Effects of Feedback and Aging on Aiming Movements in Virtual Reality
Performing Fitts' Tasks in Virtual Reality With and Without Augmented Feedback: a Comparison Between Young and Older Adults
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Sophia Hanke, M.Sc.
- Phone Number: +491607987923
- Email: sophia.hanke@univ-amu.fr
Study Contact Backup
- Name: Jean-Jacques Temprado, Full professor, PhD
- Email: jean-jacques.temprado@univ-amu.fr
Study Locations
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Marseille, France, 13009
- Faculté des Sciences du Sport, Aix Marseille University - Campus Luminy
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Contact:
- Sophia Hanke, M.Sc.
- Phone Number: +491607987923
- Email: sophia.hanke@univ-amu.fr
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Contact:
- Jean-Jacques Temprado, Full professor, PhD
- Email: jean-jacques.temprado@univ-amu.fr
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Aged 18-28 (young adults [YA] group) or 65-75 (healthy older adults [HOA] group)
- Right-handed
- Normal or corrected-to-normal vision (glasses or contact lenses permitted)
- Clear and comfortable vision through the head-mounted display during a brief fitting (very bulky glasses may be incompatible)
- No self-reported history of neurological or psychiatric disorders, as confirmed by participant report and cross-checked against a standardized list of relevant medications
- Able to provide informed consent and follow experimental instructions in French or English
Additional criteria for HOA
- Normal cognitive functioning (Montreal cognitive assessment [MoCA] score ≥ 26)
- No self-reported acute or chronic pain in the dominant arm, shoulder, or elbow that would preclude performing repetitive arm movements in space.
- Self-reported full functional range of motion in the dominant arm (able to extend the arm fully without discomfort or restriction)
Exclusion Criteria:
- Individuals currently playing video games more than 5 hours/week.
- Uncorrected visual, auditory, or motor impairments that would interfere with task performance.
- Participant height outside the range of 1.50-1.80 m.
- Self-reported diagnosis of a neurodegenerative disease (e.g., Parkinson's disease, Alzheimer's disease)
- Self-reported use of medications known to significantly affect cognitive or motor function (a list of relevant medications will be presented during screening).
- Cervical pain that could preclude wearing the VR headset during the full duration of the experimental session.
- Self-reported history of severe motion sickness or vestibular issues that could be exacerbated by VR exposure
- High susceptibility to cybersickness, as assessed via the Visually Induced Motion Sickness Susceptibility Questionnaire which was developed specifically for pre-exposure screening; cut-off: ≥ 12.
- Individuals for whom the headset cannot be properly adjusted, e.g., due to an interpupillary distance outside the adjustment range of the head-mounted display (i.e., <53 mm or >75 mm).
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Basic Science
- Allocation: Non-Randomized
- Interventional Model: Crossover Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Experimental: Right-handed young adults (18 to 28 years)
Healthy right-handed young adults aged 18 to 28 years receiving instructions to complete Fitts' task in four different feedback conditions in randomized order: R-intrinsic, VR-intrinsic, VR-augmented global, and VR-augmented specific.
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Augmented visual error feedback will indicate the type of error.
Generally, the target turns blue whenever it is entered.
After remaining inside for 1 second, the trial is confirmed and the target turns green.
For any error, the target turns red: either directly from grey if the target was never entered, or after briefly turning blue when entered and exited.
Errors further trigger written messages: overshoots show 'too long', undershoots 'too short', and other deviations display directional errors (too right/too left/too high/too low).
Augmented visual error feedback will indicate trial outcome, with the target sphere changing color (green for correct hit; red for miss).
Participants will view the physical apparatus.
Inherent visual and proprioceptive feedback will be available but no augmented visual feedback.
The immersive virtual setup will be presented without augmented visual feedback; participants will rely on intrinsic feedback.
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Experimental: Right-handed healthy older adults (65 to 75 years)
Healthy older adults (65 to 75 years) receiving instructions to complete Fitts' task in four different feedback conditions in randomized order: R-intrinsic, VR-intrinsic, VR-augmented global, and VR-augmented specific.
|
Augmented visual error feedback will indicate the type of error.
Generally, the target turns blue whenever it is entered.
After remaining inside for 1 second, the trial is confirmed and the target turns green.
For any error, the target turns red: either directly from grey if the target was never entered, or after briefly turning blue when entered and exited.
Errors further trigger written messages: overshoots show 'too long', undershoots 'too short', and other deviations display directional errors (too right/too left/too high/too low).
Augmented visual error feedback will indicate trial outcome, with the target sphere changing color (green for correct hit; red for miss).
Participants will view the physical apparatus.
Inherent visual and proprioceptive feedback will be available but no augmented visual feedback.
The immersive virtual setup will be presented without augmented visual feedback; participants will rely on intrinsic feedback.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Slope of the efficiency function (Fitts' Law) across age groups and feedback conditions
Time Frame: Day 1 of 1
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According to Fitts' Law, movement time increases linearly with task difficulty (index of difficulty; ID).
This relationship is captured by the efficiency function, plotting movement time against ID.
The slope of the efficiency function reflects an individual's information processing efficiency (IPE): steeper slopes indicate lower IPE, while shallower slopes indicate higher IPE.
Prior studies conducted in real-world conditions show older adults have steeper slopes, suggesting reduced IPE.
In VR, performance patterns such as longer movement times and more sub-movements suggest efficiency function slopes may further differ.
Therefore, this outcome will systematically compare efficiency function slopes across age groups and feedback conditions in VR and real-world settings.
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Day 1 of 1
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Effects of feedback conditions and age on movement times [ms]
Time Frame: Day 1 of 1
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It will be examined how feedback condition, task difficulty, and age group affect movement time (in ms) in virtual reality, and interactions between these factors will also be analyzed.
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Day 1 of 1
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Effects of feedback conditions and age on acceleration times [ms]
Time Frame: Day 1 of 1
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It will be examined how feedback condition, task difficulty, and age group affect acceleration time (in ms) in virtual reality, and interactions between these factors will also be analyzed.
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Day 1 of 1
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Effects of feedback conditions and age on deceleration times [ms]
Time Frame: Day 1 of 1
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It will be examined how feedback condition, task difficulty, and age group affect deceleration time (in ms) in virtual reality, and interactions between these factors will also be analyzed.
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Day 1 of 1
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Effects of feedback condition and age group on error rate [%]
Time Frame: Day 1 of 1
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It will be examined how feedback condition, task difficulty, and age group affect error rate (in %) in virtual reality, and interactions between these factors will also be analyzed.
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Day 1 of 1
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Jean-Jacques Temprado, Full professor, PhD, Aix Marseille Université
Publications and helpful links
General Publications
- FITTS PM. The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol. 1954 Jun;47(6):381-91. No abstract available.
- FITTS PM, PETERSON JR. INFORMATION CAPACITY OF DISCRETE MOTOR RESPONSES. J Exp Psychol. 1964 Feb;67:103-12. doi: 10.1037/h0045689. No abstract available.
- Voelcker-Rehage C, Godde B, Staudinger UM. Cardiovascular and coordination training differentially improve cognitive performance and neural processing in older adults. Front Hum Neurosci. 2011 Mar 17;5:26. doi: 10.3389/fnhum.2011.00026. eCollection 2011.
- Sleimen-Malkoun R, Temprado JJ, Berton E. Age-related dedifferentiation of cognitive and motor slowing: insight from the comparison of Hick-Hyman and Fitts' laws. Front Aging Neurosci. 2013 Oct 10;5:62. doi: 10.3389/fnagi.2013.00062. eCollection 2013.
- Temprado JJ, Torre MM, Langeard A, Julien-Vintrou M, Devillers-Reolon L, Sleimen-Malkoun R, Berton E. Intentional Switching Between Bimanual Coordination Patterns in Older Adults: Is It Mediated by Inhibition Processes? Front Aging Neurosci. 2020 Feb 18;12:29. doi: 10.3389/fnagi.2020.00029. eCollection 2020.
- Temprado JJ, Sleimen-Malkoun R, Lemaire P, Rey-Robert B, Retornaz F, Berton E. Aging of sensorimotor processes: a systematic study in Fitts' task. Exp Brain Res. 2013 Jul;228(1):105-16. doi: 10.1007/s00221-013-3542-0. Epub 2013 May 7.
- Niemann C, Godde B, Voelcker-Rehage C. Not only cardiovascular, but also coordinative exercise increases hippocampal volume in older adults. Front Aging Neurosci. 2014 Aug 4;6:170. doi: 10.3389/fnagi.2014.00170. eCollection 2014.
- McAnally K, Wallis G. Visual-haptic integration, action and embodiment in virtual reality. Psychol Res. 2022 Sep;86(6):1847-1857. doi: 10.1007/s00426-021-01613-3. Epub 2021 Oct 28.
- Matthews MJ, Yusuf M, Doyle C, Thompson C. Quadrupedal movement training improves markers of cognition and joint repositioning. Hum Mov Sci. 2016 Jun;47:70-80. doi: 10.1016/j.humov.2016.02.002. Epub 2016 Feb 17.
- Kourtesis P, Vizcay S, Marchal M, Pacchierotti C, Argelaguet F. Action-Specific Perception & Performance on a Fitts's Law Task in Virtual Reality: The Role of Haptic Feedback. IEEE Trans Vis Comput Graph. 2022 Nov;28(11):3715-3726. doi: 10.1109/TVCG.2022.3203003. Epub 2022 Oct 21.
- Batmaz AU, Stuerzlinger W. Effective Throughput Analysis of Different Task Execution Strategies for Mid-Air Fitts' Tasks in Virtual Reality. IEEE Trans Vis Comput Graph. 2022 Nov;28(11):3939-3947. doi: 10.1109/TVCG.2022.3203105. Epub 2022 Oct 21.
- Budde H, Voelcker-Rehage C, Pietrabyk-Kendziorra S, Ribeiro P, Tidow G. Acute coordinative exercise improves attentional performance in adolescents. Neurosci Lett. 2008 Aug 22;441(2):219-23. doi: 10.1016/j.neulet.2008.06.024. Epub 2008 Jun 13.
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
Other Study ID Numbers
- IRB00012476-2025-25-11-451
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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