Motor SkillsNCT07905768
Impact of Force Feedback in VR Training on EEG Biomarkers and Real-World Motor Performance
A study testing Active Comparator: Physical Training and Experimental: Virtual Reality with Force Feedback in people with Motor Skills and Healthy Volunteer, run by University of Ontario Institute of Technology at 1 site in Canada.
Trial summary
The goal of this interventional study is to learn how force feedback in virtual reality training affects electroencephalography (EEG) biomarkers and/or real-world motor performance. Read more about this study
- Who is it for?
- Ages 18 to 35 years
- Conditions the study is for
- Motor Skills, Healthy Volunteer
- What is being tested?
- Active Comparator: Physical Training and Experimental: Virtual Reality with Force Feedback
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 45 participants
- Where
- 1 siteCanada
- Study dates
- 21 Oct 2026to 31 Aug 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 18 to 35 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- University-aged participants 18-35 years old that are right-handed.
Who cannot join
- any known medical conditions or medication use that could influence the EEG measurements or performance in VR, including being prone to motion sickness.
Trial locations and contacts
1 site in 1 country.
Canada1 site
Human Neurophysiology lab, Ontario Tech University
Oshawa, Ontario, L1G0C5
About this study
Official title: Impact of Force Feedback in Virtual Reality Training on Electroencephalography Biomarkers and Real-World Motor Performance
The goal of this interventional study is to learn how force feedback in virtual reality training affects electroencephalography (EEG) biomarkers and/or real-world motor performance. The main question it aims to answer is:
● How does physical training compared to virtual reality training with force feedback compared with virtual reality training without force feedback affect EEG biomarkers and/or motor performance?
Read more
Participants will:
- Have baseline EEG measurements taken before, during, and after participation in either a physical or virtual training activity.
- Participate in the selected training activity they have been randomly assigned to (either physical, virtual with force feedback or virtual without force feedback)
- For both VR training groups, they will have their motor performance measured performing the real world physical activity once they have completed the training activity. This will function as a transfer task.
Read the detailed description
Background: Virtual reality (VR) is an immersive technology that allows users to experience and interact with digital environments. It is becoming increasingly popular in professional fields like medical training, sports, and rehabilitation (Rizzo \& Koenig, 2017). However, VR systems don't always provide the same physical feedback as the real world, which can impact how users learn and perform physical tasks. This is particularly relevant when it comes to force feedback, which involves using technology to simulate the resistance, pressure, and movement that your body feels when interacting with objects. For example, when picking up a water bottle, sensors in your hand allow your brain to understand the shape, size, weight, and location of the water bottle. In VR, this feedback is usually not provided, so participants may not feel the texture or resistance of objects the way that they would in the real world (Kilteni et al., 2012). These mismatches can impact the effectiveness of motor training in VR, making it harder for users to transfer skills learned in VR to real-world settings. This research aims to explore how force feedback differs in VR compared to the real world, and how these differences affect motor learning.
Purpose: First, we seek to understand how the differences in force feedback between VR and the real world impact motor learning. VR has been used in rehabilitation and motor training with some success, but the differences in sensory feedback have not been fully explored. For example, previous studies have shown that force feedback can improve motor learning in virtual environments, but force feedback is often lacking in current VR systems (Sigrist et al., 2013). Furthermore, research suggests that force feedback and visual accuracy can also play crucial roles in how well users learn and transfer skills (Riener \& Harders, 2012). This study will build on these findings to determine if and how the addition or lack of force feedback in VR affects motor learning.
Methodology: Upon providing informed consent, participants undergo demographic screening and pre-screening questionnaires to rule out confounding neck or upper limb pain. Participants are then randomly assigned to one of three parallel training arms:
- Physical Training: Skills training using a real-world physical simulator and real forceps with activated internal mechanism that gives physical feedback.
- VR with Force Feedback: Skills training using VR simulator and real forceps, with activated internal mechanism that gives physical feedback.
- VR without Force Feedback: Skills training using VR simulator and real forceps, with limp internal mechanism that does not provide feedback.
Experiment Timeline:
- Preparation: Participants are fitted with a 64-electrode EEG cap and prepared with conductive gel.
- Pre-Intervention Baseline: A 5-minute resting-state EEG recording is completed.
- Intervention Phase: Participants complete several training blocks until a performance plateau is reached) according to their assigned arm. Using the simulator requires participants to extract a round object from a narrow tunnel attached to a cave shape via a mechanical arm using forceps. Prior to skill the motor acquisition trials, participants will "see" an image of the round object in the cave, using a Meta Quest Pro VR headset for those in the VR arms of the project.
- EEG will be collected in response to various activities that relate to forceps use (e.g. attaching the object, following a trajectory to extract the object, etc.)
- Post-Intervention Testing: Immediately following training, a second 5-minute resting-state EEG is recorded.
- Conditions
- Motor Skills, Healthy Volunteer
- Being tested
- Active Comparator: Physical Training, Experimental: Virtual Reality with Force Feedback, Sham Comparator: Virtual Reality without Force Feedback
- Keywords
- Virtual Reality, Feedback, Psychological, Motor learning, Haptic technology, Electroencephalography, Task Performance and Analysis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Active Comparator: Physical TrainingOther
The participant will extract a physical round object from a real world physical cave model through a tunnel using physical forceps and will be guided by resistance from an attached mechanism.
Experimental: Virtual Reality with Force FeedbackOther
The participant will extract the round object from the cave in virtual reality using physical forceps and will be guided by resistance from the simulator.
Sham Comparator: Virtual Reality without Force FeedbackOther
The participant will extract a physical round object from the cave using physical forceps but will not receive any resistance from the simulator.
| Study group | Role | What they receive |
|---|---|---|
| Physical training | Active comparator | Participants use the physical simulator complete with an internal mechanism that is activated with resistance and coded with accurate trajectory. Receives: Other: Active Comparator: Physical Training |
| Virtual training with force feedback | Experimental | Participants use the virtual reality simulator along with a mechanism that is activated with resistance and coded with accurate trajectory. Receives: Other: Experimental: Virtual Reality with Force Feedback |
| Virtual Reality without Force Feedback | Sham comparator | Participants use the virtual reality simulator along with a mechanism that is limp and does not provide resistance. Receives: Other: Sham Comparator: Virtual Reality without Force Feedback |
What is being measured
The primary outcome is the main question the study is designed to answer.
Resting State Electroencephalography
Participants will wear a 64-electrode whole-head electroencephalography (EEG) cap to measure their brain signals. Once the EEG cap has been prepared using conductive gel, a resting state EEG recording will be performed. Participants will be asked to remain sitting still and relaxed in a chair. While sitting they will be asked to stare at a cross symbol displayed on a white screen on a monitor in front of them. While doing this, their brain signals will be recorded through the EEG.
Measured: 2 blocks of 5 minutes each before and after the training, 10 minutes total
Trajectory Measurement
The trajectory that the participants used to extract the round object from the cave will be measured using the simulator internal mechanism and compared to the expert trajectory that is coded within the simulator.
Measured: The data will be collected over 30 to 60 minutes/
Secondary outcomes (1)
EEG biomarkers related to proprioception and error
Event-related EEG potentials and error related negativity will be collected in relation to specific physical stages of the forceps use.
Measured: Over the 30 to 60 minutes of skill acquisition.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Oct 2026
- Study start21 Oct 2026
- Primary completion31 Jul 2027 (estimated)
- Study completion31 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for Motor SkillsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
- Parallel groups
- Model description
- The first group of Participants will be assigned to Physical training activity using real world-objects; The second group will be randomly assigned to 1 of 2 training conditions: a) Skills training activity in virtual reality receiving force feedback b) Skills training activity in virtual reality without force feedback
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 45 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Ontario Institute of Technology
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Bernadette Murphy, PhD, Principal investigator, Ontario Tech University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07905768
- Sponsor's protocol ID
- 20342
- Status last verified
- Oct 2026
- First submitted
- 23 Oct 2026
- Last updated
- 29 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: TCPS2 in Canada is currently requiring a new layer of participant permission prior to sharing even de-identified data, so there is no guarantee that participants will consent to this.
Publications
Riener, R., & Harders, M. (2012). Virtual Reality in Medicine. Springer. https://doi.org/10.1007/978-1-4471-4011-5
Sigrist R, Rauter G, Riener R, Wolf P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon Bull Rev. 2013 Feb;20(1):21-53. doi: 10.3758/s13423-012-0333-8.
PubMed 23132605Kilteni, K., Groten, R., & Slater, M. (2012). The sense of embodiment in virtual reality. Presence: Teleoperators and Virtual Environments, 21(4), 373-387. https://doi.org/10.1162/PRES_a_00124
Rizzo AS, Koenig ST. Is clinical virtual reality ready for primetime? Neuropsychology. 2017 Nov;31(8):877-899. doi: 10.1037/neu0000405.
PubMed 29376669
Study at a glance
From the registry record, last updated by the sponsor on 29 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Impact of Force Feedback in Virtual Reality Training on Electroencephalography Biomarkers and Real-World Motor Performance
- ClinicalTrials.gov ID
- NCT07905768
- Acronym / sponsor ID
- 20342
- Conditions
- Motor Skills, Healthy Volunteer
- Keywords
- Virtual Reality, Feedback, Psychological, Motor learning, Haptic technology, Electroencephalography, Task Performance and Analysis
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 45 participants (estimated)
- Lead sponsor
- University of Ontario Institute of TechnologyUniversity, hospital or other
- Study start
- 21 Oct 2026 (actual)
- Primary completion
- 31 Jul 2027 (estimated)
- Study completion
- 31 Aug 2027 (estimated)
- First posted
- 29 Oct 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this interventional study is to learn how force feedback in virtual reality training affects electroencephalography (EEG) biomarkers and/or real-world motor performance. The main question it aims to answer is:
● How does physical training compared to virtual reality training with force feedback compared with virtual reality training without force feedback affect EEG biomarkers and/or motor performance?
Participants will:
- Have baseline EEG measurements taken before, during, and after participation in either a physical or virtual training activity.
- Participate in the selected training activity they have been randomly assigned to (either physical, virtual with force feedback or virtual without force feedback)
- For both VR training groups, they will have their motor performance measured performing the real world physical activity once they have completed the training activity. This will function as a transfer task.
Detailed description
Background: Virtual reality (VR) is an immersive technology that allows users to experience and interact with digital environments. It is becoming increasingly popular in professional fields like medical training, sports, and rehabilitation (Rizzo \& Koenig, 2017). However, VR systems don't always provide the same physical feedback as the real world, which can impact how users learn and perform physical tasks. This is particularly relevant when it comes to force feedback, which involves using technology to simulate the resistance, pressure, and movement that your body feels when interacting with objects. For example, when picking up a water bottle, sensors in your hand allow your brain to understand the shape, size, weight, and location of the water bottle. In VR, this feedback is usually not provided, so participants may not feel the texture or resistance of objects the way that they would in the real world (Kilteni et al., 2012). These mismatches can impact the effectiveness of motor training in VR, making it harder for users to transfer skills learned in VR to real-world settings. This research aims to explore how force feedback differs in VR compared to the real world, and how these differences affect motor learning.
Purpose: First, we seek to understand how the differences in force feedback between VR and the real world impact motor learning. VR has been used in rehabilitation and motor training with some success, but the differences in sensory feedback have not been fully explored. For example, previous studies have shown that force feedback can improve motor learning in virtual environments, but force feedback is often lacking in current VR systems (Sigrist et al., 2013). Furthermore, research suggests that force feedback and visual accuracy can also play crucial roles in how well users learn and transfer skills (Riener \& Harders, 2012). This study will build on these findings to determine if and how the addition or lack of force feedback in VR affects motor learning.
Methodology: Upon providing informed consent, participants undergo demographic screening and pre-screening questionnaires to rule out confounding neck or upper limb pain. Participants are then randomly assigned to one of three parallel training arms:
- Physical Training: Skills training using a real-world physical simulator and real forceps with activated internal mechanism that gives physical feedback.
- VR with Force Feedback: Skills training using VR simulator and real forceps, with activated internal mechanism that gives physical feedback.
- VR without Force Feedback: Skills training using VR simulator and real forceps, with limp internal mechanism that does not provide feedback.
Experiment Timeline:
- Preparation: Participants are fitted with a 64-electrode EEG cap and prepared with conductive gel.
- Pre-Intervention Baseline: A 5-minute resting-state EEG recording is completed.
- Intervention Phase: Participants complete several training blocks until a performance plateau is reached) according to their assigned arm. Using the simulator requires participants to extract a round object from a narrow tunnel attached to a cave shape via a mechanical arm using forceps. Prior to skill the motor acquisition trials, participants will "see" an image of the round object in the cave, using a Meta Quest Pro VR headset for those in the VR arms of the project.
- EEG will be collected in response to various activities that relate to forceps use (e.g. attaching the object, following a trajectory to extract the object, etc.)
- Post-Intervention Testing: Immediately following training, a second 5-minute resting-state EEG is recorded.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 3
- Model description
- The first group of Participants will be assigned to Physical training activity using real world-objects; The second group will be randomly assigned to 1 of 2 training conditions: a) Skills training activity in virtual reality receiving force feedback b) Skills training activity in virtual reality without force feedback
| Arm | Type | Receives |
|---|---|---|
| Physical training | Active comparator | Other: Active Comparator: Physical TrainingParticipants use the physical simulator complete with an internal mechanism that is activated with resistance and coded with accurate trajectory. |
| Virtual training with force feedback | Experimental | Other: Experimental: Virtual Reality with Force FeedbackParticipants use the virtual reality simulator along with a mechanism that is activated with resistance and coded with accurate trajectory. |
| Virtual Reality without Force Feedback | Sham comparator | Other: Sham Comparator: Virtual Reality without Force FeedbackParticipants use the virtual reality simulator along with a mechanism that is limp and does not provide resistance. |
Who may qualify
- Ages
- 18 to 35 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (1 listed)
- University-aged participants 18-35 years old that are right-handed.
Key exclusion criteria (1 listed)
- any known medical conditions or medication use that could influence the EEG measurements or performance in VR, including being prone to motion sickness.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Active Comparator: Physical TrainingThe participant will extract a physical round object from a real world physical cave model through a tunnel using physical forceps and will be guided by resistance from an attached mechanism. | Other | Physical training |
| Experimental: Virtual Reality with Force FeedbackThe participant will extract the round object from the cave in virtual reality using physical forceps and will be guided by resistance from the simulator. | Other | Virtual training with force feedback |
| Sham Comparator: Virtual Reality without Force FeedbackThe participant will extract a physical round object from the cave using physical forceps but will not receive any resistance from the simulator. | Other | Virtual Reality without Force Feedback |
Primary outcome
Resting State Electroencephalography
Time frame: 2 blocks of 5 minutes each before and after the training, 10 minutes total
Participants will wear a 64-electrode whole-head electroencephalography (EEG) cap to measure their brain signals. Once the EEG cap has been prepared using conductive gel, a resting state EEG recording will be performed. Participants will be asked to remain sitting still and relaxed in a chair. While sitting they will be asked to stare at a cross symbol displayed on a white screen on a monitor in front of them. While doing this, their brain signals will be recorded through the EEG.
Trajectory Measurement
Time frame: The data will be collected over 30 to 60 minutes/
The trajectory that the participants used to extract the round object from the cave will be measured using the simulator internal mechanism and compared to the expert trajectory that is coded within the simulator.
1 secondary outcome
EEG biomarkers related to proprioception and error
Time frame: Over the 30 to 60 minutes of skill acquisition.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Oct 2026.
- BackgroundRiener, R., & Harders, M. (2012). Virtual Reality in Medicine. Springer. https://doi.org/10.1007/978-1-4471-4011-5
- Background: PubMed 23132605Sigrist R, Rauter G, Riener R, Wolf P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon Bull Rev. 2013 Feb;20(1):21-53. doi: 10.3758/s13423-012-0333-8.
- BackgroundKilteni, K., Groten, R., & Slater, M. (2012). The sense of embodiment in virtual reality. Presence: Teleoperators and Virtual Environments, 21(4), 373-387. https://doi.org/10.1162/PRES_a_00124
- Background: PubMed 29376669Rizzo AS, Koenig ST. Is clinical virtual reality ready for primetime? Neuropsychology. 2017 Nov;31(8):877-899. doi: 10.1037/neu0000405.
- Individual participant dataSharing planned: Undecided. TCPS2 in Canada is currently requiring a new layer of participant permission prior to sharing even de-identified data, so there is no guarantee that participants will consent to this.
Related trials for Motor Skills
Not yet recruiting
Sensory-integration Therapy Verses Augumented Reality-based Training in ASD
Autism Spectrum Disorder
Not yet recruiting
Cognitive-Motor Training With the DextEgg in Children With ADHD
Attention Deficit Hyperactivity Disorder (ADHD)
RecruitingObservational study
Predicting Future Errors During Skill Performance
Healthy
RecruitingObservational study
Motor Development and Early Predictors of Psychomotor Outcomes in Preterm and Term Infants Assessed by MOS-R and Caregiver Questionnaire at 18 and 36 Months
Neurodevelopmental Disorders, Motor Skills Disorders
RecruitingObservational study
Evaluation of Catching Skills in Preschoolers With Motor Difficulties
Development Coordination Disorder, Motor Disabilities
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Bernadette Murphy, PhD principal investigator
Ontario Tech University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Active Comparator: Physical Training and Experimental: Virtual Reality with Force Feedback in people with Motor Skills and Healthy Volunteer, run by University of Ontario Institute of Technology at 1 site in Canada.
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 1 inclusion and 1 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: under way, not looking for participants, as of the sponsor's last update on 29 Oct 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 Canada. 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. Some participants in this study may receive a placebo. 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?
This study is still under way. Results are not available in the source record yet.
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?
Resting State Electroencephalography (time frame: 2 blocks of 5 minutes each before and after the training, 10 minutes total). The study lists 2 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 NCT07905768, which also lists 4 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 29 Oct 2026.