Clinical trial NCT06543758: Effectiveness and Safety of At-home Gait Rehabilitation Using Wearable Exoskeletal Robot
Official title: Study to Verify Effectiveness and Safety of At-home Gait Rehabilitation Using Wearable Exoskeletal Robot to Improve Gait in Stroke Patients, Investigator Initiated, Single Center, Single Group Trial
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: PHASE4
Conditions: Stroke
Gait, Spastic
Gait, Hemiplegic
Keywords: Wearable robot
Exoskeletal robot
At-home rehabilitation
Gait rehabilitation
Stroke
Lead sponsor: Yonsei University
Sponsor class: OTHER
First posted: 2024-08-09
Enrollment: 16
Sex: ALL
Minimum age (years): 19
Maximum age (years): 79
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Researchers will compare pre- and post-intervention walking speeds, body composition, spatiotemporal parameters, balance, and satisfaction survey in participants and does not establish a control group.
Primary purpose: TREATMENT

Brief summary: The goal of this clinical trial is to evaluate the effectiveness and safety of a home-based robotic-assisted gait rehabilitation service using a wearable exoskeletal robot for stroke patients.

The main questions it aims to answer are:

* Can home-based robotic-assisted gait training improve walking speed in stroke patients?
* Does this intervention enhance body composition, gait patterns, balance in participants?
* How satisfied are participants with the use of the wearable exoskeletal robot ?

Researchers will compare pre- and post-intervention walking speeds, body composition, spatiotemporal parameters, balance, and satisfaction survey and does not establish a control group.

Participants will:

* Wear a wearable exoskeletal robot for gait training.
* Undergo 10 sessions of 30-minute gait training over 4 weeks at home or in nearby indoor spaces.
* Participate in physical function assessments including the 10-meter walk test, Timed Up and Go (TUG) test, and Berg Balance Scale before and after the intervention.
* Complete quality of life and depression inventories before and after the intervention.

Detailed description: After obtaining informed consent, a screening test is conducted. The screening test includes a review of the participant's baseline symptoms and signs, medical history, and medication usage, followed by a physical examination and assessment of gait status, including the use of assistive devices and gait patterns. Participants who pass the screening test undergo an initial assessment within seven days.

The initial assessment includes physical function tests such as the 10-meter walk test, the Timed Up and Go (TUG) test, and the Berg Balance Scale, along with quality of life and Beck Depression Inventory assessments. Participants who complete the initial assessment begin robotic-assisted gait training within two days.

The training is conducted using a wearable exoskeletal robot for gait training at home or in nearby indoor spaces. The training lasts for four weeks, with sessions held 2-3 times per week, totaling 10 sessions, each lasting 30 minutes.

After four weeks, the robotic-assisted gait training concludes, and within two days, an endpoint assessment identical to the initial assessment is performed. Satisfaction with the wearable exoskeletal robot is also evaluated.

Any device malfunctions are addressed and documented. The usage and satisfaction levels of the wearable exoskeletal robot are analyzed, and pre- and post-training assessment metrics are compared.

Eligibility criteria: Inclusion Criteria:

1. adults aged 19 to 79 years (based on the age on their national ID at the time of consent)
2. individuals diagnosed with cerebral infarction or intracerebral hemorrhage confirmed by MRI or CT.
3. patients who have passed at least one month since stroke diagnosis.
4. individuals exhibiting spastic hemiplegic gait patterns due to stroke.
5. patients with a Functional Ambulatory Category score of less than 4.
6. individuals who can sit on the edge of a bed without assistance and stand for 10 seconds with or without assistance.
7. individuals with sufficient cognitive ability to follow simple instructions and understand the study's content and purpose (Mini-Mental State Examination score \>= 20)

Exclusion Criteria:

1. individuals with severe joint contractures or osteoporosis, or untreated fractures that contraindicate weight-bearing on the lower limbs.
2. individuals with skin conditions or open wounds that prevent device usage.
3. individuals with significant differences in leg length.
4. individuals with severe deformities or joint contractures in the lower limbs.
5. individuals at high risk of fractures due to conditions like osteoporosis.
6. individuals unable to maintain a sitting or standing position independently.
7. individuals with severe lower limb spasticity (Modified Ashworth Scale grade 2 or higher).
8. individuals with severe cognitive impairment (Mini-Mental State Examination score \< 20), delirium, or severe language impairment that hinders cooperation with wearable exoskeletal robot gait training.
9. individuals unable to maintain prolonged standing or walking due to conditions like orthostatic hypotension or cardiopulmonary impairment.
10. individuals with conditions affecting gait, such as peripheral neuropathy, Parkinsonism, or those with alcohol dependence or severe diabetes.
11. pregnant women or those who could become pregnant.
12. individuals participating in other clinical trials.
13. individuals at high risk of falls or bleeding due to conditions like coagulopathies.
14. individuals shorter than 140 cm, taller than 190 cm, or weighing over 80 kg.
15. individuals with other clinical findings deemed inappropriate for the study by the principal investigator or study coordinator.

Primary outcomes:
measure: 10MWT (10 meter walk test)
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
Secondary outcomes:
measure: Health-related quality of life measurement (36-item Short Form Survey Instrument, SF-36)
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Beck depression inventory (BDI)
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Body composition analysis
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Spatiotemporal parameters of walking
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Timed up and go test (TUG)
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Berg Balance Scale
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
measure: Satisfaction evaluation
timeFrame: This session will be performed at baseline and after the intervention. A baseline assessment will be conducted within 2 days before the robotic-assisted gait training, and an end-point assessment will be conducted within 2 days after the gait training.
Other outcomes:
Locations:
city: Yongin-si
country: Korea, Republic of
facility: Yongin Severance Hospital
state: Gyeonggi-do
Study officials:
affiliation: Severance Hospital
name: Na Young Kim, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Salzman B. Gait and balance disorders in older adults. Am Fam Physician. 2010 Jul 1;82(1):61-8.
citation: Bennett DA, Beckett LA, Murray AM, Shannon KM, Goetz CG, Pilgrim DM, Evans DA. Prevalence of parkinsonian signs and associated mortality in a community population of older people. N Engl J Med. 1996 Jan 11;334(2):71-6. doi: 10.1056/NEJM199601113340202.
citation: Lange AK, Vanwanseele B, Fiatarone Singh MA. Strength training for treatment of osteoarthritis of the knee: a systematic review. Arthritis Rheum. 2008 Oct 15;59(10):1488-94. doi: 10.1002/art.24118.
citation: Chou CH, Hwang CL, Wu YT. Effect of exercise on physical function, daily living activities, and quality of life in the frail older adults: a meta-analysis. Arch Phys Med Rehabil. 2012 Feb;93(2):237-44. doi: 10.1016/j.apmr.2011.08.042.
citation: De Luca R, Maresca G, Balletta T, Cannavo A, Leonardi S, Latella D, Maggio MG, Portaro S, Naro A, Calabro RS. Does overground robotic gait training improve non-motor outcomes in patients with chronic stroke? Findings from a pilot study. J Clin Neurosci. 2020 Nov;81:240-245. doi: 10.1016/j.jocn.2020.09.070. Epub 2020 Oct 15.
citation: Chin LF, Lim WS, Kong KH. Evaluation of robotic-assisted locomotor training outcomes at a rehabilitation centre in Singapore. Singapore Med J. 2010 Sep;51(9):709-15.
citation: Schwartz I, Meiner Z. Robotic-assisted gait training in neurological patients: who may benefit? Ann Biomed Eng. 2015 May;43(5):1260-9. doi: 10.1007/s10439-015-1283-x. Epub 2015 Feb 28.
citation: Gajdosik RL, Bohannon RW. Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity. Phys Ther. 1987 Dec;67(12):1867-72. doi: 10.1093/ptj/67.12.1867.
citation: Gregson JM, Leathley M, Moore AP, Sharma AK, Smith TL, Watkins CL. Reliability of the Tone Assessment Scale and the modified Ashworth scale as clinical tools for assessing poststroke spasticity. Arch Phys Med Rehabil. 1999 Sep;80(9):1013-6. doi: 10.1016/s0003-9993(99)90053-9.
citation: 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 Oct;88(10):1314-9. doi: 10.1016/j.apmr.2007.06.764.
citation: Tombaugh TN, McIntyre NJ. The mini-mental state examination: a comprehensive review. J Am Geriatr Soc. 1992 Sep;40(9):922-35. doi: 10.1111/j.1532-5415.1992.tb01992.x.
citation: Plank LD. Dual-energy X-ray absorptiometry and body composition. Curr Opin Clin Nutr Metab Care. 2005 May;8(3):305-9. doi: 10.1097/01.mco.0000165010.31826.3d.
citation: Rachner TD, Khosla S, Hofbauer LC. Osteoporosis: now and the future. Lancet. 2011 Apr 9;377(9773):1276-87. doi: 10.1016/S0140-6736(10)62349-5. Epub 2011 Mar 28.
citation: Chard T. Pregnancy tests: a review. Hum Reprod. 1992 May;7(5):701-10. doi: 10.1093/oxfordjournals.humrep.a137722.
citation: Anderson C, Laubscher S, Burns R. Validation of the Short Form 36 (SF-36) health survey questionnaire among stroke patients. Stroke. 1996 Oct;27(10):1812-6. doi: 10.1161/01.str.27.10.1812.
citation: Richter P, Werner J, Heerlein A, Kraus A, Sauer H. On the validity of the Beck Depression Inventory. A review. Psychopathology. 1998;31(3):160-8. doi: 10.1159/000066239.
citation: Andreoli A, Garaci F, Cafarelli FP, Guglielmi G. Body composition in clinical practice. Eur J Radiol. 2016 Aug;85(8):1461-8. doi: 10.1016/j.ejrad.2016.02.005. Epub 2016 Feb 15.
citation: Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. doi: 10.1016/0021-9681(87)90171-8.
citation: Godi M, Franchignoni F, Caligari M, Giordano A, Turcato AM, Nardone A. Comparison of reliability, validity, and responsiveness of the mini-BESTest and Berg Balance Scale in patients with balance disorders. Phys Ther. 2013 Feb;93(2):158-67. doi: 10.2522/ptj.20120171. Epub 2012 Sep 27.
citation: Bang DH, Shin WS. Effects of robot-assisted gait training on spatiotemporal gait parameters and balance in patients with chronic stroke: A randomized controlled pilot trial. NeuroRehabilitation. 2016 Apr 6;38(4):343-9. doi: 10.3233/NRE-161325.
citation: Nedergard H, Arumugam A, Sandlund M, Brandal A, Hager CK. Effect of robotic-assisted gait training on objective biomechanical measures of gait in persons post-stroke: a systematic review and meta-analysis. J Neuroeng Rehabil. 2021 Apr 16;18(1):64. doi: 10.1186/s12984-021-00857-9.
citation: Park GM, Cho SH, Hong JT, Kim DH, Shin JC. Effects and Safety of Wearable Exoskeleton for Robot-Assisted Gait Training: A Retrospective Preliminary Study. J Pers Med. 2023 Apr 18;13(4):676. doi: 10.3390/jpm13040676.