CClinicalTrials.gg
Active, not recruitingNCT06410755Updated Jul 27, 2026

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

An interventional study of Integrated Wearable devices Monitoring sys-Assisted Home Rehabilitation Program in Gait Disorders, Neurologic, sponsored by Yonsei University. Active, not recruiting at 1 site in South Korea. Open to participants aged 19 Years and older. Per ClinicalTrials.gov, last updated 2026-07-27.

Sponsored by Yonsei University · Not applicable, Interventional, and Health services research

Phase
Not applicable
Study type
Interventional
Enrollment
120
Allocation
Randomized
Ages
19 Years and older
Sex
All
01

Study 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. 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. How satisfied are participants with the use of the integrated wearable monitoring system?

Researchers will compare an intervention group that receives the integrated wearable monitoring system with a control group that performs the same home-based exercise program without wearable monitoring and feedback.

Participants in the intervention group will receive an insole-type gait analyzer, a wrist-worn activity tracker, and access to a mobile application, along with training in a prescribed home-based exercise program. During the 6-week intervention period, participants will wear the insole-type gait analyzer and the activity tracker while performing the home-based exercise program and will use the mobile application to receive feedback and self-report selected daily health-related information. After completion of the 6-week program, the investigators will conduct a satisfaction survey to evaluate participant experience with the integrated wearable monitoring system.

Read the detailed description

After obtaining written informed consent, a screening assessment is conducted to determine participant eligibility.

The screening assessment evaluates whether participants, regardless of assistive device use, are able to walk independently for more than 10 meters, based on an assessment of baseline symptoms and clinical signs. Eligible participants who pass the screening assessment are randomly assigned to either an intervention group or a control group.

Both groups undergo an initial assessment, during which baseline gait-related outcomes are measured. Participants are provided with information regarding their current gait status and general characteristics of normal gait and are instructed in a standardized home-based exercise program.

Participants assigned to the intervention group are provided with an integrated wearable monitoring system consisting of an insole-type gait analyzer, a wrist-worn activity tracker, and access to a mobile application. The researcher provides training on the proper use of the wearable devices and application and instructs participants to wear the devices as frequently and for as long as possible during daily activities and exercise sessions to enable continuous recording of gait patterns and physical activity. Based on the collected wearable data, the researcher provides individualized feedback to participants in the intervention group via telephone on a weekly basis.

Participants in the control group perform the same home-based exercise program but do not receive wearable monitoring devices or feedback related to their exercise performance.

At the completion of the 6-week home-based exercise program, an exit assessment identical to the initial assessment is conducted for both groups. In addition, participants in the intervention group complete a satisfaction survey to evaluate their experience with the integrated wearable monitoring system.

Throughout the intervention period, device-related issues, including malfunctions and usage interruptions, are documented. Usage patterns and satisfaction levels associated with the wearable monitoring system in the intervention group are analyzed, and pre- and post-intervention outcome measures are compared between the intervention and control groups.

02

Conditions studied

  • Gait Disorders, Neurologic

Keywords

  • gait parameters
  • smart insole
  • home-based exercise
  • monitoring system
  • rehabilitation
03

In context

Gait Disorders, Neurologic

327 studies on the registry are indexed under Gait Disorders, Neurologic; 54 are open to participants now.

This study's enrollment of 120 is above the median of 30 across 246 interventional studies indexed under Gait Disorders, Neurologic.

Browse Gait Disorders, Neurologic studies →

Lead sponsor

Yonsei University is the lead sponsor of 1,387 studies on the registry; 232 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
19 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

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

Exclusion criteria

Exclusion Criteria:

  1. Those with contraindications to lower extremity weight bearing such as severe lower extremity joint contractures, osteoporosis, or untreated fractures
  2. Progressive or unstable brain disease
  3. 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
05

Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Participant)
Enrollment
120 participants (actual)

Study arms

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

    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

  • No intervention
    Control group

    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

  • DeviceIntegrated Wearable devices Monitoring sys-Assisted Home Rehabilitation Program

    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.

06

What researchers measure

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.

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

Secondary outcomes

  1. body composition analysis

    This is a test performed to check the subject's limb muscle mass, and the test method is as follows. 1. Perform body composition analysis based on bioimpedance analysis. 2. To ensure accurate measurement, the test subject is instructed to empty his/her bladder before the test and not to consume caffeinated beverages, eat, drink, or perform strenuous exercise for one hour prior to the test. 3. To correct for muscle mass differences due to height, use the calculated value of limb muscle mass (Appendicular skeletal mass) divided by the square of the height.

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

  2. Spatiotemporal parameters of walking

    Spatiotemporal parametric data of gait collected while the subject is performing a home-based activity wearing an insole gait analyzer, recording total steps, steps per minute(steps/min), gait speed(km/h), distance walked(m), stride length(m), and swing phase rate(%).

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

  3. Korea-Mini Mental State Examination

    A test that assesses the degree of overall cognitive impairment, taking into account a person's level of education, and the test assesses time and place perception, attention and calculation, memory, language, and spatial and temporal organization. The examiner asks questions corresponding to the items on the test sheet below and record a score for the answers.

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

  4. Short form of Geriatric Depression Scale (Korean version of Short form of Geriatric Depression Scale)

    This is a test used to assess the level of depression in older adults and able to assess quickly the level of depression in the elderly and identify risk. The examiner asks the subject questions according to the questionnaire below, checks items according to the answers, and scores them according to the evaluation method. This consists of 15 items and is the most commonly used version due to its brevity and ease of use. It can typically be completed in 5 to 7 minutes. Each item on the GDS is scored 0 or 1, depending on whether the symptom of depression is absent or present according to the patient's response. The total score is calculated by summing up the scores for each item. Generally, a score of 0 to 5 is considered normal, depending on the setting and clinical judgment. Scores of 5 or more suggest depression, with scores of 10 or higher almost always indicative of depression.

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

  5. Korean version of Sarcopenia Screening Questionnaire

    Questionnaire that evaluates the decrease in muscle strength and functional performance along with a decrease in muscle mass and it is highly related to aging and chronic diseases. The evaluation method is conducted by having the examiner ask the subject about the following questionnaire, and the scores for the answers are recorded. It consists of 5 questions, and each question is scored 0-2 points. The higher the score, the higher the risk of sarcopenia. If the score is 4 or higher, sarcopenia may be suspected.

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

  6. Functional Ambulation Category

    Assessment of the subject's walking function. The examiner observes the subject's gait and records a score based on the criteria in the assessment sheet below.

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

  7. Korean version of the International Physical Activity Questionnaire (K-IPAQ)

    Tests that assess various aspects of an individual's daily physical activity and it can provide information about activity level. The examiner questions the subject based on the questionnaire below, records related information, calculates the total activity time and intensity, and classifies it as 'low', 'medium', and 'high'.

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

  8. Grip Strength Test

    A test that evaluates the subject's grip strength, and the evaluation method is as follows. 1. The subject sits in the correct posture and bends the elbows to 90 degrees. 2. Place the handle of the measuring device between the first and second joints of each finger and hold it tightly according to the examiner's instructions. 3. Measure the left and right three times each and record the maximum value.

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

  9. Clinical Frailty Scale

    Test to assess the health status and frailty of elderly and assesses the health and vulnerability of the elderly after the program ends. The scale ranges from 1 to 9, with each level described through specific criteria that reflect the degree of fitness or frailty, a higher score means poorer health.

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

  10. European Quality of Life-5 Dimensions

    It consists of items evaluating exercise ability, self-management, daily activities (work, study, housework, family or leisure activities), pain/discomfort, and anxiety/depression, and examiner evaluates according to the form below. Participants will be asked to answer each question with 3 items, and a higher score means more health problems, minimum score is 5 and maximum score is 15.

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

  11. Mini-Nutritional Assessment

    An assessment of nutritional status and risk of undernutrition or malnutrition using questionnaire to assess the nutritional status of a subject, and the examiner records a score based on the criteria in the questionnaire below.

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

  12. Assessment of activities of daily living and instrumental activities of daily living (ADL & I-ADL assessment)

    This assessment uses a questionnaire that assesses the nutritional status of subjects to determine their nutritional status and whether they are undernourished or at risk of being undernourished, and the examiner records a score based on the criteria in the questionnaire below.

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

  13. Short Physical Performance Battery (SPPB)

    This is a test that evaluates three areas to assess a subject's lower extremity physical functioning, and it measures and records scores in three areas: balance, getting up from a chair, and walking speed. 1. Balance test: Line up feet in parallel and hold for 10 seconds. If possible, perform this test in a semi-upright position, then straighten feet and repeat 3 times. 2. Chair stand-up test: Perform the stand-up test 5 times from a chair. The examiner measures the time and records the score according to the criteria below. 3. Walking speed test: After having the subject walk 3m, the examiner measures the time and scores according to the criteria below.

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

  14. Timed up and go test (TUG)

    The above test assesses walking speed along with balance ability during walking, and this is performed as follows. 1. A 46 cm high armrest chair, a color cone is placed at a distance of 3 meters from the chair and the subject is instructed to sit on the chair. 2. In the preparation phase, the subject leans against the chair backrest and places his/her arms on the armrests, then stands up on the instruction "Start", walks 3 meters, turns around the color cone, returns to the starting point and sits down on the chair.

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

  15. Berg Balance Scale

    The above test assesses static and dynamic balance, in which the examiner instructs the subject to perform the 14 movements below and then scores them against a set of criteria.

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

  16. Cybex isokinetic strength evaluation

    A test to measure lower extremity strength and power using the isokinetic exercise equipment CYBEX, and 5 repetitions of 60/60 degrees per second and 15 repetitions of 150/150 degrees per second are performed to measure Peak Torque (Nm), Total Work (J), Average power per repetition (W), and Fatigue Index (%) of the lower extremity muscles.

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

  17. Application survey response rate

    Subjects complete the following five questionnaires before bed, based on the application usage method they were trained on by the examiner. Based on the subject's questionnaire records, the subject's weekly response rate is calculated as n out of 5 responses and n out of 7 days. The subject conducts the following five surveys before going to bed based on how to use the application trained by the inspector. Based on the subject's questionnaire record, the subject's weekly response rate is calculated with n responses out of 5 and n responses out of 7 days. The five surveys consist of Mood, Appetite, Sleep Quality and Duration, Activity Level, and Pain.

    Time frame: This test results will be assessed up to 6 weeks

  18. K-QEUST-based wearable device satisfaction assessment

    The subjects of the experimental group return the smart band to the inspector, and fill out a 12-item, 5-point smart band based on the Korean version of the assistance instrument satisfaction test (K-QUEST 2.0), and a satisfaction evaluation questionnaire for the application linked thereto. This questionnaire consists of 12 items to evaluate the satisfaction, and the satisfaction with the assistance instrument and the service used in this regard is expressed in 1-5 points below. If the rest of the items except for very satisfaction are filled out, instruct the subject to fill out the reason. The target group does not do the above. 1: Very unsatisfied. 2: Not satisfied 3: Usually 4: Very satisfied. 5: Very satisfied

    Time frame: This test result will be assessed once at the end of the 6-week intervention.

  19. 10m Walk Test

    The 10-Meter Walk Test16 is used to assess gait speed in patients undergoing rehabilitation for neurological and Severance: H10\_250409 musculoskeletal disorders. Participants wear an insole-type gait analyzer and walk a 10-meter straight path at a consistent pace while the time taken is measured to evaluate gait ability. 1. A total straight path of 14 meters is prepared, with the first and last 2 meters serving as non-measurement zones. 2. b) Participants are informed that their walking speed will be measured over the 10-meter section and are instructed to walk at a comfortable pace.

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

07

Study locations

1 site
  • Yongin Severance Hospital
    Yongin-si, Gyeonggi-do 16995, South Korea
08

References and documents

Publications

  • 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. PubMed 3387734 ↗
  • 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. PubMed 21820864 ↗
  • 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. PubMed 16925881 ↗
  • 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. PubMed 38096010 ↗
  • Snyder NC, Willoughby CA, Smith BK. Accuracy of Garmin and Polar Smart Watches to Predict VO2max. Medicine & Science in Sports & Exercise 2017;49:761
  • 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
  • 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
  • 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. PubMed 28933997 ↗
  • 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. PubMed 34784293 ↗
  • 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. PubMed 29659375 ↗
  • 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. PubMed 32377676 ↗
  • 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. PubMed 35612886 ↗
  • 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. PubMed 32947994 ↗
  • 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. PubMed 21051617 ↗
  • Kim AL. Effects of structured arm exercise on arteriovenous fistula stenosis in hemodialysis patient. Journal of Korean Biological Nursing Science 2012;14:300-307
  • 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. PubMed 24336819 ↗
  • 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. PubMed 18091006 ↗
  • 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. PubMed 24346993 ↗
  • 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. PubMed 17631385 ↗
  • 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. PubMed 16835422 ↗
  • 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. PubMed 12008173 ↗
  • 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. PubMed 12821592 ↗
  • Salzman B. Gait and balance disorders in older adults. Am Fam Physician. 2010 Jul 1;82(1):61-8. PubMed 20590073 ↗
  • 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. PubMed 8531961 ↗
  • 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. PubMed 18439264 ↗
  • 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. PubMed 18821647 ↗
  • Fritz S, Lusardi M. White paper: "walking speed: the sixth vital sign". J Geriatr Phys Ther. 2009;32(2):46-9. No abstract available. PubMed 20039582 ↗
  • 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. PubMed 24812254 ↗
  • 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. PubMed 24556672 ↗
  • 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. PubMed 31141973 ↗
  • Kirtley C. Clinical gait analysis: theory and practice: Elsevier Health Sciences; 2006
  • 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. PubMed 3978515 ↗
  • 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. PubMed 26971404 ↗
  • 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
  • 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. PubMed 15507257 ↗
  • 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. PubMed 28843526 ↗
  • 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. PubMed 17908575 ↗
  • 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
  • Swanson AB, Matev IB, de Groot G. The strength of the hand. Bull Prosthet Res. 1970 Fall;10(14):145-53. No abstract available. PubMed 5522244 ↗
  • 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. PubMed 16129869 ↗
  • 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. PubMed 15789944 ↗
  • 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. PubMed 17183418 ↗
  • 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
  • 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
  • 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. PubMed 24892614 ↗
  • 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. PubMed 3558716 ↗
  • 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. PubMed 23023812 ↗
  • 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. PubMed 11194105 ↗
  • 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. PubMed 29858465 ↗
  • 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. PubMed 33030707 ↗
  • 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. PubMed 23862161 ↗
  • 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
  • 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. PubMed 37115739 ↗
  • 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

Study documents

  • Protocol and statistical analysis plan · Apr 22, 2026

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jul 27, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT06410755
Lead sponsor
Yonsei University
Collaborators
Korea Health Industry Development Institute
Responsible party
Na Young Kim (Professor, Severance Hospital) — Principal investigator
First posted
May 13, 2024
Start date
May 14, 2024
Primary completion
Dec 31, 2025
Completion
Dec 31, 2026 (estimated)
Last update
Jul 27, 2026

Study contacts

Na Young Kim, MD, PhD
principal investigator · Severance Hospital

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is active, not recruiting, as verified in Jul 2026. You cannot join it, but the record below documents what was studied.

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