;11:588285.
    1. Cattaneo D, Carpinella I, Aprile I, Prosperini L, Montesano A, Jonsdottir J. Comparison of upright balance in stroke, Parkinson and multiple sclerosis. Acta Neurol Scand Acta Neurol Scand. 2016;133:346–354. doi: 10.1111/ane.12466.
    1. Prosperini L, Castelli L, De Luca F, Fabiano F, Ferrante I, De Giglio L. Task-dependent deterioration of balance underpinning cognitive-postural interference in MS. Neurology Neurology. 2016;87:1085–1092. doi: 10.1212/WNL.0000000000003090.
    1. Prosperini L, Castelli L, Sellitto G, De Luca F, De Giglio L, Gurreri F, et al. Investigating the phenomenon of “cognitive-motor interference” in multiple sclerosis by means of dual-task posturography. Gait Posture Gait Posture. 2015;41:780–785. doi: 10.1016/j.gaitpost.2015.02.002.
    1. Castelli L, De Luca F, Marchetti MR, Sellitto G, Fanelli F, Prosperini L. The dual task-cost of standing balance affects quality of life in mildly disabled MS people. Neurol Sci Neurol Sci. 2016;37:673–679.
    1. Aprile I, Conte C, Cruciani A, Pecchioli C, Castelli L, Insalaco S, et al. Efficacy of robot-assisted gait training combined with robotic balance training in subacute stroke patients: a randomized clinical trial. J Clin Med. 2022;11:5162.
    1. Castelli L, de Giglio L, Haggiag S, Traini A, de Luca F, Ruggieri S, et al. Premorbid functional reserve modulates the effect of rehabilitation in multiple sclerosis. Neurol Sci Springer. 2020;41:1251–1257. doi: 10.1007/s10072-019-04237-z.
    1. Imbimbo I, Coraci D, Santilli C, Loreti C, Piccinini G, Ricciardi D, et al. Parkinson’s disease and virtual reality rehabilitation: cognitive reserve influences the walking and balance outcome. Neurol Sci. 2021;42(11):4615-21.
    1. Giovannini S, Macchi C, Liperoti R, Laudisio A, Coraci D, Loreti C, et al. Association of body fat with health-related quality of life and depression in nonagenarians: the Mugello study. J Am Med Dir Assoc. 2019;20:564–8.
    1. Fayazi M, Dehkordi SN, Dadgoo M, Salehi M. Test-retest reliability of Motricity Index strength assessments for lower extremity in post stroke hemiparesis. Med J Islam Repub Iran. 2012;26:27–30.
    1. Berg K, Wood-Dauphinee S, Williams JI. The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Scand J Rehabil Med. 1995;27:27–36.
    1. Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–8.
    1. Volpato S, Cavalieri M, Sioulis F, Guerra G, Maraldi C, Zuliani G, et al. Predictive value of the short physical performance battery following hospitalization in older patients. J Gerontol Series A. 2011;66A:89–96.
    1. Hauser SL, Dawson DM, Lehrich JR, Beal MF, Kevy S v., Propper RD, et al. Intensive immunosuppression in progressive multiple sclerosis. A randomized, three-arm study of high-dose intravenous cyclophosphamide, plasma exchange, and ACTH. N Engl J Med. 1983;308:173–80.
    1. Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26:982–9.
    1. Mehrholz J, Wagner K, Rutte K, Meißner D, Pohl M. Predictive validity and responsiveness of the functional ambulation category in hemiparetic patients after stroke. Arch Phys Med Rehabil. 2007;88:1314–9.
    1. Watson MJ. Refining the ten-metre walking test for use with neurologically impaired people. Physiotherapy Elsevier Ltd. 2002;88:386–397. doi: 10.1016/S0031-9406(05)61264-3.
    1. Morales-Blanhir JE, Vidal CDP, de Jesús Rosas Romero M, Castro MMG, Villegas AL, Zamboni M. Six-minute walk test: a valuable tool for assessing pulmonary impairment. J Bras Pneumol. 2011;37:110–7.
    1. Collin C, Wade DT, Davies S, Horne V. The Barthel ADL Index: a reliability study. Int Disabil Stud. 1988;10:61–3.
    1. Balestroni G, Bertolotti G. EuroQol-5D (EQ-5D): an instrument for measuring quality of life. Monaldi Arch. Chest Dis. 2012;78:155–9.
    1. Hubacher M, Calabrese P, Bassetti C, Carota A, Stöcklin M, Penner IK. Assessment of post-stroke fatigue: the fatigue scale for motor and cognitive functions. Eur Neurol. 2012;67:377–84.
    1. Elbers RG, Rietberg MB, van Wegen EEH, Verhoef J, Kramer SF, Terwee CB, et al. Self-report fatigue questionnaires in multiple sclerosis, Parkinson’s disease and stroke: a systematic review of measurement properties. Qual Life Res. 2012;21:925–44.
    1. Dubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a Frontal Assessment Battery at bedside. Neurology. 2000;55:1621–6.
    1. Scarpina F, Tagini S. The Stroop color and word test. Front Psychol. 2017;8:557. doi: 10.3389/fpsyg.2017.00557.
    1. Amodio P, Wenin H, del Piccolo F, Mapelli D, Montagnese S, Pellegrini A, et al. Variability of trail making test, symbol digit test and line trait test in normal people. A normative study taking into account age-dependent decline and sociobiological variables. Aging Clin Exp Res. 2002;14:117–31.
    1. Hatta T, Yoshizaki K, Ito Y, Mase M, Kabasawa H. Reliability and validity of the digit cancellation test, a brief screen of attention. Psychologia. 2012;55:246–256. doi: 10.2117/psysoc.2012.246.
    1. Pierre Gagnon M, Orrun E, Asua J, ben Abdeljelil A, Emparanza J. Using a Modified technology acceptance model to evaluate healthcare professionals’ adoption of a new telemonitoring system. Telemed J E Health. 2012;18(1):54-9.
    1. Julious SA. Sample size of 12 per group rule of thumb for a pilot study. Pharm Stat. 2005;4:287–91.
    1. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208.
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.
    1. R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2022. .
    1. Feng L, Moritz S, Nowak G, Welsh A, O’Neill T. imputeR: a general multivariate imputation framework. R package version 2.2. 2020. <>.

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