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CompletedNCT07915583Updated Nov 4, 2026

The Effects of Fine Motor Training With Augmented Reality on the Memory of Older Adults With Amnestic Mild Cognitive Impairment

An interventional study of mPETS(modified-PETS system) in Healthy Elderly and Mild Cognitive Impairment (MCI), sponsored by National Cheng-Kung University Hospital. Completed at 1 site in Taiwan. Open to participants aged 20 Years to 85 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-11-04.

Sponsored by National Cheng-Kung University Hospital · Not applicable, Interventional, and Other

From the registry’s dates

  • Registered 7 years 10 months after the study started (first participant enrolled Dec 2018, registered Oct 2026).
Updated Nov 4, 2026Newly registeredGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
28
Allocation
Randomized
Ages
20 Years to 85 Years
Sex
All
01

Study summary

Previous studies indicated that sensory input can have positive impacts on finger force control in the elderly. Additionally, according to previous reports, apart from pharmacotherapy, nonpharmacologic interventions, such as psychosocial-environmental treatments, are emerging for the behavior and affective symptoms in cognitive impairment . Moreover, enhanced finger force control and coordination lead to better hand dexterity and is believed to eventually improve life independence in the healthy elderly and the elderly with cognitive impairment. Therefore, this study aims to investigate the effects of fine motor training integrated with AR on older adults with cognitive impairment.

02

Conditions studied

  • Healthy Elderly
  • Mild Cognitive Impairment (MCI)

Keywords

  • Augmented Reality
  • Virtual Reality
03

In context

Cognitive Dysfunction

3,941 studies on the registry are indexed under Cognitive Dysfunction; 1,117 are open to participants now.

This study's enrollment of 28 is below the median of 64 across 2,859 interventional studies indexed under Cognitive Dysfunction.

Browse Cognitive Dysfunction studies →

Lead sponsor

National Cheng-Kung University Hospital is the lead sponsor of 277 studies on the registry; 71 are open to participants now.

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

04

Who can participate

Ages eligible
20 Years to 85 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Eligibility criteria

Healthy elderly

Inclusion Criteria:

  • Aged ≥ 65
  • Healthy adult (no skeletal muscle, neurological disease that will affect training).

Exclusion Criteria:

  • Neurological disorders
  • Musculoskeletal problems
  • History of surgery Patients with mild cognitive impairment

Inclusion Criteria:

  • Aged ≥ 65
  • Diagnosed with mild cognitive impairment by physicians
  • No skeletal muscle, neurological disease that will affect training.
05

Study design

Phase
Not applicable
Primary purpose
Other
Allocation
Randomized
Intervention model
Crossover assignment
Masking
None (open label)
Enrollment
28 participants (actual)

Study arms

  • Experimental
    AR-mPETS

    Subjects will be instructed to execute simulated piano playing tasks with Augmented Reality.

    Device: mPETS(modified-PETS system)

  • No intervention
    Usual Rehabilitation Group

    Participants receive usual rehabilitation care according to standard clinical practice.

  • No intervention
    Healthy Older Adults Group

    Participants do not receive the study intervention.

Interventions

  • DevicemPETS(modified-PETS system)

    The pressing evaluation and training system (PETS) consists of five force transducers, a pad position-adjustable frame, and biofeedback system. Five force transducers are used to collect the applied normal force from five digits.

06

What researchers measure

Primary outcomes

  1. Force-track testing

    Participants will be asked to track the target force and presses task digit to fit the target line until finish.

    Time frame: Before and after intervention (8weeks)

Secondary outcomes

  1. Sequential testing( reaction time)

    In sequential testing, participants will be asked to follow the pressing guide. The reaction time of sequential movements will be recorded and calculated.

    Time frame: Before and after intervention (8 weeks)

  2. Sequential testing( correct ratio )

    In sequential testing, participants will be asked to follow the pressing guide. The correct ratio of sequential movements will be recorded and calculated.

    Time frame: Before and after intervention (8 weeks)

07

Study locations

1 site
  • Nation Cheng Kung University
    Tainan, 701, Taiwan
08

References and documents

Publications

  • Levanon Y. The advantages and disadvantages of using high technology in hand rehabilitation. J Hand Ther. 2013 Apr-Jun;26(2):179-83. doi: 10.1016/j.jht.2013.02.002. PubMed 23598084 ↗
  • Friedman N, Chan V, Reinkensmeyer AN, Beroukhim A, Zambrano GJ, Bachman M, Reinkensmeyer DJ. Retraining and assessing hand movement after stroke using the MusicGlove: comparison with conventional hand therapy and isometric grip training. J Neuroeng Rehabil. 2014 Apr 30;11:76. doi: 10.1186/1743-0003-11-76. PubMed 24885076 ↗
  • Wu YH, Truglio TS, Zatsiorsky VM, Latash ML. Learning to combine high variability with high precision: lack of transfer to a different task. J Mot Behav. 2015;47(2):153-65. doi: 10.1080/00222895.2014.961892. Epub 2014 Nov 3. PubMed 25365477 ↗
  • Stein J, Bishop J, Gillen G, Helbok R. A pilot study of robotic-assisted exercise for hand weakness after stroke. IEEE Int Conf Rehabil Robot. 2011;2011:5975426. doi: 10.1109/ICORR.2011.5975426. PubMed 22275627 ↗
  • Jo HJ, Ambike S, Lewis MM, Huang X, Latash ML. Finger force changes in the absence of visual feedback in patients with Parkinson's disease. Clin Neurophysiol. 2016 Jan;127(1):684-692. doi: 10.1016/j.clinph.2015.05.023. Epub 2015 Jun 3. PubMed 26072437 ↗
  • Loucks TM, Ofori E, Sosnoff JJ. Force control under auditory feedback: effector differences and audiomotor memory. Percept Mot Skills. 2012 Jun;114(3):915-35. doi: 10.2466/24.25.27.PMS.114.3.915-935. PubMed 22913030 ↗
  • Hu X, Loncharich M, Newell KM. Visual information interacts with neuromuscular factors in the coordination of bimanual isometric force. Exp Brain Res. 2011 Mar;209(1):129-38. doi: 10.1007/s00221-010-2528-4. Epub 2010 Dec 28. PubMed 21188355 ↗
  • Seo NJ, Fischer HW, Bogey RA, Rymer WZ, Kamper DG. Use of visual force feedback to improve digit force direction during pinch grip in persons with stroke: a pilot study. Arch Phys Med Rehabil. 2011 Jan;92(1):24-30. doi: 10.1016/j.apmr.2010.08.016. Epub 2010 Nov 18. PubMed 21092931 ↗
  • Hu X, Newell KM. Aging, visual information, and adaptation to task asymmetry in bimanual force coordination. J Appl Physiol (1985). 2011 Dec;111(6):1671-80. doi: 10.1152/japplphysiol.00760.2011. Epub 2011 Sep 29. PubMed 21960656 ↗
  • Ambike S, Zatsiorsky VM, Latash ML. Processes underlying unintentional finger-force changes in the absence of visual feedback. Exp Brain Res. 2015 Mar;233(3):711-21. doi: 10.1007/s00221-014-4148-x. Epub 2014 Nov 23. PubMed 25417192 ↗
  • Li K, Marquardt TL, Li ZM. Removal of visual feedback lowers structural variability of inter-digit force coordination during sustained precision pinch. Neurosci Lett. 2013 Jun 17;545:1-5. doi: 10.1016/j.neulet.2013.04.011. Epub 2013 Apr 24. PubMed 23624025 ↗
  • Kim Y, Shim JK, Hong YK, Lee SH, Yoon BC. Cutaneous sensory feedback plays a critical role in agonist-antagonist co-activation. Exp Brain Res. 2013 Aug;229(2):149-56. doi: 10.1007/s00221-013-3601-6. Epub 2013 Jul 9. PubMed 23836110 ↗
  • Shim JK, Karol S, Kim YS, Seo NJ, Kim YH, Kim Y, Yoon BC. Tactile feedback plays a critical role in maximum finger force production. J Biomech. 2012 Feb 2;45(3):415-20. doi: 10.1016/j.jbiomech.2011.12.001. Epub 2012 Jan 4. PubMed 22222494 ↗
  • Langlois F, Vu TT, Chasse K, Dupuis G, Kergoat MJ, Bherer L. Benefits of physical exercise training on cognition and quality of life in frail older adults. J Gerontol B Psychol Sci Soc Sci. 2013 May;68(3):400-4. doi: 10.1093/geronb/gbs069. Epub 2012 Aug 28. PubMed 22929394 ↗
  • Wu YH, Pazin N, Zatsiorsky VM, Latash ML. Improving finger coordination in young and elderly persons. Exp Brain Res. 2013 Apr;226(2):273-83. doi: 10.1007/s00221-013-3433-4. Epub 2013 Feb 15. PubMed 23411675 ↗
  • Verheij S, Muilwijk D, Pel JJ, van der Cammen TJ, Mattace-Raso FU, van der Steen J. Visuomotor impairment in early-stage Alzheimer's disease: changes in relative timing of eye and hand movements. J Alzheimers Dis. 2012;30(1):131-43. doi: 10.3233/JAD-2012-111883. PubMed 22377783 ↗
  • Franssen EH, Souren LE, Torossian CL, Reisberg B. Equilibrium and limb coordination in mild cognitive impairment and mild Alzheimer's disease. J Am Geriatr Soc. 1999 Apr;47(4):463-9. doi: 10.1111/j.1532-5415.1999.tb07240.x. PubMed 10203123 ↗
  • Olafsdottir H, Zhang W, Zatsiorsky VM, Latash ML. Age-related changes in multifinger synergies in accurate moment of force production tasks. J Appl Physiol (1985). 2007 Apr;102(4):1490-501. doi: 10.1152/japplphysiol.00966.2006. Epub 2007 Jan 4. PubMed 17204576 ↗
  • Shinohara M, Li S, Kang N, Zatsiorsky VM, Latash ML. Effects of age and gender on finger coordination in MVC and submaximal force-matching tasks. J Appl Physiol (1985). 2003 Jan;94(1):259-70. doi: 10.1152/japplphysiol.00643.2002. Epub 2002 Sep 13. PubMed 12391031 ↗
  • Shinohara M, Scholz JP, Zatsiorsky VM, Latash ML. Finger interaction during accurate multi-finger force production tasks in young and elderly persons. Exp Brain Res. 2004 Jun;156(3):282-92. doi: 10.1007/s00221-003-1786-9. Epub 2004 Feb 19. PubMed 14985892 ↗
  • Parikh PJ, Cole KJ. Handling objects in old age: forces and moments acting on the object. J Appl Physiol (1985). 2012 Apr;112(7):1095-104. doi: 10.1152/japplphysiol.01385.2011. Epub 2012 Jan 12. PubMed 22241054 ↗
  • Shim JK, Lay BS, Zatsiorsky VM, Latash ML. Age-related changes in finger coordination in static prehension tasks. J Appl Physiol (1985). 2004 Jul;97(1):213-24. doi: 10.1152/japplphysiol.00045.2004. Epub 2004 Mar 5. PubMed 15003998 ↗
  • Kim SW, Shim JK, Zatsiorsky VM, Latash ML. Finger inter-dependence: linking the kinetic and kinematic variables. Hum Mov Sci. 2008 Jun;27(3):408-22. doi: 10.1016/j.humov.2007.08.005. Epub 2008 Feb 5. PubMed 18255182 ↗
  • Zhang W, Scholz JP, Zatsiorsky VM, Latash ML. What do synergies do? Effects of secondary constraints on multidigit synergies in accurate force-production tasks. J Neurophysiol. 2008 Feb;99(2):500-13. doi: 10.1152/jn.01029.2007. Epub 2007 Nov 28. PubMed 18046000 ↗
  • Kwok TC, Lam KC, Wong PS, Chau WW, Yuen KS, Ting KT, Chung EW, Li JC, Ho FK. Effectiveness of coordination exercise in improving cognitive function in older adults: a prospective study. Clin Interv Aging. 2011;6:261-7. doi: 10.2147/CIA.S19883. Epub 2011 Sep 29. PubMed 22087065 ↗
  • Keogh JW, Morrison S, Barrett R. Strength training improves the tri-digit finger-pinch force control of older adults. Arch Phys Med Rehabil. 2007 Aug;88(8):1055-63. doi: 10.1016/j.apmr.2007.05.014. PubMed 17678670 ↗
  • Olafsdottir HB, Zatsiorsky VM, Latash ML. The effects of strength training on finger strength and hand dexterity in healthy elderly individuals. J Appl Physiol (1985). 2008 Oct;105(4):1166-78. doi: 10.1152/japplphysiol.00054.2008. Epub 2008 Aug 7. PubMed 18687981 ↗
  • Ranganathan VK, Siemionow V, Sahgal V, Liu JZ, Yue GH. Skilled finger movement exercise improves hand function. J Gerontol A Biol Sci Med Sci. 2001 Aug;56(8):M518-22. doi: 10.1093/gerona/56.8.m518. PubMed 11487606 ↗
  • Grabiner MD, Enoka RM. Changes in movement capabilities with aging. Exerc Sport Sci Rev. 1995;23:65-104. No abstract available. PubMed 7556361 ↗

Individual participant data

Plan to share: Undecided

09

Timeline

1 registry update since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Ran from Dec 2018 to primary completion in Jan 2019, 0 months.

Of 1,443 non-industry interventional studies with no phase under Cognitive Dysfunction, half reached primary completion within 27 months of starting (the median), counting those still running; a quarter within 13 and three quarters within 51. This study's 0 months is below that.

Counting every sponsor, half of 1,517 studies reached it within 26 months; a quarter within 12 and three quarters within 49.

How these figures are worked out, and which studies are left out of them.

Registered
Oct 29, 2026
First posted
Nov 4, 2026
StartActual
Dec 24, 2018
Primary completionActual
Jan 22, 2019
CompletionActual
Jan 22, 2019
Last update
Nov 4, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
Registered
First appeared on the registry. No changes since
Nov 4, 2026
Show all 1 update
  1. Nov 4, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07915583
Responsible party
Fong Chin Su (Chair Professor, National Cheng Kung University) — Principal investigator
First posted
Nov 4, 2026
Start date
Dec 24, 2018
Primary completion
Jan 22, 2019
Completion
Jan 22, 2019
Last update
Nov 4, 2026

Oversight

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

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