1. Economics, DA . No postcode untouched: Stroke in Australia 2017. 2017. Melbourne, Victoria, Australia: National Stroke Foundation.
Google Scholar2. Economics, DA . The economic impact of stroke in Australia. 2013. Melbourne, Victoria, Australia: National Stroke Foundation.
Google Scholar3. Jorgensen, HS, Nakayama, H, Raaschou, HO, et al. Recovery of walking function in stroke patients: the copenhagen stroke study. Arch Phys Med Rehabil 1995; 76: 27–32.
Google Scholar | Crossref | Medline | ISI4. Zhang, X, Yue, Z, Wang, J. Robotics in lower-limb rehabilitation after stroke. Behav Neurol 2017; 2017: 3731802. doi:10.1155/2017/3731802
Google Scholar | Crossref | Medline5. Morone, G, Paolucci, S, Cherubini, A, 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
Google Scholar | Crossref | Medline6. Australian Institute of Health and Welfare . Disability In Australia: Acquired Brain Inury. Canberra, ACT, Australia: Australian Institute of Health and Welfare, 2007.
Google Scholar7. Kleim, J . Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage J Speech, Lang Hearing Res 2008; 51: 225–239.
Google Scholar | Crossref | Medline | ISI8. Behrman, AL, Bowden, MG, Nair, PM. Neuroplasticity after spinal cord injury and training: an emerging paradigm shift in rehabilitation and walking recovery. Phys Ther 2006; 86: 1406–1425.
Google Scholar | Crossref | Medline | ISI9. Chen, G, Chan, CK, Guo, Z, et al. A review on lower extremity assistive robotic exoskeleton in rehabilitation therapy Crit Rev Biomed Eng 2013; 41: 343–363.
Google Scholar | Crossref | Medline10. Bruni, MF, Melegari, C, De Cola, MC, et al. What does best evidence tell us about robotic gait rehabilitation in stroke patients: a systematic review and meta-analysis. J Clin Neurosci 2018; 48: 11–17. doi:10.1016/j.jocn.2017.10.048
Google Scholar | Crossref | Medline11. van Nunen, MPM, Gerrits, KHL, Konijnenbelt, M, et al. Recovery of walking ability using a robotic device in subacute stroke patients: a randomized controlled study. Disabil Rehabil Assistive Tech 2015; 10: 141–148. doi:10.3109/17483107.2013.873489
Google Scholar | Crossref | Medline | ISI12. Field-Fote, EC, Roach, KE. Influence of a locomotor training approach on walking speed and distance in people with chronic spinal cord injury: a randomized clinical trial. Phys Ther 2011; 91: 48–60.
Google Scholar | Crossref | Medline | ISI13. Viteckova, S, Kutilek, P, Jirina, M. Wearable lower limb robotics: a review. Biocybernetics Biomed Eng 2013; 33: 96–105. doi:10.1016/j.bbe.2013.03.005
Google Scholar | Crossref | ISI14. Swank, C, Sikka, S, Driver, S, et al. Feasibility of integrating robotic exoskeleton gait training in inpatient rehabilitation. Disabil Rehabil Assistive Tech 2020; 15: 409–417. doi:10.1080/17483107.2019.1587014
Google Scholar | Crossref | Medline15. Nilsson, A, Skough Vreede, K, Häglund, V, et al. Gait training early after stroke with a new exoskeleton - the hybrid assistive limb: a study of safety and feasibility. J NeuroEngineering Rehabil (Jner) 2014; 11: 1–18. doi:10.1186/1743-0003-11-92
Google Scholar | Crossref | Medline16. Yoshimoto, T, Shimizu, I, Hiroi, Y, et al. Feasibility and efficacy of high-speed gait training with a voluntary driven exoskeleton robot for gait and balance dysfunction in patients with chronic stroke: nonrandomized pilot study with concurrent control. Int J Rehabil Res 2015; 38: 338–343. doi:10.1097/MRR.0000000000000132
Google Scholar | Crossref | Medline17. Ueba, T, Hamada, O, Ogata, T, et al. Feasibility and safety of acute phase rehabilitation after stroke using the hybrid assistive limb robot suit. Neurol Med Chir (Tokyo) 2013; 53: 287–290.
Google Scholar | Crossref | Medline18. Goffredo, M, Guanziroli, E, Pournajaf, S, et al. Overground wearable powered exoskeleton for gait training in subacute stroke subjects: clinical and gait assessments. Eur J Phys Rehabil Med 2019; 55: 710–721. doi:10.23736/s1973-9087.19.05574-6
Google Scholar | Crossref | Medline19. Louie, DR, Eng, JJ. Powered robotic exoskeletons in post-stroke rehabilitation of gait: a scoping review. J Neuroeng Rehabil 2016; 13: 53.
Google Scholar | Crossref | Medline20. Postol, N, Marquez, J, Spartalis, S, et al. Do powered over-ground lower limb robotic exoskeletons affect outcomes in the rehabilitation of people with acquired brain injury? Disabil Rehabil Assistive Tech 2018: 1–12. doi:10.1080/17483107.2018.1499137
Google Scholar | Crossref21. Pinto-Fernandez, D, Torricelli, D, Sanchez-Villamanan, MdC, et al. Performance evaluation of lower limb exoskeletons:a systematic review. IEEE Trans Neural Syst Rehabil Eng 2020; 28: 1573.
Google Scholar | Crossref | Medline22. Rex Bionics, L . REX bionics, https://www.rexbionics.com/(2019, accessed 24 January 2019).
Google Scholar23. Barbareschi, G, Richards, R, Thornton, M, et al. Statically vs dynamically balanced gait: analysis of a robotic exoskeleton compared with a human. Annu Int Conf IEEE Eng Med Biol Soc 2015; 2015: 6728–6731. doi:10.1109/EMBC.2015.7319937
Google Scholar | Crossref | Medline24. Nasreddine, ZS, Phillips, NA, Bédirian, V, et al. The montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 2005; 53: 695–699. doi:10.1111/j.1532-5415.2005.53221.x
Google Scholar | Crossref | Medline | ISI25. Terence, JQ, Martin, T-R, Aishah, C, et al. Pre-sroke modified rankin scale: evaluation of validity, prognostic accuracy, and association with treatment. Front Neurol 2017; 8: 275. doi:10.3389/fneur.2017.00275
Google Scholar | Crossref | Medline26. , , et al. Investigation of new motor assessment scale for stroke paitents. Phys Ther 1985; 65: 175–180.
Google Scholar | Crossref | Medline27. Tyson, SF, DeSouza, LH. Reliability and validity of functional balance tests post stroke. Clin Rehabil 2004; 18: 916.
Google Scholar | SAGE Journals | ISI28. Roberts, HC, Denison, HJ, Martin, HJ, et al. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing 2011; 40: 423–429. doi:10.1093/ageing/afr051
Google Scholar | Crossref | Medline | ISI29. Bohannon, R, Shove, M, Barreca, S, et al. Five-repetition sit-to-stand test performance by community-dwelling adults: a preliminary investigation of times, determinants, and relationship with self-reported physical performance. Isokinetics Exerc Sci 2007; 15: 77–81. doi:10.3233/IES-2007-0253
Google Scholar | Crossref30. Bohannon, RW, Wolfson, LI, White, WB. Functional reach of older adults: normative reference values based on new and published data. Physiotherapy 2017; 103: 387–391. doi:10.1016/j.physio.2017.03.006
Google Scholar | Crossref | Medline31. Glinsky, J . Tardieu scale. J Physiother 2016; 62: 229. doi:10.1016/j.jphys.2016.07.007
Google Scholar | Crossref | Medline32. Collin, C, Wade, DT, Davies, S, et al. The barthel ADL index: a reliability study. Int Disabil Stud 1988; 10: 61–63. doi:10.3109/09638288809164103
Google Scholar | Crossref | Medline33. Bjelland, I, Dahl, AA, Haug, TT, et al. The validity of the hospital anxiety and depression scale: an updated literature review. J Psychosomatic Res 2002; 52: 69–77. doi:10.1016/S0022-3999(01)00296-3
Google Scholar | Crossref | Medline | ISI34. Mead, G, Lynch, J, Greig, C, et al. Evaluation of fatigue scales in stroke patients. Stroke 2007; 38: 2090–2095. doi:10.1161/STROKEAHA.106.478941.
Google Scholar | Crossref | Medline | ISI35. Ware, J. . Jr SF-36® health survey update. The use of psychological testing for treatment planning and outcomes assessment. 2004; 3: 693–718.
Google Scholar36. STATA . STATA software, https://www.stata.com/(2019, accessed 11 March 2019).
Google Scholar37. Dromerick, AW, Edwards, DF, Diringer, MN. Sensitivity to changes in disability after stroke: a comparison of four scales useful in clinical trials. J Rehabil Res Develop 2003; 40: 1–8.
Google Scholar | Crossref | Medline38. English, CK, Hillier, SL, Stiller, K, et al. The sensitivity of three commonly used outcome measures to detect change amongst patients receiving inpatient rehabilitation following stroke. Clin Rehabil 2006; 20: 52–55.
Google Scholar | SAGE Journals | ISI39. Lang, CE, Edwards, DF, Birkenmeier, RL, et al. Estimating minimal clinically important differences of upper-extremity measures early after stroke. Arch Phys Med Rehabil 2008; 89: 1693.
Google Scholar | Crossref | Medline | ISI40. Spiers, G, Aspinal, F, Bernard, S, et al. What outcomes are important to people with long-term neurological conditions using integrated health and social care? Health Soc Care Community 2015; 23: 559–568. doi:10.1111/hsc.12171
Google Scholar | Crossref | Medline41. Lam, MY, Tatla, SK, Lohse, KR, et al. Perceptions of technology and Its use for therapeutic application for individuals with hemiparesis: findings from adult and pediatric focus groups. JMIR Rehabil Assistive Tech 2015; 2: e1. doi:10.2196/rehab.3484
Google Scholar | Crossref | Medline42. Lajeunesse, V, Lettre, J, Routhier, F, et al. Perspectives of individuals with incomplete spinal cord injury concerning the usability of lower limb exoskeletons: an exploratory study. Tech Disabil 2018; 30: 63–76. doi:10.3233/TAD-180195
Google Scholar | Crossref43. Gagnon, DH, Vermette, M, Duclos, C, et al. Satisfaction and perceptions of long-term manual wheelchair users with a spinal cord injury upon completion of a locomotor training program with an overground robotic exoskeleton. Disabil Rehabil Assistive Tech 2019; 14: 138–145. doi:10.1080/17483107.2017.1413145
Google Scholar | Crossref | Medline