Innovative technology-based interventions in Parkinson's disease: A systematic review and meta-analysis
Chun En Yau,
Eric Chi Kiat Ho,
Natasha Yixuan Ong,
Clifton Joon Keong Loh,
Aaron Shengting Mai,
Eng-King Tan,
Chun En Yau
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorEric Chi Kiat Ho
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorNatasha Yixuan Ong
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorClifton Joon Keong Loh
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorAaron Shengting Mai
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorCorresponding Author
Eng-King Tan
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Neuroscience and Behavioural Disorders, Duke-NUS Medical School, Singapore, Singapore
Correspondence
Eng-King Tan, Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Outram Road, Singapore 169608, Singapore. Tel: +65 6326 5003; Fax: +65 6220 3321; E-mail: [email protected]
Search for more papers by this authorChun En Yau,
Eric Chi Kiat Ho,
Natasha Yixuan Ong,
Clifton Joon Keong Loh,
Aaron Shengting Mai,
Eng-King Tan,
Chun En Yau
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorEric Chi Kiat Ho
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorNatasha Yixuan Ong
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorClifton Joon Keong Loh
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorAaron Shengting Mai
Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Search for more papers by this authorCorresponding Author
Eng-King Tan
Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Singapore, Singapore
Neuroscience and Behavioural Disorders, Duke-NUS Medical School, Singapore, Singapore
Correspondence
Eng-King Tan, Department of Neurology, Singapore General Hospital Campus, National Neuroscience Institute, Outram Road, Singapore 169608, Singapore. Tel: +65 6326 5003; Fax: +65 6220 3321; E-mail: [email protected]
Search for more papers by this authorAbstract
Objective
Novel technology-based interventions have the potential to improve motor symptoms and gait in Parkinson's disease (PD). Promising treatments include virtual-reality (VR) training, robotic assistance, and biofeedback. Their effectiveness remains unclear, and thus, we conducted a Bayesian network meta-analysis.
Methods
We searched the Medline, Embase, Cochrane CENTRAL, and Clinicaltrials.gov databases until 2 April 2024 and only included randomized controlled trials. Outcomes included changes in UPDRS-III/MDS-UPDRS-III score, stride length, 10-meter walk test (10MWT), timed up-and-go (TUG) test, balance scale scores and quality-of-life (QoL) scores. Results were reported as mean differences (MD) or standardized mean differences (SMD), with 95% credible intervals (95% CrI).
Results
Fifty-one randomized controlled trials with 2095 patients were included. For UPDRS (motor outcome), all interventions had similar efficacies. VR intervention was the most effective in improving TUG compared with control (MD: −4.36, 95% CrI: −8.57, −0.35), outperforming robotic, exercise, and proprioceptive interventions. Proprioceptive intervention significantly improved stride length compared to control intervention (MD: 0.11 m, 95% CrI: 0.03, 0.19), outperforming VR, robotic and exercise interventions. Virtual reality improved balance scale scores significantly compared to exercise intervention (SMD: 0.75, 95% CrI: 0.12, 1.39) and control intervention (SMD: 1.42, 95% CrI: 0.06, 2.77). Virtual reality intervention significantly improved QoL scores compared to control intervention (SMD: −0.95, 95% CrI: −1.43, −0.52), outperforming Internet-based interventions.
Interpretation
VR-based and proprioceptive interventions were the most promising interventions, consistently ranking as the top treatment choices for most outcomes. Their use in clinical practice could be helpful in managing motor symptoms and QoL in PD.
Conflict of Interest
The authors do not have any competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Open Research
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
Supporting Information
| Filename | Description |
|---|---|
| acn352160-sup-0001-Supinfo.docxWord 2007 document , 221.8 KB |
Appendix S1. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1Hirsch L, Jette N, Frolkis A, Steeves T, Pringsheim T. The incidence of Parkinson's disease: a systematic review and meta-analysis. Neuroepidemiology. 2016; 46(4): 292-300. doi:10.1159/000445751
- 2Schapira AHV. Neurobiology and treatment of Parkinson's disease. Trends Pharmacol Sci. 2009; 30(1): 41-47. doi:10.1016/j.tips.2008.10.005
- 3Ou Z, Pan J, Tang S, et al. Global trends in the incidence, prevalence, and years lived with disability of Parkinson's disease in 204 countries/territories from 1990 to 2019. Front Public Health. 2021; 9:776847. doi:10.3389/fpubh.2021.776847
- 4Feigin VL, Nichols E, Alam T, et al. Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the global burden of disease study 2016. Lancet Neurol. 2019; 18(5): 459-480. doi:10.1016/S1474-4422(18)30499-X
- 5Moustafa AA, Chakravarthy S, Phillips JR, et al. Motor symptoms in Parkinson's disease: a unified framework. Neurosci Biobehav Rev. 2016; 68: 727-740. doi:10.1016/j.neubiorev.2016.07.010
- 6Schapira AHV, Bezard E, Brotchie J, et al. Novel pharmacological targets for the treatment of Parkinson's disease. Nat Rev Drug Discov. 2006; 5(10): 845-854. doi:10.1038/nrd2087
- 7Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson's disease. Mov Disord. 2015; 30(12): 1591-1601. doi:10.1002/mds.26424
- 8Marsili L, Rizzo G, Colosimo C. Diagnostic criteria for Parkinson's disease: from James Parkinson to the concept of prodromal disease. Front Neurol. 2018; 9: 156. doi:10.3389/fneur.2018.00156
- 9Kuopio A-M, Marttila RJ, Helenius H, Toivonen M, Rinne UK. The quality of life in Parkinson's disease. Mov Disord. 2000; 15(2): 216-223. doi:10.1002/1531-8257(200003)15:2<216::AID-MDS1003>3.0.CO;2-#
- 10Stamford JA, Schmidt PN, Friedl KE. What engineering technology could do for quality of life in Parkinson's disease: a review of current needs and opportunities. IEEE J Biomed Health Inform. 2015; 19(6): 1862-1872. doi:10.1109/JBHI.2015.2464354
- 11Abbruzzese G, Marchese R, Avanzino L, Pelosin E. Rehabilitation for Parkinson's disease: current outlook and future challenges. Parkinsonism Relat Disord. 2016; 22: S60-S64. doi:10.1016/j.parkreldis.2015.09.005
- 12Rascol O, Payoux P, Ory F, Ferreira JJ, Brefel-Courbon C, Montastruc J-L. Limitations of current Parkinson's disease therapy. Ann Neurol. 2003; 53(S3): S3-S15. doi:10.1002/ana.10513
- 13Fasano A, Aquino CC, Krauss JK, Honey CR, Bloem BR. Axial disability and deep brain stimulation in patients with Parkinson disease. Nat Rev Neurol. 2015; 11(2): 98-110. doi:10.1038/nrneurol.2014.252
- 14Tsuboi T, Watanabe H, Tanaka Y, et al. Distinct phenotypes of speech and voice disorders in Parkinson's disease after subthalamic nucleus deep brain stimulation. J Neurol Neurosurg Psychiatry. 2015; 86(8): 856-864. doi:10.1136/jnnp-2014-308043
- 15Rogers MW. Disorders of posture, balance, and gait in Parkinson's disease. Clin Geriatr Med. 1996; 12(4): 825-845. doi:10.1016/S0749-0690(18)30203-9
- 16Dockx K, Bekkers EMJ, Van den Bergh V, et al. Virtual reality for rehabilitation in Parkinson's disease. Cochrane Database Syst Rev. 2016; 2016: CD010760. doi:10.1002/14651858.CD010760.pub2
10.1002/14651858.CD010760.pub2 Google Scholar
- 17Sale P, De Pandis MF, Domenica LP, et al. Robot-assisted walking training for individuals with Parkinson's disease: a pilot randomized controlled trial. BMC Neurol. 2013; 13:50. doi:10.1186/1471-2377-13-50
- 18Kleiner AFR, Souza Pagnussat A, Pinto C, Redivo Marchese R, Salazar AP, Galli M. Automated mechanical peripheral stimulation effects on gait variability in individuals with Parkinson disease and freezing of gait: a double-blind, randomized controlled trial. Arch Phys Med Rehabil. 2018; 99(12): 2420-2429. doi:10.1016/j.apmr.2018.05.009
- 19Achey M, Aldred JL, Aljehani N, et al. The past, present, and future of telemedicine for Parkinson's disease: telemedicine for Parkinson's disease. Mov Disord. 2014; 29(7): 871-883. doi:10.1002/mds.25903
- 20Lee HS, Park YJ, Park SW. The effects of virtual reality training on function in chronic stroke patients: a systematic review and meta-analysis. Biomed Res Int. 2019; 2019:7595639. doi:10.1155/2019/7595639
- 21Herman T, Giladi N, Hausdorff JM. Properties of the ‘timed up and go’ test: more than meets the eye. Gerontology. 2011; 57(3): 203-210. doi:10.1159/000314963
- 22Pelosin E, Cerulli C, Ogliastro C, et al. A multimodal training modulates short afferent inhibition and improves complex walking in a cohort of faller older adults with an increased prevalence of Parkinson's disease. J Gerontol A Biol Sci Med Sci. 2020; 75(4): 722-728. doi:10.1093/gerona/glz072
- 23Ferrazzoli D, Ortelli P, Madeo G, Giladi N, Petzinger GM, Frazzitta G. Basal ganglia and beyond: the interplay between motor and cognitive aspects in Parkinson's disease rehabilitation. Neurosci Biobehav Rev. 2018; 90: 294-308. doi:10.1016/j.neubiorev.2018.05.007
- 24Montero-Odasso M, Verghese J, Beauchet O, Hausdorff JM. Gait and cognition: a complementary approach to understanding brain function and the risk of falling. J Am Geriatr Soc. 2012; 60(11): 2127-2136. doi:10.1111/j.1532-5415.2012.04209.x
- 25Mirelman A, Rochester L, Reelick M, et al. V-TIME: a treadmill training program augmented by virtual reality to decrease fall risk in older adults: study design of a randomized controlled trial. BMC Neurol. 2013; 13:15. doi:10.1186/1471-2377-13-15
- 26Cipriani A, Higgins JPT, Geddes JR, Salanti G. Conceptual and technical challenges in network meta-analysis. Ann Intern Med. 2013; 159(2): 130-137. doi:10.7326/0003-4819-159-2-201307160-00008
- 27Spina S, Facciorusso S, Cinone N, et al. Effectiveness of robotic balance training on postural instability in patients with mild Parkinson's disease: a pilot, single blind, randomized controlled trial. J Rehabil Med. 2021; 53(2):jrm00154. doi:10.2340/16501977-2793
- 28Parsons TD, Gaggioli A, Riva G. Virtual reality for research in social neuroscience. Brain Sci. 2017; 7(4): 42. doi:10.3390/brainsci7040042
- 29Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. doi:10.1136/bmj.n71
- 30Higgins JP, Li T, Deeks JJ. Choosing effect measures and computing estimates of effect. Cochrane Handbook for Systematic Reviews of Interventions. Wiley; 2019: 143-176.
10.1002/9781119536604.ch6 Google Scholar
- 31Andrade C. Mean difference, standardized mean difference (SMD), and their use in meta-analysis: as simple as it gets. J Clin Psychiatry. 2020; 81(5):20f13681. doi:10.4088/JCP.20f13681
- 32Stocchi F, Sale P, Kleiner AFR, et al. Long-term effects of automated mechanical peripheral stimulation on gait patterns of patients with Parkinson's disease. Int J Rehabil Res. 2015; 38(3): 238-245. doi:10.1097/MRR.0000000000000120
- 33Caudron S, Guerraz M, Eusebio A, Gros JP, Azulay JP, Vaugoyeau M. Evaluation of a visual biofeedback on the postural control in Parkinson's disease. Neurophysiol Clin. 2014; 44(1): 77-86. doi:10.1016/j.neucli.2013.10.134
- 34Nanhoe-Mahabier W, Allum JH, Pasman EP, Overeem S, Bloem BR. The effects of vibrotactile biofeedback training on trunk sway in Parkinson's disease patients. Parkinsonism Relat Disord. 2012; 18(9): 1017-1021. doi:10.1016/j.parkreldis.2012.05.018
- 35Volpe D, Giantin MG, Fasano A. A wearable proprioceptive stabilizer (Equistasi®) for rehabilitation of postural instability in Parkinson's disease: a phase II randomized double-blind, double-dummy, controlled study. PLoS One. 2014; 9(11):e112065. doi:10.1371/journal.pone.0112065
- 36Carpinella I, Cattaneo D, Bonora G, et al. Wearable sensor-based biofeedback training for balance and gait in Parkinson disease: a pilot randomized controlled trial. Arch Phys Med Rehabil. 2017; 98(4): 622-630.e3. doi:10.1016/j.apmr.2016.11.003
- 37van Valkenhoef G, Lu G, de Brock B, Hillege H, Ades AE, Welton NJ. Automating network meta-analysis. Res Synth Methods. 2012; 3(4): 285-299. doi:10.1002/jrsm.1054
- 38Béliveau A, Boyne DJ, Slater J, Brenner D, Arora P. BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network meta-analyses. BMC Med Res Methodol. 2019; 19(1): 196. doi:10.1186/s12874-019-0829-2
- 39Flynn A, Preston E, Dennis S, Canning CG, Allen NE. Home-based exercise monitored with telehealth is feasible and acceptable compared to centre-based exercise in Parkinson's disease: a randomised pilot study. Clin Rehabil. 2021; 35(5): 728-739. doi:10.1177/0269215520976265
- 40Lai B, Bond K, Kim Y, Barstow B, Jovanov E, Bickel CS. Exploring the uptake and implementation of tele-monitored home-exercise programmes in adults with Parkinson's disease: a mixed-methods pilot study. J Telemed Telecare. 2020; 26(1–2): 53-63. doi:10.1177/1357633X18794315
- 41Beck CA, Beran DB, Biglan KM, et al. National randomized controlled trial of virtual house calls for Parkinson disease. Neurology. 2017; 89(11): 1152-1161. doi:10.1212/WNL.0000000000004357
- 42Wilkinson JR, Spindler M, Wood SM, et al. High patient satisfaction with telehealth in Parkinson disease a randomized controlled study. Neurology: Clinical Practice. 2016; 6(3): 241-251. doi:10.1212/CPJ.0000000000000252
- 43Sekimoto S, Oyama G, Hatano T, et al. A randomized crossover pilot study of telemedicine delivered via iPads in Parkinson's disease. Parkinsons Disease. 2019; 2019: 1-7. doi:10.1155/2019/9403295
- 44Ellis TD, Cavanaugh JT, DeAngelis T, et al. Comparative effectiveness of mHealth-supported exercise compared with exercise alone for people with Parkinson disease: randomized controlled pilot study. Phys Ther. 2019; 99(2): 203-216. doi:10.1093/ptj/pzy131
- 45Peppe A, Paravati S, Baldassarre MG, et al. Proprioceptive focal stimulation (Equistasi®) may improve the quality of gait in middle-moderate Parkinson's disease patients. Double-blind, double-dummy, randomized, crossover, Italian multicentric study. Front Neurol. 2019; 10: 10. doi:10.3389/fneur.2019.00998
- 46Pinto C, Pagnussat AS, Rozin Kleiner AF, et al. Automated mechanical peripheral stimulation improves gait parameters in subjects with Parkinson disease and freezing of gait: a randomized clinical trial. Am J Phys Med Rehabil. 2018; 97(6): 383-389. doi:10.1097/PHM.0000000000000890
- 47Galli M, Vicidomini C, Rozin Kleiner AF, et al. Peripheral neurostimulation breaks the shuffling steps patterns in parkinsonian gait: a double blind randomized longitudinal study with automated mechanical peripheral stimulation. Eur J Phys Rehabil Med. 2018; 54(6): 860-865. doi:10.23736/S1973-9087.18.05037-2
- 48El-Tamawy MS, Darwish MH, Khallaf ME. Effects of augmented proprioceptive cues on the parameters of gait of individuals with Parkinson's disease. Ann Indian Acad Neurol. 2012; 15(4): 267-272. doi:10.4103/0972-2327.104334
- 49Unterreiner M, Biedermann C, El-Fahem R, et al. Comparing computer-aided therapy with conventional physiotherapy in Parkinson's disease: an equivalence study. Neurology Asia. 2019; 24(4): 309-315.
- 50Ginis P, Nieuwboer A, Dorfman M, et al. Feasibility and effects of home-based smartphone-delivered automated feedback training for gait in people with Parkinson's disease: a pilot randomized controlled trial. Parkinsonism Relat Disord. 2016; 22: 28-34. doi:10.1016/j.parkreldis.2015.11.004
- 51Pagnussat AS, Kleiner AFR, Rieder CRM, et al. Plantar stimulation in parkinsonians: from biomarkers to mobility—randomized-controlled trial. Restor Neurol Neurosci. 2018; 36(2): 195-205. doi:10.3233/rnn-170744
- 52Subramanian L, Morris MB, Brosnan M, Turner DL, Morris HR, Linden DEJ. Functional magnetic resonance imaging neurofeedback-guided motor imagery training and motor training for Parkinson's disease: randomized trial. Clinical trial. Front Behav Neurosci. 2016; 10: 10. doi:10.3389/fnbeh.2016.00111
- 53Chang MC, Chun MH. The effect of balance training with tetra-ataxiometric posturography on balance function in patients with parkinsonism. NeuroRehabilitation. 2019; 45(3): 379-384. doi:10.3233/nre-192850
- 54Romanato M, Guiotto A, Spolaor F, et al. Changes of biomechanics induced by Equistasi® in Parkinson's disease: coupling between balance and lower limb joints kinematics. Med Biol Eng Comput. 2021; 59(7): 1403-1415. doi:10.1007/s11517-021-02373-3
- 55Shen X, Mak MKY. Balance and gait training with augmented feedback improves balance confidence in people with Parkinson's disease: a randomized controlled trial. Neurorehabil Neural Repair. 2014; 28(6): 524-535. doi:10.1177/1545968313517752
- 56Furnari A, Calabrò RS, De Cola MC, et al. Robotic-assisted gait training in Parkinson's disease: a three-month follow-up randomized clinical trial. Int J Neurosci. 2017; 127(11): 996-1004. doi:10.1080/00207454.2017.1288623
- 57Picelli A, Melotti C, Origano F, et al. Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: a single-blind randomized controlled trial. Clin Rehabil. 2015; 29(4): 339-347. doi:10.1177/0269215514544041
- 58Picelli A, Melotti C, Origano F, Neri R, Waldner A, Smania N. Robot-assisted gait training versus equal intensity treadmill training in patients with mild to moderate Parkinson's disease: a randomized controlled trial. Parkinsonism Relat Disord. 2013; 19(6): 605-610. doi:10.1016/j.parkreldis.2013.02.010
- 59Picelli A, Melotti C, Origano F, et al. Robot-assisted gait training in patients with parkinson disease: a randomized controlled trial. Neurorehabil Neural Repair. 2012; 26(4): 353-361. doi:10.1177/1545968311424417
- 60Picelli A, Melotti C, Origano F, Waldner A, Gimigliano R, Smania N. Does robotic gait training improve balance in Parkinson's disease? A randomized controlled trial. Parkinsonism Relat Disord. 2012; 18(8): 990-993. doi:10.1016/j.parkreldis.2012.05.010
- 61Capecci M, Pournajaf S, Galafate D, et al. Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial. Ann Phys Rehabil Med. 2019; 62(5): 303-312. doi:10.1016/j.rehab.2019.06.016
- 62Carda S, Invernizzi M, Baricich A, Comi C, Croquelois A, Cisari C. Robotic gait training is not superior to conventional treadmill training in parkinson disease: a single-blind randomized controlled trial. Neurorehabil Neural Repair. 2012; 26(9): 1027-1034. doi:10.1177/1545968312446753
- 63Galli M, Cimolin V, De Pandis MF, et al. Robot-assisted gait training versus treadmill training in patients with Parkinson's disease: a kinematic evaluation with gait profile score. Funct Neurol. 2016; 31(3): 163-170. doi:10.11138/fneur/2016.31.3.163
- 64Kim H, Kim E, Yun SJ, et al. Robot-assisted gait training with auditory and visual cues in Parkinson's disease: a randomized controlled trial. Ann Phys Rehabil Med. 2022; 65(3):101620. doi:10.1016/j.rehab.2021.101620
- 65Kegelmeyer DA, Minarsch R, Kostyk SK, Kline D, Smith R, Kloos AD. Use of a robotic walking device for home and community mobility in Parkinson disease: a randomized controlled trial. J Neurol Phys Ther. 2024; 48(2): 102-111. doi:10.1097/npt.0000000000000467
- 66Ribas CG, Alves da Silva L, Correa MR, Teive HG, Valderramas S. Effectiveness of exergaming in improving functional balance, fatigue and quality of life in Parkinson's disease: a pilot randomized controlled trial. Parkinsonism Relat Disord. 2017; 38: 13-18. doi:10.1016/j.parkreldis.2017.02.006
- 67Pazzaglia C, Imbimbo I, Tranchita E, et al. Comparison of virtual reality rehabilitation and conventional rehabilitation in Parkinson's disease: a randomised controlled trial. Physiotherapy (United Kingdom). 2020; 106: 36-42. doi:10.1016/j.physio.2019.12.007
- 68Ferraz DD, Trippo KV, Duarte GP, Neto MG, Bernardes Santos KO, Filho JO. The effects of functional training, bicycle exercise, and exergaming on walking capacity of elderly patients with Parkinson disease: a pilot randomized controlled single-blinded trial. Arch Phys Med Rehabil. 2018; 99(5): 826-833. doi:10.1016/j.apmr.2017.12.014
- 69Feng H, Li C, Liu J, et al. Virtual reality rehabilitation versus conventional physical therapy for improving balance and gait in parkinson's disease patients: a randomized controlled trial. Med Sci Monit. 2019; 25: 4186-4192. doi:10.12659/MSM.916455
- 70Pompeu JE, Mendes FADS, Silva KGD, et al. Effect of Nintendo Wii™based motor and cognitive training on activities of daily living in patients with Parkinson's disease: a randomised clinical trial. Physiotherapy (United Kingdom). 2012; 98(3): 196-204. doi:10.1016/j.physio.2012.06.004
10.1016/j.physio.2012.06.004 Google Scholar
- 71Tollar J, Nagy F, Hortobágyi T. Vastly different exercise programs similarly improve parkinsonian symptoms: a randomized clinical trial. Gerontology. 2019; 65(2): 120-127. doi:10.1159/000493127
- 72Shih M-C, Wang R-Y, Cheng S-J, Yang Y-R. Effects of a balance-based exergaming intervention using the Kinect sensor on posture stability in individuals with Parkinson's disease: a single-blinded randomized controlled trial. J Neuroeng Rehabil. 2016; 13(1): 78. doi:10.1186/s12984-016-0185-y
- 73Gandolfi M, Geroin C, Dimitrova E, et al. Virtual reality telerehabilitation for postural instability in Parkinson's disease: a multicenter, single-blind, randomized, controlled trial. Biomed Res Int. 2017; 2017: 1-11. doi:10.1155/2017/7962826
10.1155/2017/7962826 Google Scholar
- 74Santos P, Machado T, Santos L, Ribeiro N, Melo A. Efficacy of the Nintendo Wii combination with conventional exercises in the rehabilitation of individuals with Parkinson's disease: a randomized clinical trial. NeuroRehabilitation. 2019; 45(2): 255-263. doi:10.3233/NRE-192771
- 75Yang WC, Wang HK, Wu RM, Lo CS, Lin KH. Home-based virtual reality balance training and conventional balance training in Parkinson's disease: a randomized controlled trial. J Formos Med Assoc. 2016; 115(9): 734-743. doi:10.1016/j.jfma.2015.07.012
- 76Liao YY, Yang YR, Wu YR, Wang RY. Virtual reality-based Wii fit training in improving muscle strength, sensory integration ability, and walking abilities in patients with Parkinson's disease: a randomized control trial. Int J Gerontol. 2015; 9(4): 190-195. doi:10.1016/j.ijge.2014.06.007
10.1016/j.ijge.2014.06.007 Google Scholar
- 77Liao YY, Yang YR, Cheng SJ, Wu YR, Fuh JL, Wang RY. Virtual reality-based training to improve obstacle-crossing performance and dynamic balance in patients with Parkinson's disease. Neurorehabil Neural Repair. 2015; 29(7): 658-667. doi:10.1177/1545968314562111
- 78Tollár J, Nagy F, Kovács N, Hortobágyi T. A high-intensity multicomponent agility intervention improves Parkinson patients' clinical and motor symptoms. Arch Phys Med Rehabil. 2018; 99(12): 2478-2484.e1. doi:10.1016/j.apmr.2018.05.007
- 79van den Heuvel MRC, Kwakkel G, Beek PJ, Berendse HW, Daffertshofer A, van Wegen EEH. Effects of augmented visual feedback during balance training in Parkinson's disease: a pilot randomized clinical trial. Parkinsonism Relat Disord. 2014; 20(12): 1352-1358. doi:10.1016/j.parkreldis.2014.09.022
- 80Pedreira G, Prazeres A, Cruz D, Gomes I, Monteiro L, Melo A. Virtual games and quality of life in Parkinson's disease: a randomised controlled trial. APD. 2013; 2(4): 97-101. doi:10.4236/apd.2013.24018
10.4236/apd.2013.24018 Google Scholar
- 81Kashif M, Ahmad A, Bandpei MAM, Gilani SA, Hanif A, Iram H. Combined effects of virtual reality techniques and motor imagery on balance, motor function and activities of daily living in patients with Parkinson's disease: a randomized controlled trial. BMC Geriatr. 2022; 22(1): 381. doi:10.1186/s12877-022-03035-1
- 82Kafle A, Rizvi SR. Effect of wii-based motor and cognitive training on activities of daily living in patients with Parkinson's disease. Indian J Physiother Occupat Ther. 2021; 15: 1-7.
10.37506/ijpot.v15i3.16157 Google Scholar
- 83Goffredo M, Baglio F, De Icco R, et al. Efficacy of non-immersive virtual reality-based telerehabilitation on postural stability in Parkinson's disease: a multicenter randomized controlled trial. Eur J Phys Rehabil Med. 2023; 59(6): 689-696. doi:10.23736/s1973-9087.23.07954-6
- 84Barry E, Galvin R, Keogh C, Horgan F, Fahey T. Is the timed up and go test a useful predictor of risk of falls in community dwelling older adults: a systematic review and meta-analysis. BMC Geriatr. 2014; 14:14. doi:10.1186/1471-2318-14-14
- 85Duque G, Boersma D, Loza-Diaz G, et al. Effects of balance training using a virtual-reality system in older fallers. Clin Interv Aging. 2013; 8: 257-263. doi:10.2147/CIA.S41453
- 86Cho KH, Lee KJ, Song CH. Virtual-reality balance training with a video-game system improves dynamic balance in chronic stroke patients. Tohoku J Exp Med. 2012; 228(1): 69-74. doi:10.1620/tjem.228.69
- 87Kalilani L, Asgharnejad M, Palokangas T, Durgin T. Comparing the incidence of falls/fractures in Parkinson's disease patients in the US population. PLoS One. 2016; 11(9):e0161689. doi:10.1371/journal.pone.0161689
- 88Brognara L, Cauli O. Mechanical plantar foot stimulation in Parkinson's disease: a scoping review. Diseases. 2020; 8(2): 12. doi:10.3390/diseases8020012
- 89de la Torre-Díez I, López-Coronado M, Vaca C, Aguado JS, de Castro C. Cost-utility and cost-effectiveness studies of telemedicine, electronic, and mobile health systems in the literature: a systematic review. Telemed J E Health. 2015; 21(2): 81-85. doi:10.1089/tmj.2014.0053
- 90Carpino G, Pezzola A, Urbano M, Guglielmelli E. Assessing effectiveness and costs in robot-mediated lower limbs rehabilitation: a meta-analysis and state of the art. J Healthc Eng. 2018; 2018:7492024. doi:10.1155/2018/7492024
- 91Islam MK, Brunner I. Cost-analysis of virtual reality training based on the virtual reality for upper extremity in subacute stroke (VIRTUES) trial. Int J Technol Assess Health Care. 2019; 35(5): 373-378. doi:10.1017/s026646231900059x
- 92Brognara L, Navarro-Flores E, Iachemet L, Serra-Catalá N, Cauli O. Beneficial effect of foot plantar stimulation in gait parameters in individuals with Parkinson's disease. Brain Sci. 2020; 10(2): 69. doi:10.3390/brainsci10020069
- 93Norouzi-Gheidari N, Hernandez A, Archambault PS, Higgins J, Poissant L, Kairy D. Feasibility, safety and efficacy of a virtual reality exergame system to supplement upper extremity rehabilitation post-stroke: a pilot randomized clinical trial and proof of principle. Int J Environ Res Public Health. 2019; 17(1):113. doi:10.3390/ijerph17010113
- 94Rocon E, Ruiz AF, Raya R, et al. Human–robot physical interaction. In: JL Pons, ed. Wearable Robots. John Wiley & Sons, Ltd; 2008: 127-163.
10.1002/9780470987667.ch5 Google Scholar
- 95Bessler J, Prange-Lasonder GB, Schaake L, et al. Safety assessment of rehabilitation robots: a review identifying safety skills and current knowledge gaps. Front Robot AI. 2021; 8:602878. doi:10.3389/frobt.2021.602878
- 96Lu Y, Ge Y, Chen W, et al. The effectiveness of virtual reality for rehabilitation of Parkinson disease: an overview of systematic reviews with meta-analyses. Syst Rev. 2022; 11(1): 50. doi:10.1186/s13643-022-01924-5
Citing Literature
