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Healthy AdultNCT07394231

Exploring Innovative Strategies to Enhance Eye-Hand Coordination and Cognitive Functions Through Drone Catching Exercise.

A study testing Real Object-Based Catching System and Virtual Object-Based Catching System in people with Healthy Adult, run by National Cheng-Kung University Hospital at 1 site in Taiwan.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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Trial summary

Eye-hand coordination (EHC) is a critical cognitive-motor function that enables individuals to interact effectively with their environment through visually guided hand movements. It plays an essential role in daily activities such as reaching, grasping, and object manipulation. Read more about this study

Who is it for?
Ages 60 years and olderHealthy volunteers can take part
Conditions the study is for
Healthy Adult
What is being tested?
Real Object-Based Catching System and Virtual Object-Based Catching System
Could I receive a placebo?
No, everyone receives an active treatment
How many people
38 participants
Where
1 siteTaiwan
Study dates
19 Oct 2024to 23 Dec 2024
Phase
Interventional
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 60 years and older
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Who may be able to join

  • 60 years and older (65 years and older preferred).
  • Able to perform regular exercise.
  • Normal vision or normal vision after correction.

Who cannot join

  • Have a history of significant chronic diseases such as neurological (e.g., stroke, dementia, Parkinson's disease, poor vision, and hearing loss), cardiovascular, metabolic, pulmonary, or musculoskeletal diseases.
  • Have a history of significant motion sickness, active nausea, and vomiting, or epilepsy.
  • Fear of wearing a VR headset.

Trial locations and contacts

1 site in 1 country.

Taiwan1 site

  • Motion Analysis Laboratory, Dept. of Biomedical Engineeing, National Cheng Kung University

    Tainan, 701

Other trials in Taiwan

About this study

Eye-hand coordination (EHC) is a critical cognitive-motor function that enables individuals to interact effectively with their environment through visually guided hand movements. It plays an essential role in daily activities such as reaching, grasping, and object manipulation. Previous studies have shown that targeted physical activities and sports can enhance EHC performance. However, aging is commonly associated with declines in EHC, executive function, and postural control, which can negatively affect independence in daily living. These age-related changes are also closely linked to cognitive decline and may contribute to the development of mild cognitive impairment (MCI), dementia, and Alzheimer's disease, thereby increasing the burden on families and healthcare systems.

To mitigate these effects, various cognitive-motor and technology-assisted training approaches have been proposed to improve EHC and cognitive function in older adults. While many existing EHC training systems are computerized and implemented using virtual reality (VR) or mixed reality (MR), accumulating evidence suggests that virtual environments may not fully replicate real-world eye-hand interactions. Limitations in depth perception, haptic feedback, and realism may alter visual fixation strategies, movement execution, and overall task performance, potentially reducing training effectiveness compared with real-world interactions.

Given these limitations, it remains unclear whether real-world EHC training provides greater benefits to executive functions and motor performance than virtual training. Therefore, this study aims to compare the acute effects of EHC exercise performed in a real-world environment and a mixed reality passthrough environment among older adults. The proposed EHC training task involves catching a real three-dimensional (3D) object guided by a physical mini drone, inspired by natural human behaviors such as swatting at flying insects, and its virtual counterpart involving a virtual 3D object and drone. The primary objective is to examine differences in executive functions, task performance, and postural stability between real and virtual EHC conditions. By identifying which training modality better supports cognitive-motor performance, this study seeks to inform the design of effective and engaging interventions for healthy aging and early prevention of cognitive decline.

Conditions
Healthy Adult
Being tested
Real Object-Based Catching System, Virtual Object-Based Catching System
Keywords
Eye-Hand Coordination (EHC), Physical and Virtual Objects, Mixed Reality (MR), Executive Functions, Behavioral Responses, Postural Stabilities, Gerontechnology

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Real Object-Based Catching SystemOther

    This condition involves a participant grasping a physical 3D object located beneath the drone in a real-world environment.

  • Virtual Object-Based Catching SystemOther

    The condition involves a participant grasping a virtual counterpart of a physical 3D object within a mixed reality (MR) passthrough environment.

Study groups in NCT07394231
Study groupRoleWhat they receive
Underwent the virtual system after the real systemExperimentalNot described
Receives: Other: Real Object-Based Catching System; Other: Virtual Object-Based Catching System
Underwent the real system after the virtual systemExperimentalNot described
Receives: Other: Real Object-Based Catching System; Other: Virtual Object-Based Catching System

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Executive Functions via Flanker-ERP Measurement

    Each participant underwent Flanker-ERP assessment at three stages: at baseline (pre-intervention) and following both the physical and virtual object-based EHC training sessions.

    Measured: 2 hours

  2. Success Rate (SR)

    SR was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.

    Measured: 1-1.5 hours

  3. Reaction Time (RT)

    RT was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.

    Measured: 1-1.5 hours

  4. Movement Time (MT)

    MT was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.

    Measured: 1-1.5 hours

  5. Peak Hand Velocity (PHV)

    PHV was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.

    Measured: 1-1.5 hours

  6. Time-to-Peak Hand Velocity (TPHV)

    TPHV was measured for each participant during object-catching trials across two EHC training modalities: the physical and the virtual 3D object-based drone-catching systems.

    Measured: 1-1.5 hours

  7. Center of Mass (CoM)

    The CoM of every participant while performing EHC training tasks was investigated regarding two different EHC training modalities, including physical object-based and virtual object-based drone-catching systems.

    Measured: 1-1.5 hours

  8. Center of Pressure (CoP)

    The CoP of every participant while performing EHC training tasks was investigated regarding two different EHC training modalities, including physical object-based and virtual object-based drone-catching systems.

    Measured: 1-1.5 hours

Secondary outcomes (3)

  1. Subjective participant feedback on perceived task difficulty

    Subjective participant feedback on perceived task difficulty regarding the physical and virtual object-based EHC training systems was collected using a 5-point Likert scale (1=very easy, 2=easy, 3=neutral, 4=difficult, and 5=very difficult).

    Measured: 10-15 minutes

  2. Subjective participant feedback on system preference

    Subjective participant feedback regarding preference between the physical and virtual object-based EHC training systems was collected.

    Measured: 10-15 minutes

  3. Virtual Reality Sickness Questionnaire (VRSQ)

    Adverse effects of the mixed reality environment were evaluated at the end of the experiment using the Virtual Reality Sickness Questionnaire (VRSQ). The VRSQ assesses the severity of nine distinct symptoms on a 4-point scale (none, slight, moderate, and severe). These symptoms include general discomfort, fatigue, headache, eye strain, difficulty focusing, fullness of the head, blurred vision, dizziness with eyes closed, and vertigo.

    Measured: 10-15 minutes

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted6 Feb 2026
  2. Study start19 Oct 2024
  3. Primary completion23 Dec 2024
  4. Study completion23 Dec 2024

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Other
Allocation
Randomised
Intervention model
Single group
Masking
None (open label)
Enrolment
38 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07394231
Sponsor's protocol ID
113-420
Status last verified
Feb 2026
First submitted
22 Jan 2026
Last updated
6 Feb 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Undecided: The study is currently under manuscript preparation.

Publications

  • R. B. Davis, S. Õunpuu, D. Tyburski, and J. R. Gage, "A gait analysis data collection and reduction technique," Hum Mov Sci, vol. 10, no. 5, pp. 575-587, 1991, doi: https://doi.org/10.1016/0167-9457(91)90046-Z.

  • Lopez-Calderon J, Luck SJ. ERPLAB: an open-source toolbox for the analysis of event-related potentials. Front Hum Neurosci. 2014 Apr 14;8:213. doi: 10.3389/fnhum.2014.00213. eCollection 2014.

    PubMed 24782741

  • Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004 Mar 15;134(1):9-21. doi: 10.1016/j.jneumeth.2003.10.009.

    PubMed 15102499

  • Birckhead B, Khalil C, Liu X, Conovitz S, Rizzo A, Danovitch I, Bullock K, Spiegel B. Recommendations for Methodology of Virtual Reality Clinical Trials in Health Care by an International Working Group: Iterative Study. JMIR Ment Health. 2019 Jan 31;6(1):e11973. doi: 10.2196/11973.

    PubMed 30702436

  • M. Aly and H. Kojima, "Acute moderate-intensity exercise generally enhances neural resources related to perceptual and cognitive processes: A randomized controlled ERP study," Ment Health Phys Act, vol. 19, p. 100363, 2020, doi: https://doi.org/10.1016/j.mhpa.2020.100363.

  • Pei YC, Chou SW, Lin PS, Lin YC, Hsu TH, Wong AM. Eye-hand coordination of elderly people who practice Tai Chi Chuan. J Formos Med Assoc. 2008 Feb;107(2):103-10. doi: 10.1016/S0929-6646(08)60123-0.

    PubMed 18285242

  • B. A. Eriksen and C. W. Eriksen, "Effects of noise letters upon the identification of a target letter in a nonsearch task," Percept Psychophys, vol. 16, no. 1, pp. 143-149, 1974, doi: 10.3758/BF03203267.

  • Lavoie E, Hebert JS, Chapman CS. Comparing eye-hand coordination between controller-mediated virtual reality, and a real-world object interaction task. J Vis. 2024 Feb 1;24(2):9. doi: 10.1167/jov.24.2.9.

    PubMed 38393742

  • A. Dalia Blaga, M. Frutos-Pascual, C. Creed, and I. Williams, "A Grasp on Reality: Understanding Grasping Patterns for Object Interaction in Real and Virtual Environments," in 2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), 2021, pp. 391-396. doi: 10.1109/ISMAR-Adjunct54149.2021.00090.

  • Chan PT, Chang WC, Chiu HL, Kao CC, Liu D, Chu H, Chou KR. Effect of interactive cognitive-motor training on eye-hand coordination and cognitive function in older adults. BMC Geriatr. 2019 Jan 28;19(1):27. doi: 10.1186/s12877-019-1029-y.

    PubMed 30691404

  • "Dementia Prevention and Care Policy and Action Plan 2.0 Ministry of Health and Welfare," 2018.

  • P. Lenik, K. Przednowek, M. Śliż, G. Bobula, and J. Lenik, "The impact of exercises with a reaction ball on the eye-hand coordination of basketball players," Apr. 2017.

  • C. A. Manning and J. K. Ducharme, "Chapter 6 - Dementia Syndromes in the Older Adult," in Handbook of Assessment in Clinical Gerontology (Second Edition), Second Edition., P. A. Lichtenberg, Ed., San Diego: Academic Press, 2010, pp. 155-178. doi: https://doi.org/10.1016/B978-0-12-374961-1.10006-5.

  • Heintz Walters B, Huddleston WE, O'Connor K, Wang J, Hoeger Bement M, Keenan KG. The role of eye movements, attention, and hand movements on age-related differences in pegboard tests. J Neurophysiol. 2021 Nov 1;126(5):1710-1722. doi: 10.1152/jn.00629.2020. Epub 2021 Oct 13.

    PubMed 34644180

  • Van Halewyck F, Lavrysen A, Levin O, Boisgontier MP, Elliott D, Helsen WF. Both age and physical activity level impact on eye-hand coordination. Hum Mov Sci. 2014 Aug;36:80-96. doi: 10.1016/j.humov.2014.05.005. Epub 2014 Jun 22.

    PubMed 24964357

Questions about this trial

What is this clinical trial studying?

A study testing Real Object-Based Catching System and Virtual Object-Based Catching System in people with Healthy Adult, run by National Cheng-Kung University Hospital at 1 site in Taiwan.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: finished, as of the sponsor's last update on 6 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Executive Functions via Flanker-ERP Measurement (time frame: 2 hours). The study lists 8 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07394231, which also lists 17 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Feb 2026.

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