Effects of Feedback and Aging on Aiming Movements in Virtual Reality

Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-75
SponsorAix Marseille Université

About this trial

This study has two main objectives: First, to better understand how a motor task commonly used by researchers, known as the Fitts' task, is performed in virtual reality. It consists of reaching a target, which may be large or small, by extending the right arm. This task is similar to movements commonly performed in everyday life. It is also increasingly used in virtual reality video games designed to train older adults or patients with functional limitations. Secondly, the investigators aim to describe how age influences performance in this task by comparing young adults and older adults. This can help better adapt the protocols used in virtual reality to the characteristics of users. It is of particular interest how movements change when the task becomes more difficult, whether these changes differ between young adults and older adults, and whether the information and feedback provided through virtual reality can improve the quality of motor performance. What is expected of participants: Participants will be seated comfortably, wearing a lightweight virtual reality headset and holding a controller in their right hand that will be used to reach for a target by keeping the controller within the target for about one second. The targets will vary in size, so some trials will seem easier and others more difficult. The task is simply to move as quickly as possible while remaining accurate (hitting the target). This instruction is important, and the experimenter will repeat it regularly during the experiment. The task will be performed under different conditions: sometimes participants will see the actual configuration of the experimental device in the physical world through the headset, and other times they will see the same configuration presented in virtual reality. In some virtual reality conditions, participants will also receive additional visual information indicating whether the target has been hit correctly. Short breaks are scheduled at regular intervals. Additional breaks can be asked for at any time when needed. The most important point is to avoid any fatigue or discomfort. If participants experience any, they are asked and encouraged to inform the experimenter. Before starting the experiment, participants will undergo a short training session to familiarize themselves with the task and the device.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

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)

Disqualifiers

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)

Trial design

Design model

Crossover

Treatments tested in this trial

  • VR-augmented specific feedback

    Behavioral

    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).

  • VR-augmented global feedback

    Behavioral

    Augmented visual error feedback will indicate trial outcome, with the target sphere changing color (green for correct hit; red for miss).

  • R-intrinsic feedback

    Behavioral

    Participants will view the physical apparatus. Inherent visual and proprioceptive feedback will be available but no augmented visual feedback.

  • VR-intrinsic feedback

    Behavioral

    The immersive virtual setup will be presented without augmented visual feedback; participants will rely on intrinsic feedback.

Treatment groups

30 Participants
are divided into 2 treatment groups
Group A: Right-handed young adults (18 to 28 years)Experimental treatment 4 interventions
Group B: Right-handed healthy older adults (65 to 75 years)Experimental treatment 4 interventions

Trial outcomes

Primary outcomes

1

Slope of the efficiency function (Fitts' Law) across age groups and feedback conditions

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.

Time frame
Day 1 of 1

Secondary outcomes

1

Effects of feedback conditions and age on movement times [ms]

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.

Time frame
Day 1 of 1
2

Effects of feedback conditions and age on acceleration times [ms]

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.

Time frame
Day 1 of 1
3

Effects of feedback conditions and age on deceleration times [ms]

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.

Time frame
Day 1 of 1
4

Effects of feedback condition and age group on error rate [%]

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.

Time frame
Day 1 of 1

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

This trial is not recruiting at the moment. You can still explore other options: