Healthy Volunteers - Male and FemaleNCT07922265
Neuroergonomic Analysis of a Brain-Computer Interface Device (BCI)
A study testing EEG-Based Brain-Computer Interface Device in people with Healthy Volunteers - Male and Female, run by Universidade Federal do Paraná at 2 sites in Brazil.
Trial summary
This study evaluates the mental workload and user experience associated with a Brain-Computer Interface (BCI) device called Exobots. The Exobots system uses a non-invasive electroencephalography (EEG) headset to detect neural signals and control a robotic glove that assists hand movement. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Healthy Volunteers - Male and Female
- What is being tested?
- EEG-Based Brain-Computer Interface Device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30 participants
- Where
- 2 sitesBrazil
- Study dates
- 28 Dec 2026to 31 Mar 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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Technical-level students, undergraduate students, graduate students, and staff members, of both sexes, healthy, affiliated with the Federal University of Paraná (UFPR) or the Federal Institute of Paraná (IFPR).
- Age 18 years or older.
Who cannot join
- Use of psychoactive medications.
- History of epilepsy or other neurological conditions that would preclude the use of the device.
- Severe motor limitations that prevent interaction with the device.
- Recent traumatic brain injuries.
- Injury, dermatitis, or open wound on the scalp.
- Excessive consumption of stimulant substances within the last 4 hours.
- Sleep deprivation (less than 5 hours of sleep the previous night) or extreme sleepiness on the day of data collection.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Brazil2 sites
Federal Technological University of Paraná
Curitiba, Paraná, 80230901
Lucas T dos Santos Vieira, +55 041 987469362, lucastadeu1875@gmail.com
Henrique C Carvalho, +55 012 9991383609, hccarvalho@utfpr.edu.br
UFPR
Curitiba, Paraná
Lucas Tadeu dos Santos Vieira, Bacharel, +55 041 987469362, lucastadeu1875@gmail.com
About this study
Official title: Neuroergonomic Analysis of a Brain-Computer Interface (BCI) Device Based on EEG Signals and User Experience
This study evaluates the mental workload and user experience associated with a Brain-Computer Interface (BCI) device called Exobots. The Exobots system uses a non-invasive electroencephalography (EEG) headset to detect neural signals and control a robotic glove that assists hand movement. The primary goal is to assess how three different system sensitivity levels (low, medium, high) impact mental effort, usability, and overall user perception. Healthy adult volunteers (students and staff from IFPR and UFPR) will participate in a single experimental session. During the session, they will perform a repeated mental imagery task (imagine hand movement) while the EEG records their brain activity. After each sensitivity block, participants will complete standardized questionnaires (NASA Task Load Index and User Experience Questionnaire) and a semi-structured qualitative interview about their experience. By combining objective neurophysiological data with subjective feedback, this research aims to identify optimal sensitivity thresholds that minimize cognitive strain and maximize user comfort. The findings are expected to provide technical recommendations for designing more adaptive, user-centered BCI systems for future neurorehabilitation applications.
Read the detailed description
Background and Rationale
Brain-Computer Interfaces (BCIs) are increasingly employed in neurorehabilitation settings to assist individuals with motor impairments. While these systems enable direct neural control of assistive devices, there is a significant gap in understanding the cognitive demands they impose on users. Excessive mental workload can lead to frustration, disengagement, and suboptimal therapeutic outcomes. This study addresses this gap by applying a neuroergonomic approach-integrating objective neurophysiological measures with subjective user experience (UX) assessments.
Objectives
Primary Objective: To evaluate cognitive load during interaction with the Exobots BCI device by integrating neurophysiological metrics (EEG), psychometric UX scores, and subjective user perceptions.
Secondary Objectives:
- To map neural activity patterns, focusing on theta, alpha, and beta frequency bands, during BCI interaction.
- To correlate neurophysiological indicators of mental effort with usability and UX measures obtained via the NASA-TLX and UEQ.
- To identify preliminary operational sensitivity threshold parameters established during individual device calibration.
- To analyze participants' subjective perceptions of the physical BCI interface using a semi-structured questionnaire with open-ended questions and visual cards.
- To formulate technical recommendations for BCI interface design based on the integrated analysis of neurophysiological, psychometric, and qualitative data.
Study Design
This is an interventional, single-group, experimental study without a control arm. All participants will undergo the same protocol, testing three distinct sensitivity levels (low, medium, high) in a within-subjects design, with the order of sensitivity levels counterbalanced to avoid order effects.
Study Population and Sample Size
Healthy adults (aged 18 years or older) who are students (undergraduate, graduate, technical level) or staff members from the Federal University of Paraná (UFPR) and the Federal Institute of Paraná (IFPR) will be recruited.
The minimum sample size was calculated using G*Power software (version 3.1.9.7) for a bivariate normal correlation model (Exact test, Family: Correlation). Considering an expected effect size of r = 0.50, a significance level of α = 0.05, and a statistical power of (1-β) = 0.80, the calculation indicated a minimum of 29 participants. To ensure statistical robustness and account for potential data loss due to EEG artifacts or voluntary dropouts, the target enrollment is set at 30 participants, with recruitment extended to up to 60 individuals if necessary.
Intervention and Procedures
Screening and Consent: Interested individuals will receive and sign the Informed Consent Form (TCLE). A screening questionnaire will be administered to verify inclusion/exclusion criteria (e.g., no neurological disorders, no recent head injuries).
Device and Preparation: Participants will interact with the Exobots device (provided by Neurobots). An elastic cap equipped with six dry/wet EEG electrodes will be placed on the participant's scalp. A water-based conductive gel will be applied to the contact points to ensure optimal signal quality. The robotic glove will be fitted to the participant's hand.
Calibration: The system will be calibrated to recognize each participant's specific neural patterns. Based on the calibration, three distinct sensitivity thresholds (low, medium, high) will be defined and tested individually.
Experimental Protocol: Each participant will complete a sequence of repeated cycles consisting of four sequential steps:
Prepare: The participant focuses attention on their hand in anticipation of the command.
Think: The participant imagines opening/closing their hand without physically executing the movement. The EEG system detects the motor imagery signal. If the signal is maintained above the predetermined threshold for three consecutive seconds, the robotic glove is activated.
Move: The robotic glove passively moves the participant's hand. The participant is instructed to voluntarily accompany this movement if possible.
Relax: The participant stops focusing and rests for a few seconds before the next cycle.
Each sensitivity level will be tested in blocks of approximately 10 minutes, totaling approximately 35 minutes of effective interaction per participant. Sessions will be scheduled in advance, with at least 48 hours' notice.
Outcome Measures
Neurophysiological: Continuous 6-channel EEG recording throughout the task. Spectral power analysis will focus on theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) bands, with particular emphasis on the theta/beta ratio as a validated marker of cognitive load.
Psychometric: Immediately after each sensitivity block, participants will complete the NASA Task Load Index (NASA-TLX) to assess perceived mental, physical, and temporal demands, effort, and frustration. At the end of the entire session, the User Experience Questionnaire (UEQ) will be administered to evaluate pragmatic and hedonic quality attributes.
Qualitative: A semi-structured interview with open-ended questions and thematic cards will be conducted to capture nuanced perceptions regarding the physical interface, comfort, and overall experience that standardized scales may not fully address.
Statistical Analysis
Pearson correlation coefficients will be calculated to assess the association between neurophysiological metrics (e.g., theta/beta ratio, alpha power) and UX scores (UEQ and NASA-TLX). A significance level of p < 0.05 will be adopted. Qualitative data will be analyzed using content analysis techniques to identify recurring themes and insights.
Ethical Considerations
The study protocol was reviewed and approved by the Research Ethics Committee of the Federal Technological University of Paraná (CEP/UTFPR) under Approval Number 8.558.948 (issued July 2, 2026; CAAE: 97426026.1.0000.0165). All procedures comply with Brazilian regulations (Resolution CNS 466/12 and LGPD - Lei Geral de Proteção de Dados).
Participants will be informed that no direct clinical benefits are expected, but that their participation will contribute to the scientific advancement of assistive technologies. Risks are minimal and include mild scalp discomfort from the EEG cap/gel, transient fatigue, or mild frustration. Participants may take breaks or withdraw at any time without penalty. All data will be anonymized, stored on a password-protected local hard drive, and kept confidential.
Data Monitoring Committee
A formal Data Monitoring Committee (DMC) will not be established, as this is a low-risk, non-clinical, academic study with healthy volunteers and no investigational drug or device under IDE regulations.
- Conditions
- Healthy Volunteers - Male and Female
- Being tested
- EEG-Based Brain-Computer Interface Device
- Keywords
- Brain-Computer Interface, BCI, Electroencephalography, Mental Workload, Motor Imagery, NASA-TLX, UEQ, Human Factors
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
EEG-Based Brain-Computer Interface DeviceOther
Also called Exobots BCI System
Non-invasive electroencephalography (EEG)-based Brain-Computer Interface (BCI) system consisting of a 6-channel EEG headset and a robotic hand exoskeleton (glove). The device detects motor imagery neural signals associated with imagined hand movements. When the EEG signal is maintained above a predefined sensitivity threshold for three consecutive seconds, the system triggers the robotic glove to passively move the participant's hand. The study evaluates three distinct sensitivity levels (low, medium, high) during individual calibration. The EEG headset uses water-based conductive gel on contact points to ensure signal quality. The device is manufactured by Neurobots and provided for this research.
| Study group | Role | What they receive |
|---|---|---|
| Exobots BCI Device | Experimental | Participants perform motor imagery tasks (imagining hand movements) while using the Exobots EEG-based BCI device. The system detects neural signals and activates a robotic glove to assist hand movement. Three distinct sensitivity thresholds (low, medium, high) are tested in a counterbalanced order within a single 35-minute experimental session. Receives: Other: EEG-Based Brain-Computer Interface Device |
What is being measured
The primary outcome is the main question the study is designed to answer.
EEG Theta/Beta Ratio as a Neurophysiological Marker of Cognitive Load
Change in the theta/beta spectral power ratio derived from 6-channel electroencephalography (EEG) recordings during motor imagery (imagined hand movement) tasks. The theta/beta ratio is a validated neurophysiological indicator of cognitive workload and mental effort. This measure is compared across the three distinct device sensitivity levels (low, medium, high) to assess differences in cognitive demand.
Measured: Measured continuously during each 10-minute experimental block (blocks 1, 2, and 3) throughout the single 35-minute session.
Secondary outcomes (4)
NASA Task Load Index (NASA-TLX) Global Workload Score
Subjective assessment of perceived mental workload using the NASA-TLX questionnaire. The instrument evaluates six dimensions: mental demand, physical demand, temporal demand, performance, effort, and frustration. The global workload score ranges from 0 to 100, with higher scores indicating greater perceived workload.
Measured: Immediately after each sensitivity block (3 times total) during the experimental session.
User Experience Questionnaire (UEQ) Scores
Assessment of user experience using the standardized User Experience Questionnaire (UEQ). The instrument measures six scales: Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. Each scale ranges from -3 (very negative) to +3 (very positive), with higher scores indicating a more favorable user experience.
Measured: At the end of the entire experimental session.
Qualitative Feedback on BCI Physical Interface and Overall Experience
Thematic content analysis of responses collected through a semi-structured qualitative interview consisting of open-ended questions and visual thematic cards. The analysis captures nuanced perceptions regarding the physical interface (EEG cap and robotic glove), comfort, emotional engagement, usability, and suggestions for device improvement.
Measured: Immediately following the conclusion of the experimental session.
Individual Operational Sensitivity Thresholds
Identification of the optimal sensitivity level (low, medium, or high) for each participant based on the calibration phase and successful device triggering during motor imagery tasks. This measure assesses how individual neural signal characteristics influence the optimal threshold for reliable BCI operation.
Measured: During the calibration phase and across all three experimental blocks within the session.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Nov 2026
- Study start28 Dec 2026 (estimated)
- Primary completion31 Mar 2027 (estimated)
- Study completion31 Mar 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Healthy Volunteers - Male and FemaleStudies 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
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- All participants are assigned to a single group and undergo the same experimental protocol. Each participant interacts with the Exobots BCI device across three distinct sensitivity levels (low, medium, high), presented in a counterbalanced order to minimize order effects. The intervention consists of motor imagery tasks with EEG recording and robotic glove assistance.
- Masking
- None (open label)
- Enrolment
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Universidade Federal do Paraná
- Sponsor type
- University, hospital or other
- Collaborators
- Instituto Federal do Paraná (IFPR), Universidade Federal do Paraná (UFPR), Universidade Tecnológica Federal do Paraná (UTFPR)
- Responsible party
- Principal investigator, Henrique Cunha Carvalho, Universidade Federal do Paraná
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07922265
- Sponsor's protocol ID
- 97426026.1.0000.0165
- Status last verified
- Nov 2026
- First submitted
- 2 Nov 2026
- Last updated
- 6 Nov 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Ethical or Consent Restrictions: Participants may not have given explicit consent for their data to be shared beyond the original study.Legal or Institutional Policies: Data sharing may be restricted by Brazillian laws.
Publications
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 15102499Karikari E, Koshechkin KA. Review on brain-computer interface technologies in healthcare. Biophys Rev. 2023 Sep 14;15(5):1351-1358. doi: 10.1007/s12551-023-01138-6. eCollection 2023 Oct.
PubMed 37974976Wang S, Tao X, Ma H, Li F, Wu C. EEG assessment of artificial intelligence-generated content impact on student creative performance and neurophysiological states in product design. Front Psychol. 2025 Jul 2;16:1508383. doi: 10.3389/fpsyg.2025.1508383. eCollection 2025.
PubMed 40678433Lotte F, Bougrain L, Cichocki A, Clerc M, Congedo M, Rakotomamonjy A, Yger F. A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update. J Neural Eng. 2018 Jun;15(3):031005. doi: 10.1088/1741-2552/aab2f2. Epub 2018 Feb 28.
PubMed 29488902Hernandez R, Roll SC, Jin H, Schneider S, Pyatak EA. Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) adapted for the whole day repeated measures context. Ergonomics. 2022 Jul;65(7):960-975. doi: 10.1080/00140139.2021.2006317. Epub 2021 Nov 22.
PubMed 34766872Arico P, Borghini G, Di Flumeri G, Sciaraffa N, Babiloni F. Passive BCI beyond the lab: current trends and future directions. Physiol Meas. 2018 Aug 29;39(8):08TR02. doi: 10.1088/1361-6579/aad57e.
PubMed 30039806
Study at a glance
From the registry record, last updated by the sponsor on 6 Nov 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Neuroergonomic Analysis of a Brain-Computer Interface (BCI) Device Based on EEG Signals and User Experience
- ClinicalTrials.gov ID
- NCT07922265
- Acronym / sponsor ID
- 97426026.1.0000.0165
- Conditions
- Healthy Volunteers - Male and Female
- Keywords
- Brain-Computer Interface, BCI, Electroencephalography, Mental Workload, Motor Imagery, NASA-TLX, UEQ, Human Factors
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- Universidade Federal do ParanáUniversity, hospital or other
- Collaborators
- Instituto Federal do Paraná (IFPR), Universidade Federal do Paraná (UFPR), Universidade Tecnológica Federal do Paraná (UTFPR)
- Study start
- 28 Dec 2026 (estimated)
- Primary completion
- 31 Mar 2027 (estimated)
- Study completion
- 31 Mar 2027 (estimated)
- First posted
- 6 Nov 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.
This study evaluates the mental workload and user experience associated with a Brain-Computer Interface (BCI) device called Exobots. The Exobots system uses a non-invasive electroencephalography (EEG) headset to detect neural signals and control a robotic glove that assists hand movement. The primary goal is to assess how three different system sensitivity levels (low, medium, high) impact mental effort, usability, and overall user perception. Healthy adult volunteers (students and staff from IFPR and UFPR) will participate in a single experimental session. During the session, they will perform a repeated mental imagery task (imagine hand movement) while the EEG records their brain activity. After each sensitivity block, participants will complete standardized questionnaires (NASA Task Load Index and User Experience Questionnaire) and a semi-structured qualitative interview about their experience. By combining objective neurophysiological data with subjective feedback, this research aims to identify optimal sensitivity thresholds that minimize cognitive strain and maximize user comfort. The findings are expected to provide technical recommendations for designing more adaptive, user-centered BCI systems for future neurorehabilitation applications.
Detailed description
Background and Rationale
Brain-Computer Interfaces (BCIs) are increasingly employed in neurorehabilitation settings to assist individuals with motor impairments. While these systems enable direct neural control of assistive devices, there is a significant gap in understanding the cognitive demands they impose on users. Excessive mental workload can lead to frustration, disengagement, and suboptimal therapeutic outcomes. This study addresses this gap by applying a neuroergonomic approach-integrating objective neurophysiological measures with subjective user experience (UX) assessments.
Objectives
Primary Objective: To evaluate cognitive load during interaction with the Exobots BCI device by integrating neurophysiological metrics (EEG), psychometric UX scores, and subjective user perceptions.
Secondary Objectives:
- To map neural activity patterns, focusing on theta, alpha, and beta frequency bands, during BCI interaction.
- To correlate neurophysiological indicators of mental effort with usability and UX measures obtained via the NASA-TLX and UEQ.
- To identify preliminary operational sensitivity threshold parameters established during individual device calibration.
- To analyze participants' subjective perceptions of the physical BCI interface using a semi-structured questionnaire with open-ended questions and visual cards.
- To formulate technical recommendations for BCI interface design based on the integrated analysis of neurophysiological, psychometric, and qualitative data.
Study Design
This is an interventional, single-group, experimental study without a control arm. All participants will undergo the same protocol, testing three distinct sensitivity levels (low, medium, high) in a within-subjects design, with the order of sensitivity levels counterbalanced to avoid order effects.
Study Population and Sample Size
Healthy adults (aged 18 years or older) who are students (undergraduate, graduate, technical level) or staff members from the Federal University of Paraná (UFPR) and the Federal Institute of Paraná (IFPR) will be recruited.
The minimum sample size was calculated using G*Power software (version 3.1.9.7) for a bivariate normal correlation model (Exact test, Family: Correlation). Considering an expected effect size of r = 0.50, a significance level of α = 0.05, and a statistical power of (1-β) = 0.80, the calculation indicated a minimum of 29 participants. To ensure statistical robustness and account for potential data loss due to EEG artifacts or voluntary dropouts, the target enrollment is set at 30 participants, with recruitment extended to up to 60 individuals if necessary.
Intervention and Procedures
Screening and Consent: Interested individuals will receive and sign the Informed Consent Form (TCLE). A screening questionnaire will be administered to verify inclusion/exclusion criteria (e.g., no neurological disorders, no recent head injuries).
Device and Preparation: Participants will interact with the Exobots device (provided by Neurobots). An elastic cap equipped with six dry/wet EEG electrodes will be placed on the participant's scalp. A water-based conductive gel will be applied to the contact points to ensure optimal signal quality. The robotic glove will be fitted to the participant's hand.
Calibration: The system will be calibrated to recognize each participant's specific neural patterns. Based on the calibration, three distinct sensitivity thresholds (low, medium, high) will be defined and tested individually.
Experimental Protocol: Each participant will complete a sequence of repeated cycles consisting of four sequential steps:
Prepare: The participant focuses attention on their hand in anticipation of the command.
Think: The participant imagines opening/closing their hand without physically executing the movement. The EEG system detects the motor imagery signal. If the signal is maintained above the predetermined threshold for three consecutive seconds, the robotic glove is activated.
Move: The robotic glove passively moves the participant's hand. The participant is instructed to voluntarily accompany this movement if possible.
Relax: The participant stops focusing and rests for a few seconds before the next cycle.
Each sensitivity level will be tested in blocks of approximately 10 minutes, totaling approximately 35 minutes of effective interaction per participant. Sessions will be scheduled in advance, with at least 48 hours' notice.
Outcome Measures
Neurophysiological: Continuous 6-channel EEG recording throughout the task. Spectral power analysis will focus on theta (4-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) bands, with particular emphasis on the theta/beta ratio as a validated marker of cognitive load.
Psychometric: Immediately after each sensitivity block, participants will complete the NASA Task Load Index (NASA-TLX) to assess perceived mental, physical, and temporal demands, effort, and frustration. At the end of the entire session, the User Experience Questionnaire (UEQ) will be administered to evaluate pragmatic and hedonic quality attributes.
Qualitative: A semi-structured interview with open-ended questions and thematic cards will be conducted to capture nuanced perceptions regarding the physical interface, comfort, and overall experience that standardized scales may not fully address.
Statistical Analysis
Pearson correlation coefficients will be calculated to assess the association between neurophysiological metrics (e.g., theta/beta ratio, alpha power) and UX scores (UEQ and NASA-TLX). A significance level of p < 0.05 will be adopted. Qualitative data will be analyzed using content analysis techniques to identify recurring themes and insights.
Ethical Considerations
The study protocol was reviewed and approved by the Research Ethics Committee of the Federal Technological University of Paraná (CEP/UTFPR) under Approval Number 8.558.948 (issued July 2, 2026; CAAE: 97426026.1.0000.0165). All procedures comply with Brazilian regulations (Resolution CNS 466/12 and LGPD - Lei Geral de Proteção de Dados).
Participants will be informed that no direct clinical benefits are expected, but that their participation will contribute to the scientific advancement of assistive technologies. Risks are minimal and include mild scalp discomfort from the EEG cap/gel, transient fatigue, or mild frustration. Participants may take breaks or withdraw at any time without penalty. All data will be anonymized, stored on a password-protected local hard drive, and kept confidential.
Data Monitoring Committee
A formal Data Monitoring Committee (DMC) will not be established, as this is a low-risk, non-clinical, academic study with healthy volunteers and no investigational drug or device under IDE regulations.
Study design
- Primary purpose
- Basic science
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- All participants are assigned to a single group and undergo the same experimental protocol. Each participant interacts with the Exobots BCI device across three distinct sensitivity levels (low, medium, high), presented in a counterbalanced order to minimize order effects. The intervention consists of motor imagery tasks with EEG recording and robotic glove assistance.
| Arm | Type | Receives |
|---|---|---|
| Exobots BCI Device | Experimental | Other: EEG-Based Brain-Computer Interface DeviceParticipants perform motor imagery tasks (imagining hand movements) while using the Exobots EEG-based BCI device. The system detects neural signals and activates a robotic glove to assist hand movement. Three distinct sensitivity thresholds (low, medium, high) are tested in a counterbalanced order within a single 35-minute experimental session. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Technical-level students, undergraduate students, graduate students, and staff members, of both sexes, healthy, affiliated with the Federal University of Paraná (UFPR) or the Federal Institute of Paraná (IFPR).
- Age 18 years or older.
Key exclusion criteria (7 listed)
- Use of psychoactive medications.
- History of epilepsy or other neurological conditions that would preclude the use of the device.
- Severe motor limitations that prevent interaction with the device.
- Recent traumatic brain injuries.
- Injury, dermatitis, or open wound on the scalp.
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 |
|---|---|---|
| EEG-Based Brain-Computer Interface DeviceAlso: Exobots BCI SystemNon-invasive electroencephalography (EEG)-based Brain-Computer Interface (BCI) system consisting of a 6-channel EEG headset and a robotic hand exoskeleton (glove). The device detects motor imagery neural signals associated with imagined hand movements. When the EEG signal is maintained above a predefined sensitivity threshold for three consecutive seconds, the system triggers the robotic glove to passively move the participant's hand. The study evaluates three distinct sensitivity levels (low, medium, high) during individual calibration. The EEG headset uses water-based conductive gel on contact points to ensure signal quality. The device is manufactured by Neurobots and provided for this research. | Other | Exobots BCI Device |
Primary outcome
EEG Theta/Beta Ratio as a Neurophysiological Marker of Cognitive Load
Time frame: Measured continuously during each 10-minute experimental block (blocks 1, 2, and 3) throughout the single 35-minute session.
Change in the theta/beta spectral power ratio derived from 6-channel electroencephalography (EEG) recordings during motor imagery (imagined hand movement) tasks. The theta/beta ratio is a validated neurophysiological indicator of cognitive workload and mental effort. This measure is compared across the three distinct device sensitivity levels (low, medium, high) to assess differences in cognitive demand.
4 secondary outcomes
NASA Task Load Index (NASA-TLX) Global Workload Score
Time frame: Immediately after each sensitivity block (3 times total) during the experimental session.
User Experience Questionnaire (UEQ) Scores
Time frame: At the end of the entire experimental session.
Qualitative Feedback on BCI Physical Interface and Overall Experience
Time frame: Immediately following the conclusion of the experimental session.
Individual Operational Sensitivity Thresholds
Time frame: During the calibration phase and across all three experimental blocks within the session.
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 6 Nov 2026.
- Background: PubMed 15102499Delorme 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.
- Background: PubMed 37974976Karikari E, Koshechkin KA. Review on brain-computer interface technologies in healthcare. Biophys Rev. 2023 Sep 14;15(5):1351-1358. doi: 10.1007/s12551-023-01138-6. eCollection 2023 Oct.
- Background: PubMed 40678433Wang S, Tao X, Ma H, Li F, Wu C. EEG assessment of artificial intelligence-generated content impact on student creative performance and neurophysiological states in product design. Front Psychol. 2025 Jul 2;16:1508383. doi: 10.3389/fpsyg.2025.1508383. eCollection 2025.
- Background: PubMed 29488902Lotte F, Bougrain L, Cichocki A, Clerc M, Congedo M, Rakotomamonjy A, Yger F. A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update. J Neural Eng. 2018 Jun;15(3):031005. doi: 10.1088/1741-2552/aab2f2. Epub 2018 Feb 28.
- Background: PubMed 34766872Hernandez R, Roll SC, Jin H, Schneider S, Pyatak EA. Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) adapted for the whole day repeated measures context. Ergonomics. 2022 Jul;65(7):960-975. doi: 10.1080/00140139.2021.2006317. Epub 2021 Nov 22.
- Background: PubMed 30039806Arico P, Borghini G, Di Flumeri G, Sciaraffa N, Babiloni F. Passive BCI beyond the lab: current trends and future directions. Physiol Meas. 2018 Aug 29;39(8):08TR02. doi: 10.1088/1361-6579/aad57e.
- Individual participant dataSharing planned: No. Ethical or Consent Restrictions: Participants may not have given explicit consent for their data to be shared beyond the original study.Legal or Institutional Policies: Data sharing may be restricted by Brazillian laws.
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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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing EEG-Based Brain-Computer Interface Device in people with Healthy Volunteers - Male and Female, run by Universidade Federal do Paraná at 2 sites in Brazil.
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 2 inclusion and 7 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: opening soon, as of the sponsor's last update on 6 Nov 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Brazil. 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?
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?
Contact Lucas T dos Santos Vieira (+55 041 998746-9352, lucastadeu1875@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
EEG Theta/Beta Ratio as a Neurophysiological Marker of Cognitive Load (time frame: Measured continuously during each 10-minute experimental block (blocks 1, 2, and 3) throughout the single 35-minute session.). 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 NCT07922265, which also lists 6 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 Nov 2026.