Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurological impairments. The purpose of this study is to investigate the effects of rehabilitation with robotic devices on quality of life and depression.
Data sources
Two electronic databases (MEDLINE and Scopus) were searched for studies from inception up to December 2022.
Review methods
Randomized controlled trials (RCTs) and non-RCTs were pooled separately for analyses, studying each one’s mental and physical health and depression. Random effect meta-analyses were run using standardized mean difference and 95% confidence interval (CI).
Results
A total of 853 studies were identified from the literature search. 31 studies (17 RCTs and 14 non-RCTs) including 1151 subjects met the inclusion criteria. 31 studies were selected for the systematic review and 27 studies for the meta-analysis. The outcome measure of mental health significantly improved in favor of the RAGT group in RCTs and non-RCTs (adjusted Hedges’g 0.72, 95% CI: 0.34–1.10, adjusted Hedges g = 0.80, 95% CI 0.21-1.39, respectively). We observed a significant effect of RAGT on physical health in RCTs and non-RCTs (adjusted Hedges’g 0.58, 95% CI 0.28, 0.88, adjusted Hedges g = 0.73, 95% CI 0.12, 1.33). After realizing a sensitivity analysis in RCTs, a positive impact on depression is observed (Hedges’ g of −0.66, 95% CI −1.08 to −0.24).
Conclusion
This study suggests that RAGT could improve the quality of life of patients with neurological impairments. A positive impact on depression is also observed in the short term. Further studies are needed to differentiate grounded and overgrounded exoskeletons as well as RCT comparing overground exoskeletons with a control group.
StolzeHKlebeSBaeckerC, et al.Prevalence of gait disorders in hospitalized neurological patients. Mov Disord2005; 20: 89–94.
2.
Rodríguez-FernándezALobo-PratJFont-LlagunesJM. Systematic review on wearable lower-limb exoskeletons for gait training in neuromuscular impairments. J Neuroeng Rehabil2021; 18: 1–21.
3.
FangCYTsaiJLLiGS,et al.Effects of robot-assisted gait training in individuals with spinal cord injury: A meta-analysis. Biomed Res Int2020; 2020: 2102785.
4.
WangLZhengYDangY, et al.Effects of robot-assisted training on balance function in patients with stroke: A systematic review and meta-analysis. J Rehabil Med2021; 53: jrm00174.
5.
NedergårdHArumugamASandlundM,et al.Effect of robotic-assisted gait training on objective biomechanical measures of gait in persons post-stroke: A systematic review and meta-analysis. J Neuroeng Rehabil2021; 18: 64.
6.
BowmanTGervasoniEAmicoAP, et al.What is the impact of robotic rehabilitation on balance and gait outcomes in people with multiple sclerosis? A systematic review of randomized control trials. Eur J Phys Rehabil Med. Edizioni Minerva Medica2021; 57: 246–253.
MorrisonAPolisenaJHusereauD, et al.The effect of English-language restriction on systematic review-based meta-analyses: A systematic review of empirical studies. Int J Technol Assess Health Care2012; 28: 138–144.
9.
HigginsJPTAltmanDGGøtzschePC, et al.The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ2011; 343: d5928.
10.
CantrellACrootEJohnsonM, et al.Access to primary and community health-care services for people 16 years and over with intellectual disabilities: A mapping and targeted systematic review. Health Serv Deliv Res2020; 8: 1–142.
11.
HozoSPDjulbegovicBHozoI. Estimating the mean and variance from the median, range, and the size of a sample. BMC Med Res Methodol2005; 5: 13.
12.
SconzaCNegriniFdi MatteoB, et al.Robot-assisted gait training in patients with multiple sclerosis: A randomized controlled crossover trial. Medicina (Lithuania)2021; 57: 713.
13.
van NesIJWvan DijsseldonkRBvan HerpenFHM,et al.Improvement of quality of life after 2-month exoskeleton training in patients with chronic spinal cord injury. J Spinal Cord Med2022: 1–7. doi:10.1080/10790268.2022.2052502.
14.
SawadaTOkawaraHMatsubayashiK, et al.Influence of body weight-supported treadmill training with voluntary-driven exoskeleton on the quality of life of persons with chronic spinal cord injury: A pilot study. Int J Rehabil Res2021; 44: 343–349.
15.
MaggioMGNaroAde LucaR, et al.Body representation in patients with severe spinal cord injury: A pilot study on the promising role of powered exoskeleton for gait training. J Pers Med2022; 12: 619. doi:10.3390/jpm12040619.
16.
LouieDRMortensonWBDurocherM, et al.Efficacy of an exoskeleton-based physical therapy program for non-ambulatory patients during subacute stroke rehabilitation: A randomized controlled trial. J Neuroeng Rehabil2021; 18: 149.
17.
MengGMaXChenP, et al.Effect of early integrated robot-assisted gait training on motor and balance in patients with acute ischemic stroke: A single-blinded randomized controlled trial. Ther Adv Neurol Disord2022; 15, 1-10 doi:10.1177/17562864221123195.
18.
MiuraKTsudaEKogawaM, et al.Effects of gait training with a voluntary-driven wearable cyborg, hybrid assistive limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids. J Clin Neurosci2021; 89: 211–215.
19.
PlatzTGillnerABorgwaldtN,et al.Device-training for individuals with thoracic and lumbar spinal cord injury using a powered exoskeleton for technically assisted mobility: Achievements and user satisfaction. Biomed Res Int2016; 2016: 8459018.
20.
PoritzJPattersonLTsengSC,et al.Evaluation of quality of life measures for wearable robotic therapy in individuals with neurological disability: A preliminary report. In: 2017 international symposium on wearable robotics and rehabilitation, WeRob, Houston, TX, USA, 2017, pp. 1–2.
21.
TsaiCYAsselinPKHongE, et al.Exoskeletal-assisted walking may improve seated balance in persons with chronic spinal cord injury: A pilot study. Spinal Cord Ser Cases2021; 7: 20.
22.
JuszczakMGalloEBushnikT. Examining the effects of a powered exoskeleton on quality of life and secondary impairments in people living with spinal cord injury. Top Spinal Cord Inj Rehabil2018; 24: 336–342.
23.
CalabròRSde ColaMCLeoA, et al.Robotic neurorehabilitation in patients with chronic stroke: Psychological well-being beyond motor improvement. Int J Rehabil Res2015; 38: 219–225.
24.
McGibbonCSextonAGryfeP, et al. Effect of using of a lower-extremity exoskeleton on disability of people with multiple sclerosis. Disabil Rehabil: Assist Technol 2021: 1–8. doi:10.1080/1783107.2021.1874064.
25.
BaunsgaardCBNissenUVBrustAK, et al.Exoskeleton gait training after spinal cord injury: An exploratory study on secondary health conditions. J Rehabil Med2018; 50: 806–813.
26.
BertolucciFdi MartinoSOrsucciD, et al.Robotic gait training improves motor skills and quality of life in hereditary spastic paraplegia. NeuroRehabilitation2015; 36: 93–99.
27.
ChunAAsselinPKKnezevicS, et al.Changes in bowel function following exoskeletal-assisted walking in persons with spinal cord injury: An observational pilot study. Spinal Cord2020; 58: 459.
28.
KimHSParkJHLeeHS, et al.Effects of wearable powered exoskeletal training on functional mobility, physiological health and quality of life in non-ambulatory spinal cord injury patients. J Korean Med Sci2021; 36: 1–15.
29.
KozlowskiAJFabianMLadD,et al.Feasibility and safety of a powered exoskeleton for assisted walking for persons with multiple sclerosis: A single-group preliminary study. Arch Phys Med Rehabil2017; 98: 1300–1307.
30.
WuMLandryJMKimJ,et al.Robotic resistance/assistance training improves locomotor function in individuals poststroke: A randomized controlled study. Arch Phys Med Rehabil2014; 95: 799–806.
31.
CalabròRSRussoMNaroA, et al.Robotic gait training in multiple sclerosis rehabilitation: Can virtual reality make the difference? Findings from a randomized controlled trial. J Neurol Sci2017; 377: 25–30.
32.
RussoMDattolaVde ColaMC, et al.The role of robotic gait training coupled with virtual reality in boosting the rehabilitative outcomes in patients with multiple sclerosis. Int J Rehabil Res2018; 41: 166–172.
33.
ParkCOh-ParkMDohleC, et al.Effects of innovative hip-knee-ankle interlimb coordinated robot training on ambulation, cardiopulmonary function, depression, and fall confidence in acute hemiplegia. NeuroRehabilitation2020; 46: 577–587.
34.
TaveggiaGBorboniAMuléC,et al.Conflicting results of robot-assisted versus usual gait training during postacute rehabilitation of stroke patients: A randomized clinical trial. Int J Rehabil Res2016; 39: 29.
35.
DundarUToktasHSolakO, et al.A comparative study of conventional physiotherapy versus robotic training combined with physiotherapy in patients with stroke. Top Stroke Rehabil.2015; 21: 453–461.
36.
GormanPHForrestGFAsselinPK, et al.The effect of exoskeletal-assisted walking on spinal cord injury bowel function: Results from a randomized trial and comparison to other physical interventions. J Clin Med2021; 10: 64.
37.
ManuliAMaggioMGLatellaD, et al.Can robotic gait rehabilitation plus virtual reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols. J Stroke Cerebrovasc Dis2020; 29: 104994.
38.
StraudiSFanciullacciCMartinuzziC, et al.The effects of robot-assisted gait training in progressive multiple sclerosis: A randomized controlled trial. Mult Scler2016; 22: 373–384.
39.
MustafaogluRErhanBYeldanI,et al.Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial. Acta Neurol Belg2020; 120: 335–344.
40.
de LucaRMarescaGBallettaT, et al.Does overground robotic gait training improve non-motor outcomes in patients with chronic stroke? Findings from a pilot study. J Clin Neurosci2020; 81: 240–245.
41.
RussoMMaggioMGNaroA, et al.Can powered exoskeletons improve gait and balance in multiple sclerosis? A retrospective study. Int J Rehabil Res2021; 44: 126–130.
42.
The EuroQol Group. EuroQol—a new facility for the measurement of health-related quality of life. Health Policy (New York)1990; 16: 199–208.
43.
WareJEKosinskiMKellerSD. A 12-item short-form health survey: Construction of scales and preliminary tests of reliability and validity. Med Care1996; 34: 220–233.
44.
WareJEJrSherbourneCDWareJJ,et al.The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992; 30: 473–483.
45.
WilliamsLSWeinbergerMHarrisLE,et al.Development of a stroke-specific quality of life scale. Stroke1999; 30: 1362–1369.
46.
TulskyDSKisalaPA. The spinal cord injury – quality of life (SCI-QOL) measurement system: Development, psychometrics, and item bank calibration. J Spinal Cord Med2015; 38: 51.
47.
TulskyDSKisalPATateDG,et al.Development and psychometric characteristics of the SCI-QOL bladder management difficulties and bowel management difficulties item banks and short forms and the SCI-QOL bladder complications scale. J Spinal Cord Med2015; 38: 288–302.
48.
CellaDLaiJSNowinskiCJ, et al. Neuro-QOL: Brief measures of health-related quality of life for clinical research in neurology. Neurology. 2012; 78: 1860.
49.
DienerEEmmonsRALarsemRJ,et al.The satisfaction with life scale. J Pers Assess1985; 49: 71–75.
50.
HamiltonM. A rating scale for depression. J Neurol Neurosurg Psychiatry1960; 23: 56–62.
51.
GrossiECompareA. Psychological general well-being Index (PGWB). In: MichalosAC (ed) Encyclopedia of quality of life and well-being research. Netherlands: Springer, 2014, pp. 5152–5156.
52.
WilliamsLSBrizendineEJPlueL, et al.Performance of the PHQ-9 as a screening tool for depression after stroke. Stroke2005; 36: 635–638.
53.
HubleyAM. Beck depression inventory. In: MichalosAC (ed) Encyclopedia of quality of life and well-being Research. Netherlands: Springer, 2014, pp. 338–345.
54.
KimSYYangLParkIJ, 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 Eng2015; 23: 636–642.
55.
LouieDREngJJLamT. Gait speed using powered robotic exoskeletons after spinal cord injury: A systematic review and correlational study. J Neuroeng Rehabil2015; 12: 82.
56.
BaylorCYorkstonKJensenM,et al.Scoping review of common secondary conditions after stroke and their associations with age and time post stroke. 2014; 21: 371–382.
57.
JensenMPTruittARSchomerKG,et al.Frequency and age effects of secondary health conditions in individuals with spinal cord injury: A scoping review. Spinal Cord2013; 51: 882–892.
58.
MillerLEZimmermannAKHerbertWG. Clinical effectiveness and safety of powered exoskeleton-assisted walking in patients with spinal cord injury: Systematic review with meta-analysis. Med Devices (Auckl)2016; 9: 455–466.
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