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Kim H, Shin J, Kim Y, Lee Y, You JSH. Identifying best fall-related balance factors and robotic-assisted gait training attributes in 105 post-stroke patients using clinical machine learning models. NeuroRehabilitation 2024:NRE240116. [PMID: 39031394 DOI: 10.3233/nre-240116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2024]
Abstract
BACKGROUND Despite the promising effects of robot-assisted gait training (RAGT) on balance and gait in post-stroke rehabilitation, the optimal predictors of fall-related balance and effective RAGT attributes remain unclear in post-stroke patients at a high risk of fall. OBJECTIVE We aimed to determine the most accurate clinical machine learning (ML) algorithm for predicting fall-related balance factors and identifying RAGT attributes. METHODS We applied five ML algorithms- logistic regression, random forest, decision tree, support vector machine (SVM), and extreme gradient boosting (XGboost)- to a dataset of 105 post-stroke patients undergoing RAGT. The variables included the Berg Balance Scale score, walking speed, steps, hip and knee active torques, functional ambulation categories, Fugl- Meyer assessment (FMA), the Korean version of the Modified Barthel Index, and fall history. RESULTS The random forest algorithm excelled (receiver operating characteristic area under the curve; AUC = 0.91) in predicting balance improvement, outperforming the SVM (AUC = 0.76) and XGboost (AUC = 0.71). Key determinants identified were knee active torque, age, step count, number of RAGT sessions, FMA, and hip torque. CONCLUSION The random forest algorithm was the best prediction model for identifying fall-related balance and RAGT determinants, highlighting the importance of key factors for successful RAGT outcome performance in fall-related balance improvement.
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Affiliation(s)
- Heejun Kim
- Department of Physical Therapy, Sports Movement Artificial Robotics Technology (SMART) Institute, Yonsei University, Wonju, Republic of Korea
- Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea
| | - Jiwon Shin
- Department of Physical Therapy, Sports Movement Artificial Robotics Technology (SMART) Institute, Yonsei University, Wonju, Republic of Korea
- Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea
| | - Yunhwan Kim
- Department of Physical Therapy, Sports Movement Artificial Robotics Technology (SMART) Institute, Yonsei University, Wonju, Republic of Korea
- Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea
| | - Yongseok Lee
- Department of Rehabilitation Medicine, Myongji Choonhey Rehabilitation Hospital, Seoul, Republic of Korea
| | - Joshua Sung H You
- Department of Physical Therapy, Sports Movement Artificial Robotics Technology (SMART) Institute, Yonsei University, Wonju, Republic of Korea
- Department of Physical Therapy, Yonsei University, Wonju, Republic of Korea
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Alashram AR. Effectiveness of combined robotics and virtual reality on lower limb functional ability in stroke survivors: A systematic review of randomized controlled trials. Neurol Sci 2024:10.1007/s10072-024-07618-1. [PMID: 38829579 DOI: 10.1007/s10072-024-07618-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Accepted: 05/22/2024] [Indexed: 06/05/2024]
Abstract
Lower limb impairments are common consequences of stroke. Robotics and virtual reality (VR) play crucial roles in improving lower limb function post-stroke. This review aims to assess the effects of combined robot and VR interventions on lower limb functional ability poststroke and to provide recommendations for future studies in the rehabilitation field. PubMed, SCOPUS, CINAHL, MEDLINE, EMBASE, and Web of Science were searched from inception to March 1, 2024. Randomized controlled trials (RCTs) involving patients with a stroke, administering combined robot and VR compared with passive (i.e., rest) or active (any intervention), and including at least one outcome evaluating lower limb function (i.e., balance, gait, mobility, muscle tone, muscle strength, range of motion) or activities of daily living were selected. The Cochrane Collaboration tool was employed to evaluate the risk of bias in the included studies. Nine studies met the eligibility criteria. In total, 364 stroke survivors (Mean age 55.62 years) were involved in this review. According to the Cochrane Collaboration tool, five studies were classified as "high quality," "moderate quality" (n=3), and "low quality" (n=1). There are mixed findings on the effects of combined robot and VR on lower limb functional ability in stroke survivors. The evidence for the effects of combined robot and VR on lower limb functional ability post-stroke is promising. Further trials with long-term follow-up are strongly warranted to understand the immediate and long-term effect of combined robot and VR intervention on various lower limb impairments and to define the optimal treatment protocols.
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Affiliation(s)
- Anas R Alashram
- Department of Physiotherapy, Middle East University, Airport Road 11831, Amman, Jordan.
- Applied Science Research Center, Applied Science Private University, Amman, Jordan.
- Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Roma Open University, Rome, Italy.
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Wen S, Huang R, Liu L, Zheng Y, Yu H. Robotic exoskeleton-assisted walking rehabilitation for stroke patients: a bibliometric and visual analysis. Front Bioeng Biotechnol 2024; 12:1391322. [PMID: 38827036 PMCID: PMC11140054 DOI: 10.3389/fbioe.2024.1391322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 04/08/2024] [Indexed: 06/04/2024] Open
Abstract
Objective This study aimed to conduct a bibliometric analysis of the literature on exoskeleton robot assisted walking rehabilitation for stroke patients in the Web of Science Core Collection over the past decade. Method Retrieved literature on exoskeleton robot assisted gait training for stroke hemiplegic patients from the Web of Science Core Collection from 1 January 2014 to 31 January 2024. The search method was topic search, and the types of documents were "article, meeting abstract, review article, early access." CiteSpace was used to analyze the search results from countries, institutions, keywords, cited references and cited authors. Result A total of 1,349 articles were retrieved, and 1,034 were ultimately included for visualization analysis. The annual publication volume showed an upward trend, with countries, institutions, and authors from Europe and America in a leading position. The core literature was also published by authors from European and American countries. The keywords were divided into 8 clusters: # 0 soft robotic exit, # 1 robot assisted gain training, # 2 multiple scales, # 3 magnetic rheological brake, # 4 test retest reliability, # 5 electromechanical assisted training, # 6 cerebra salary, and # 7 slow gain. The early research direction focused on the development of exoskeleton robots, verifying their reliability and feasibility. Later, the focus was on the combination of exoskeleton robot with machine learning and other technologies, rehabilitation costs, and patient quality of life. Conclusion This study provides a visual display of the research status, development trends, and research hotspots, which helps researchers in this field to grasp the research hotspots and choose future research directions.
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Affiliation(s)
- Shuangshuang Wen
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Ruina Huang
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Lu Liu
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Yan Zheng
- Shenzhen Health Capacity Building and Continuing Education Center, Shenzhen, China
| | - Hegao Yu
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
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Park YH, Lee DH, Lee JH. A Comprehensive Review: Robot-Assisted Treatments for Gait Rehabilitation in Stroke Patients. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:620. [PMID: 38674266 PMCID: PMC11052271 DOI: 10.3390/medicina60040620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/02/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024]
Abstract
Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a groundbreaking method to improve motor recovery and enhance the quality of life for stroke survivors. This review investigates the effectiveness and application of various RAGT systems, including both end-effector and exoskeleton robots, in facilitating gait enhancements. The selection process for this comprehensive analysis involved a meticulous review of the literature from databases such as PubMed, the Cochrane Library, and EMBASE, focusing on studies published between 2018 and 2023. Ultimately, 27 studies met the criteria and were included in the final analysis. The focus of these studies was on the various RAGT systems and their role in promoting gait and balance improvements. The results of these studies conclusively show that patients experience significant positive effects from RAGT, and when combined with other physiotherapy methods, the outcomes are notably superior in enhancing functional ambulation and motor skills. This review emphasizes RAGT's capability to deliver a more customized and effective rehabilitation experience, highlighting the importance of tailoring interventions to meet the specific needs of each patient.
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Affiliation(s)
- Yong-Hwa Park
- Immanuel Medical Rehabilitation Hospital, 2140, Cheongnam-ro, Cheongju-si 28702, Republic of Korea; (Y.-H.P.); (D.-H.L.)
| | - Dae-Hwan Lee
- Immanuel Medical Rehabilitation Hospital, 2140, Cheongnam-ro, Cheongju-si 28702, Republic of Korea; (Y.-H.P.); (D.-H.L.)
| | - Jung-Ho Lee
- Department of Physical Therapy, University of Kyungdong, 815, Gyeonhwon-ro, Munmak-eup, Wonju-si 26495, Republic of Korea
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Podurgiel J, Piscitelli D, Denegar C. Challenges in applying minimal clinically important difference: a critical review. Int J Rehabil Res 2024; 47:10-19. [PMID: 38250825 DOI: 10.1097/mrr.0000000000000613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
Healthcare clinicians strive to make meaningful changes in patient function and participation. A minimal clinically important difference (MCID) is an estimate of the magnitude of change needed to be meaningful to a patient. Clinicians and investigators may assume that a cited MCID is a valid and generalizable estimate of effect. There are, however, at least two concerns about this assumption. First, multiple methods exist for calculating an MCID that can yield divergent values and raise doubt as to which one to apply. Second, MCID values may be erroneously generalized to patients with dissimilar health conditions. With this in mind, we reviewed the methods used to calculate MCID and citations of reported MCID values for outcome measures commonly used in neurologic, orthopedic, and geriatric populations. Our goal was to assess whether the calculation methods were acknowledged in the cited work and whether the enrolled patients were similar to the sample from which the MCID estimate was derived. We found a concerning variation in the methods employed to estimate MCID. We also found a lack of transparency in identifying calculation methods and applicable health conditions in the cited work. Thus, clinicians and researchers must pay close attention and exercise caution in assuming changes in patient status that exceed a specific MCID reflect meaningful improvements in health status. A common standard for the calculation and reporting of an MCID is needed to address threats to the validity of conclusions drawn from the interpretation of an MCID.
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Affiliation(s)
- Joseph Podurgiel
- Doctor of Physical Therapy Program, Department of Kinesiology, University of Connecticut, Storrs, Connecticut, USA
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Huang L, Huang HL, Dang XW, Wang YJ. Effect of Body Weight Support Training on Lower Extremity Motor Function in Patients With Spinal Cord Injury: A Systematic Review and Meta-analysis. Am J Phys Med Rehabil 2024; 103:149-157. [PMID: 37535636 DOI: 10.1097/phm.0000000000002320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
OBJECTIVES The aims of the study are to systematically evaluate the effect of body weight support training on lower extremity motor function(s) in patients with spinal cord injury and to compare the effect differences among three body weight support training methods. DESIGN PubMed, Web of Science, Cochrane Library, Embase, CNKI, CBM, China Scientific Journal, and Wan Fang databases were searched until December 31, 2022. Meta-analysis and network meta-analysis were conducted using RevMan 5.4 and ADDIS 1.16.8. RESULTS Nineteen randomized controlled trials involving 864 patients were included. The meta-analysis showed that body weight support training could improve lower extremity motor scores according to the International Standards for Neurological Classification of Spinal Cord Injury standard (mean difference = 6.38, 95% confidence interval = 3.96-8.80, P < 0.05), walking speed (standard mean difference = 0.77, 95% confidence interval = 0.52-1.02, P < 0.05), and modified Barthel Index scores (mean difference = 9.85, 95% confidence interval = 8.39-11.30, P < 0.05). The network meta-analysis showed no significant difference among the three body weight support training methods for improving lower extremity motor scores in patients with spinal cord injury. The best probability ranking of the body weight support training methods for improving lower extremity motor scores in patients with spinal cord injury was robot-assisted gait training ( P = 0.60), followed by aquatic exercise ( P = 0.21) and body weight support training ( P = 0.19). CONCLUSIONS Body weight support training can improve lower extremity motor score in patients with spinal cord injury. No significant difference was observed among the three body weight support training methods, but robot-assisted gait training may produce the best effect.
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Affiliation(s)
- Lei Huang
- From the College of Rehabilitation Medicine, Shandong University of Traditional Chinese Medicine, Changqing District, Jinan City, China
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Parsaei M, Amanollahi M, TaghaviZanjani F, Khanmohammadi S, Jameie M, Naser Moghadasi A. Effects of non-pharmacological interventions on gait and balance of persons with Multiple Sclerosis: A narrative review. Mult Scler Relat Disord 2024; 82:105415. [PMID: 38211505 DOI: 10.1016/j.msard.2023.105415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Multiple Sclerosis (MS) is among the most common reasons for disability in young adults. Mobility impairment, primarily related to gait and balance, is ranked as the preeminent concern among persons with MS (PwMS). Gait and balance dysfunction can directly affect the quality of life and activities of daily life in PwMS, hence the importance of effective treatment strategies. Previous studies have demonstrated the positive effect of various non-pharmacological rehabilitation methods, including physiotherapy and electrical stimulation, on gait and mobility in PwMS. Non-pharmacological methods can be tailored to the individual needs and abilities of each patient, allowing healthcare providers to create personalized training programs. Furthermore, these methods typically result in minimal or no side effects. PURPOSE This review provides a comprehensive overview of an array of non-pharmacological treatment approaches aimed at enhancing ambulatory performance in PwMS. METHODS We performed a narrative review of the original papers available in PubMed, investigating the effects of different nonmedical approaches on the gait and balance performance of the PwMS. Reviewed treatment approaches include "exercise, physical rehabilitation, dual-task (DT) rehabilitation, robot-assisted rehabilitation, virtual reality-assisted rehabilitation, game training, electrical stimulation devices, auditory stimulation, visual feedback, and shoe insoles". RESULTS AND CONCLUSIONS Eighty articles were meticulously reviewed. Our study highlights the positive effects of non-pharmacological interventions on patients' quality of life, reducing disability, fatigue, and muscle spasticity. While some methods, including exercise and physiotherapy, showed substantial promise, further research is needed to evaluate whether visual biofeedback and auditory stimulation are preferable over conventional approaches. Additionally, approaches such as functional electrical stimulation, non-invasive brain stimulation, and shoe insoles demonstrate substantial short-term benefits, prompting further investigation into their long-term effects. Non-pharmacological interventions can serve as a valuable complement to medication-based approaches.
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Affiliation(s)
- Mohammadamin Parsaei
- Maternal, Fetal, and Neonatal Research Center, Family Health Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Mobina Amanollahi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | - Melika Jameie
- Neuroscience Research Center, Iran University of Medical Sciences, Tehran, Iran; Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Abdorreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran.
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Yang J, Gong Y, Yu L, Peng L, Cui Y, Huang H. Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials. BMJ Open 2023; 13:e074481. [PMID: 37709309 PMCID: PMC10503387 DOI: 10.1136/bmjopen-2023-074481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
OBJECTIVES Numbers of research have reported the usage of robot-assisted gait training for walking restoration post-stroke. However, no consistent conclusion has been reached yet about the efficacy of exoskeleton robot-assisted training (ERAT) on gait function of stroke survivors, especially during the chronic period. We conducted a systematic review to investigate the efficacy of ERAT on gait function for chronic stroke survivors. DESIGN This review followed the Participant, Intervention, Comparison and Outcome principle. DATA SOURCES PubMed, Cochrane Library, Web of Science, Embase and Cumulative Index to Nursing and Allied Health Literature databases were systematically searched until December 2022. ELIGIBILITY CRITERIA Only randomised controlled trials (RCTs) were included and these RCTs took patients who had a chronic stroke as participants, exoskeleton robot-assisted gait training as intervention, regular rehabilitation therapy as comparison and gait-related functional assessments as outcomes. DATA EXTRACTION AND SYNTHESIS Data extraction and synthesis used the reporting checklist for systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The risk of bias and methodological quality of included studies were evaluated by two independent investigators under the guidance of Cochrane risk of bias. RESULTS Out of 278 studies, a total of 10 studies (n=323, mean age 57.6 years, 63.2% males) were identified in this systematic review. According to the Cochrane risk of bias, the quality of these studies was assessed as low risk. Six studies reported favourable effects of ERAT on gait function involving gait performance, balance function and physical endurance, and the ERAT group was significantly superior when compared with the control group. In contrast, the other four trials showed equal or negative effects of ERAT considering different study designs. All the included studies did not claim any serious adverse events. CONCLUSION ERAT could be an efficient intervention to improve gait function for individuals who had a chronic stroke. However, more rigorously designed trials are required to draw more solid evidence. PROSPERO REGISTRATION NUMBER CRD42023410796.
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Affiliation(s)
- Jinchao Yang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yu Gong
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lei Yu
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Laiying Peng
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yuanfen Cui
- Department of Pain Management, Wuhan No 1 Hospital, Wuhan, China
| | - Hailong Huang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
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