Home-based Rehabilitation Monitoring System With Wearable Devices and Self-Report Application

NCT06410755 | Active Not Recruiting

• 1 other identifier: 9-2023-0194
• Study Type: interventional
• Target: 120
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to evaluate whether monitoring and providing feedback on the performance of a home-based exercise program using an integrated wearable monitoring system improves physical and cognitive function, and activity level in participants with stroke. The integrated wearable monitoring system consists of an insole-type gait analyzer for objective gait assessment, a wrist-worn activity tracker for monitoring daily physical activity, and a self-report mobile application for delivering feedback and collecting participant-reported information. This study also aims to assess participant satisfaction with the integrated wearable monitoring system during a 6-week home-based gait rehabilitation program. The main questions this study aims to answer are:

1. 1.What effect does monitoring and providing feedback using an integrated wearable monitoring system have on physical and cognitive function, and activity level during a home-based gait rehabilitation program?
2. 2.How satisfied are participants with the use of the integrated wearable monitoring system?

Conditions

Gait Disorders, Neurologic

Keywords

gait parameters; smart insole; home-based exercise; monitoring system; rehabilitation

Outcome Measures

Primary Outcomes (1)

• 6-minute walking test results

  While wearing the insole gait analyzer, the subject performs a 6-minute gait test, which is the test that most closely approximates everyday walking, and the examiner provides feedback on the gait by comparing the average parameter data extracted from the insole gait analyzer to a normal gait reference. The above evaluation is a test conducted to evaluate walking endurance, and the evaluation method is as follows. 1. Install a colored cone with 30m on the floor and prepare a stopwatch. 2. Instruct the subject to travel as many times as possible in a straight line of 30m for 6 minutes. 3. Teach that they can rest and stop during the test and use only permitted phrases ('You're doing well', 'Keep going'). 4. The examiner records the total distance traveled and the pattern and occurrence time of the abnormal gait.

  This test results will be assessed two times: baseline, exit (after 6 weeks)

Secondary Outcomes (19)

• body composition analysis

  This test results will be assessed two times: baseline, exit (after 6 weeks)

• Spatiotemporal parameters of walking

  This test results will be assessed two times: baseline, exit (after 6 weeks)

• Korea-Mini Mental State Examination

  This test results will be assessed two times: baseline, exit (after 6 weeks)

• Short form of Geriatric Depression Scale (Korean version of Short form of Geriatric Depression Scale)

  This test results will be assessed two times: baseline, exit (after 6 weeks)

• Korean version of Sarcopenia Screening Questionnaire

  This test results will be assessed two times: baseline, exit (after 6 weeks)

Study Arms (2)

Multi-modal Wearable Devices and Self-report Application group receiving monitoring and feedback

EXPERIMENTAL

The intervention group uses an integrated wearable monitoring system consisting of an insole-type gait analyzer, a wrist-worn activity tracker, and a self-report mobile application, and participants are instructed to use the wearable devices as frequently and for as long as possible during daily activities, particularly during outdoor walking. Researchers provide individualized feedback to participants once a week based on data collected from the wearable devices and the mobile application. After 6 weeks, usability and satisfaction with the integrated wearable monitoring system are evaluated.

Device: Integrated Wearable devices Monitoring sys-Assisted Home Rehabilitation Program

Control group

NO INTERVENTION

The control group is trained in the same exercise program as the intervention group, but doesn't use an integrated wearable monitoring system consisting of an insole-type gait analyzer, a wrist-worn activity tracker, and a self-report mobile application.

Interventions

Integrated Wearable devices Monitoring sys-Assisted Home Rehabilitation Program DEVICE

The researcher provides weekly feedback via telephone to participants in the intervention group based on exercise amount, walking level, and activity data collected through the integrated wearable monitoring system, which includes an insole-type gait analyzer, a wrist-worn activity tracker, and a self-report mobile application. Data collection stability is regularly monitored, and any abnormalities or device-related issues are addressed promptly and documented through telephone communication or in-person visits when necessary.

Multi-modal Wearable Devices and Self-report Application group receiving monitoring and feedback

Eligibility Criteria

• Age: 19 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adults over 19 years of age
• Patients with a score of 2-3 on the Modified Rankin Scale who are ambulatory
• Patients who visited Yongin Severance Hospital who understood and agreed to the study and completed the informed consent form

You may not qualify if:

• Those with contraindications to lower extremity weight bearing such as severe lower extremity joint contractures, osteoporosis, or untreated fractures
• Progressive or unstable brain disease
• In addition to above, those who have clinically significant findings that are deemed inappropriate for this study in the medical judgment of the study director or person in charge

Sponsors & Collaborators

• Yonsei University: lead
• Korea Health Industry Development Institute: collaborator

Study Sites (1)

Yongin Severance Hospital

Yongin-si, Gyeonggi-do, 16995, South Korea

Location

Related Publications (54)

• Karvonen J, Vuorimaa T. Heart rate and exercise intensity during sports activities. Practical application. Sports Med. 1988 May;5(5):303-11. doi: 10.2165/00007256-198805050-00002.

  PMID: 3387734 RESULT

• Sindhu BS, Shechtman O, Tuckey L. Validity, reliability, and responsiveness of a digital version of the visual analog scale. J Hand Ther. 2011 Oct-Dec;24(4):356-63; quiz 364. doi: 10.1016/j.jht.2011.06.003. Epub 2011 Aug 6.

  PMID: 21820864 RESULT

• Hagstromer M, Oja P, Sjostrom M. The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr. 2006 Sep;9(6):755-62. doi: 10.1079/phn2005898.

  PMID: 16925881 RESULT

• Wang TL, Wu HY, Wang WY, Chen CW, Chien WC, Chu CM, Wu YS. Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study. JMIR Form Res. 2023 Dec 14;7:e52519. doi: 10.2196/52519.

  PMID: 38096010 RESULT

• Snyder NC, Willoughby CA, Smith BK. Accuracy of Garmin and Polar Smart Watches to Predict VO2max. Medicine & Science in Sports & Exercise 2017;49:761

  RESULT

• Alsiddiky A, Awwad W, Bakarman K, Fouad H, Mahmoud NM. Magnetic resonance imaging evaluation of vertebral tumor prediction using hierarchical hidden Markov random field model on Internet of Medical Things (IOMT) platform. Measurement 2020;159:107772

  RESULT

• Al-Makhadmeh Z, Tolba A. Utilizing IoT wearable medical device for heart disease prediction using higher order Boltzmann model: A classification approach. Measurement 2019;147:106815

  RESULT

• Pinto S, Almeida F, Caldeira S, Martins JC. The Comfort app prototype: introducing a web-based application for monitoring comfort in palliative care. Int J Palliat Nurs. 2017 Sep 2;23(9):420-431. doi: 10.12968/ijpn.2017.23.9.420.

  PMID: 28933997 RESULT

• Larsen K, Akindele B, Head H, Evans R, Mehta P, Hlatky Q, Krause B, Chen S, King D. Developing a User-Centered Digital Clinical Decision Support App for Evidence-Based Medication Recommendations for Type 2 Diabetes Mellitus: Prototype User Testing and Validation Study. JMIR Hum Factors. 2022 Jan 18;9(1):e33470. doi: 10.2196/33470.

  PMID: 34784293 RESULT

• Suso-Ribera C, Castilla D, Zaragoza I, Ribera-Canudas MV, Botella C, Garcia-Palacios A. Validity, Reliability, Feasibility, and Usefulness of Pain Monitor: A Multidimensional Smartphone App for Daily Monitoring of Adults With Heterogenous Chronic Pain. Clin J Pain. 2018 Oct;34(10):900-908. doi: 10.1097/AJP.0000000000000618.

  PMID: 29659375 RESULT

• Yoshida Y, Patil SJ, Brownson RC, Boren SA, Kim M, Dobson R, Waki K, Greenwood DA, Torbjornsen A, Ramachandran A, Masi C, Fonseca VA, Simoes EJ. Using the RE-AIM framework to evaluate internal and external validity of mobile phone-based interventions in diabetes self-management education and support. J Am Med Inform Assoc. 2020 Jun 1;27(6):946-956. doi: 10.1093/jamia/ocaa041.

  PMID: 32377676 RESULT

• Jakob R, Harperink S, Rudolf AM, Fleisch E, Haug S, Mair JL, Salamanca-Sanabria A, Kowatsch T. Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review. J Med Internet Res. 2022 May 25;24(5):e35371. doi: 10.2196/35371.

  PMID: 35612886 RESULT

• Collins DAJ, Harvey SB, Lavender I, Glozier N, Christensen H, Deady M. A Pilot Evaluation of a Smartphone Application for Workplace Depression. Int J Environ Res Public Health. 2020 Sep 16;17(18):6753. doi: 10.3390/ijerph17186753.

  PMID: 32947994 RESULT

• Estrin D, Sim I. Health care delivery. Open mHealth architecture: an engine for health care innovation. Science. 2010 Nov 5;330(6005):759-60. doi: 10.1126/science.1196187. No abstract available.

  PMID: 21051617 RESULT

• Kim AL. Effects of structured arm exercise on arteriovenous fistula stenosis in hemodialysis patient. Journal of Korean Biological Nursing Science 2012;14:300-307

  RESULT

• Schrack JA, Zipunnikov V, Goldsmith J, Bai J, Simonsick EM, Crainiceanu C, Ferrucci L. Assessing the "physical cliff": detailed quantification of age-related differences in daily patterns of physical activity. J Gerontol A Biol Sci Med Sci. 2014 Aug;69(8):973-9. doi: 10.1093/gerona/glt199. Epub 2013 Dec 14.

  PMID: 24336819 RESULT

• Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008 Jan;40(1):181-8. doi: 10.1249/mss.0b013e31815a51b3.

  PMID: 18091006 RESULT

• Shiroma EJ, Freedson PS, Trost SG, Lee IM. Patterns of accelerometer-assessed sedentary behavior in older women. JAMA. 2013 Dec 18;310(23):2562-3. doi: 10.1001/jama.2013.278896. No abstract available.

  PMID: 24346993 RESULT

• Talbot LA, Morrell CH, Fleg JL, Metter EJ. Changes in leisure time physical activity and risk of all-cause mortality in men and women: the Baltimore Longitudinal Study of Aging. Prev Med. 2007 Aug-Sep;45(2-3):169-76. doi: 10.1016/j.ypmed.2007.05.014. Epub 2007 Jun 2.

  PMID: 17631385 RESULT

• Manini TM, Everhart JE, Patel KV, Schoeller DA, Colbert LH, Visser M, Tylavsky F, Bauer DC, Goodpaster BH, Harris TB. Daily activity energy expenditure and mortality among older adults. JAMA. 2006 Jul 12;296(2):171-9. doi: 10.1001/jama.296.2.171.

  PMID: 16835422 RESULT

• Talbot LA, Morrell CH, Metter EJ, Fleg JL. Comparison of cardiorespiratory fitness versus leisure time physical activity as predictors of coronary events in men aged < or = 65 years and > 65 years. Am J Cardiol. 2002 May 15;89(10):1187-92. doi: 10.1016/s0002-9149(02)02302-0.

  PMID: 12008173 RESULT

• Thompson PD, Buchner D, Pina IL, Balady GJ, Williams MA, Marcus BH, Berra K, Blair SN, Costa F, Franklin B, Fletcher GF, Gordon NF, Pate RR, Rodriguez BL, Yancey AK, Wenger NK; American Heart Association Council on Clinical Cardiology Subcommittee on Exercise, Rehabilitation, and Prevention; American Heart Association Council on Nutrition, Physical Activity, and Metabolism Subcommittee on Physical Activity. Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity). Circulation. 2003 Jun 24;107(24):3109-16. doi: 10.1161/01.CIR.0000075572.40158.77. No abstract available.

  PMID: 12821592 RESULT

• Salzman B. Gait and balance disorders in older adults. Am Fam Physician. 2010 Jul 1;82(1):61-8.

  PMID: 20590073 RESULT

• 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.

  PMID: 8531961 RESULT

• Lamoth CJ, Stins JF, Pont M, Kerckhoff F, Beek PJ. Effects of attention on the control of locomotion in individuals with chronic low back pain. J Neuroeng Rehabil. 2008 Apr 25;5:13. doi: 10.1186/1743-0003-5-13.

  PMID: 18439264 RESULT

• 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.

  PMID: 18821647 RESULT

• Fritz S, Lusardi M. White paper: "walking speed: the sixth vital sign". J Geriatr Phys Ther. 2009;32(2):46-9. No abstract available.

  PMID: 20039582 RESULT

• Middleton A, Fritz SL, Lusardi M. Walking speed: the functional vital sign. J Aging Phys Act. 2015 Apr;23(2):314-22. doi: 10.1123/japa.2013-0236. Epub 2014 May 2.

  PMID: 24812254 RESULT

• Muro-de-la-Herran A, Garcia-Zapirain B, Mendez-Zorrilla A. Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications. Sensors (Basel). 2014 Feb 19;14(2):3362-94. doi: 10.3390/s140203362.

  PMID: 24556672 RESULT

• Ngueleu AM, Blanchette AK, Maltais D, Moffet H, McFadyen BJ, Bouyer L, Batcho CS. Validity of Instrumented Insoles for Step Counting, Posture and Activity Recognition: A Systematic Review. Sensors (Basel). 2019 May 28;19(11):2438. doi: 10.3390/s19112438.

  PMID: 31141973 RESULT

• Kirtley C. Clinical gait analysis: theory and practice: Elsevier Health Sciences; 2006

  RESULT

• Guyatt GH, Sullivan MJ, Thompson PJ, Fallen EL, Pugsley SO, Taylor DW, Berman LB. The 6-minute walk: a new measure of exercise capacity in patients with chronic heart failure. Can Med Assoc J. 1985 Apr 15;132(8):919-23.

  PMID: 3978515 RESULT

• 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.

  PMID: 26971404 RESULT

• Kang Y, NA DL, Hahn S. A validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients. Journal of the Korean neurological association 1997:300-308

  RESULT

• Bae JN, Cho MJ. Development of the Korean version of the Geriatric Depression Scale and its short form among elderly psychiatric patients. J Psychosom Res. 2004 Sep;57(3):297-305. doi: 10.1016/j.jpsychores.2004.01.004.

  PMID: 15507257 RESULT

• Kim S, Kim M, Won CW. Validation of the Korean Version of the SARC-F Questionnaire to Assess Sarcopenia: Korean Frailty and Aging Cohort Study. J Am Med Dir Assoc. 2018 Jan;19(1):40-45.e1. doi: 10.1016/j.jamda.2017.07.006. Epub 2017 Aug 31.

  PMID: 28843526 RESULT

• 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.

  PMID: 17908575 RESULT

• Kim Heon-tae, Moon Jun-bae, Ryu Seung-ho, and Kang Min-soo. Validity study of the Korean version of the International Physical Activity Questionnaire (IPAQ): Verification of construct-related validity. Korean Journal of Physical Education No. 2017;56

  RESULT

• Swanson AB, Matev IB, de Groot G. The strength of the hand. Bull Prosthet Res. 1970 Fall;10(14):145-53. No abstract available.

  PMID: 5522244 RESULT

• Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, Mitnitski A. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005 Aug 30;173(5):489-95. doi: 10.1503/cmaj.050051.

  PMID: 16129869 RESULT

• Nowels D, McGloin J, Westfall JM, Holcomb S. Validation of the EQ-5D quality of life instrument in patients after myocardial infarction. Qual Life Res. 2005 Feb;14(1):95-105. doi: 10.1007/s11136-004-0614-4.

  PMID: 15789944 RESULT

• Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, Morley JE, Chumlea W, Salva A, Rubenstein LZ, Garry P. Overview of the MNA--Its history and challenges. J Nutr Health Aging. 2006 Nov-Dec;10(6):456-63; discussion 463-5.

  PMID: 17183418 RESULT

• Won CW, Rho YG, Kim SY, Cho BR, Lee YS. The validity and reliability of Korean Activities of Daily Living (K-ADL) scale. Journal of the Korean Geriatrics Society 2002;6:98-106

  RESULT

• KANG SJ, Choi SH, LEE BH, KWON JC, NA DL, Han SH. The reliability and validity of the Korean Instrumental Activities of Daily Living (K-IADL). Journal of the Korean Neurological Association 2002:8-14

  RESULT

• Gomez JF, Curcio CL, Alvarado B, Zunzunegui MV, Guralnik J. Validity and reliability of the Short Physical Performance Battery (SPPB): a pilot study on mobility in the Colombian Andes. Colomb Med (Cali). 2013 Sep 30;44(3):165-71. eCollection 2013 Jul.

  PMID: 24892614 RESULT

• 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.

  PMID: 3558716 RESULT

• 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.

  PMID: 23023812 RESULT

• Dolny DG, Collins MG, Wilson T, Germann ML, Davis HP. Validity of lower extremity strength and power utilizing a new closed chain dynamometer. Med Sci Sports Exerc. 2001 Jan;33(1):171-5. doi: 10.1097/00005768-200101000-00026.

  PMID: 11194105 RESULT

• Tudor-Locke C, Han H, Aguiar EJ, Barreira TV, Schuna JM Jr, Kang M, Rowe DA. How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: a narrative review. Br J Sports Med. 2018 Jun;52(12):776-788. doi: 10.1136/bjsports-2017-097628.

  PMID: 29858465 RESULT

• Murtagh EM, Mair JL, Aguiar E, Tudor-Locke C, Murphy MH. Outdoor Walking Speeds of Apparently Healthy Adults: A Systematic Review and Meta-analysis. Sports Med. 2021 Jan;51(1):125-141. doi: 10.1007/s40279-020-01351-3.

  PMID: 33030707 RESULT

• Iosa M, Fusco A, Marchetti F, Morone G, Caltagirone C, Paolucci S, Peppe A. The golden ratio of gait harmony: repetitive proportions of repetitive gait phases. Biomed Res Int. 2013;2013:918642. doi: 10.1155/2013/918642. Epub 2013 Jun 4.

  PMID: 23862161 RESULT

• She J, Nakamura H, Makino K, Ohyama Y, Hashimoto H. Selection of suitable maximum-heart-rate formulas for use with Karvonen formula to calculate exercise intensity. International journal of automation and computing 2015;12:62-69

  RESULT

• Speed C, Arneil T, Harle R, Wilson A, Karthikesalingam A, McConnell M, Phillips J. Measure by measure: Resting heart rate across the 24-hour cycle. PLOS Digit Health. 2023 Apr 28;2(4):e0000236. doi: 10.1371/journal.pdig.0000236. eCollection 2023 Apr.

  PMID: 37115739 RESULT

• Lee SH, Jung BK, Park SY. Korean translation and psychometric properties of Quebec user evaluation of satisfaction assistive technology 2.0. Journal of the Korea Academia-Industrial Cooperation Society 2013;14:3284-3292

  RESULT

MeSH Terms

Conditions

Gait Disorders, Neurologic

Condition Hierarchy (Ancestors)

Neurologic Manifestations; Nervous System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Na Young Kim, MD, PhD

  Severance Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Anonymization is achieved by using the unique number of the wearable devices issued to the subject, and data collected through the application will be stored in accordance with the medical device company's security policy and will be discarded after the end of the study, and will be deidentified before being forwarded to the medical device company. De-anonymization is limited to cases where it is necessary in relation to the individual's treatment
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Model Details: This study is a researcher-led, exploratory, randomized controlled clinical study conducted over 6 weeks. Participants are randomly assigned to either an intervention or a control group, which differ in exposure to the wearable device-based intervention. The integrated wearable monitoring system includes an insole-type gait analyzer, a wrist-worn activity tracker, and a self-report mobile application. Participants in the intervention group use the wearable system during daily activities, and weekly individualized feedback is provided via telephone based on collected data. Usability and satisfaction are assessed after the intervention. The control group performs the same home-based exercise program without wearable devices, mobile application access, or feedback.

Study Record Dates

• First Submitted: April 21, 2024
• First Posted: May 13, 2024
• Study Start: March 12, 2024
• Primary Completion: April 23, 2024
• Study Completion (Estimated): December 31, 2026
• Last Updated: April 29, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

KR (1)