EpilepsyNCT06705439
A Study of Detection of Paroxysmal Events Utilizing Computer Vision and Machine Learning (USF)
An observational study of Epilepsy, run by Neuro Event Labs Inc. at 1 site in United States.
Trial summary
Increased computational power has made it possible to implement complex image recognition tasks and machine learning to be implemented in every day usage. The computer vision and machine learning based solution used in this project (Nelli) is an automatic seizure detection and reporting method that has a CE mark for… Read more about this study
- Who is it for?
- Ages 18 to 99 years
- Conditions the study is for
- Epilepsy
- What is being tested?
- Nelli
- Type of treatment
- Medical device
- How many people
- 33 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Nov 2024to 31 Jan 2026
- Phase
- Observational
- 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 18 to 99 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with suspected motor seizures that are undergoing video-EEG monitoring for routine clinical care.
Who may be able to join
- All patients undergoing video-EEG monitoring for clinical purposes who are suspected of having seizures.
Who cannot join
- -
Trial locations and contacts
1 site in 1 country.
About this study
Increased computational power has made it possible to implement complex image recognition tasks and machine learning to be implemented in every day usage. The computer vision and machine learning based solution used in this project (Nelli) is an automatic seizure detection and reporting method that has a CE mark for this specific use.
The present study will provide data to expand the utility and detection capability of NELLI and enhance the accuracy and clinical utility of automated computer vision and machine learning based seizure detection.
Read the detailed description
This is a prospective, blind comparison to the clinical gold standard for seizure characterization. This study is intended to compare the Nelli Software's ability to identify seizure events to vEEG review in adults with suspected nighttime seizures. Simultaneously, Nelli will continuously record audio and video while video-electroencephalography (vEEG) is recorded per typical standard of care. Events with positive motor manifestations will be independently identified, following standard clinical practice, by three epileptologists using clinical vEEG data. Nelli Software will review the audio and video data and independently identify events with positive motor manifestations. The outcomes of event identification will be compared between Epileptologists and the Nelli Software. For each category of event captured the positive percent agreement will be calculated using the exact binomial method. The primary endpoint of this study is to demonstrate that Nelli is able to identify seizures that have a positive motor component with a sensitivity of > 70%.
- Conditions
- Epilepsy
- Being tested
- Nelli
- Keywords
- Nelli
- Medical subject headings
- Epilepsy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
NelliDevice
Nelli detects and registers activity that is indicative of seizure events. Nelli captures, stores, and processes video and audio recordings from each patient. Biomarker data is collected during periods of rest for the length of an examination period, which may span several days or months (when used inside and outside of a hospital setting, respectively), as prescribed by a treating physician.
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity of a seizure detection system
The primary outcome measure will be the sensitivity of the Nelli system to detect seizrues with a positive motor component in comparison to independent Neurologist review of vEEG collected in an epilepsy monitoring unit. This is a blinded comparison to the clinical gold standard (vEEG)
Measured: During routine seizure monitoring in the hospital - up to one week
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Nov 2024
- Study start15 Nov 2024
- Primary completion31 Dec 2025
- Study completion31 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for EpilepsyStudies 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
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 33 participants (actual)
Sponsor and investigators
- Lead sponsor
- Neuro Event Labs Inc.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Selim Benbadis, MD, Principal investigator, University of South Florida
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06705439
- Sponsor's protocol ID
- STUDY005226
- Status last verified
- Feb 2026
- First submitted
- 22 Nov 2024
- Last updated
- 13 Feb 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Study of Detection of Paroxysmal Events Utilizing Computer Vision and Machine Learning (USF)
- ClinicalTrials.gov ID
- NCT06705439
- Acronym / sponsor ID
- STUDY005226
- Conditions
- Epilepsy
- Keywords
- Nelli
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 33 participants (actual)
- Lead sponsor
- Neuro Event Labs Inc.Industry (pharma, biotech, devices)
- Study start
- 15 Nov 2024 (actual)
- Primary completion
- 31 Dec 2025 (actual)
- Study completion
- 31 Jan 2026 (actual)
- First posted
- 26 Nov 2024 (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.
Increased computational power has made it possible to implement complex image recognition tasks and machine learning to be implemented in every day usage. The computer vision and machine learning based solution used in this project (Nelli) is an automatic seizure detection and reporting method that has a CE mark for this specific use.
The present study will provide data to expand the utility and detection capability of NELLI and enhance the accuracy and clinical utility of automated computer vision and machine learning based seizure detection.
Detailed description
This is a prospective, blind comparison to the clinical gold standard for seizure characterization. This study is intended to compare the Nelli Software's ability to identify seizure events to vEEG review in adults with suspected nighttime seizures. Simultaneously, Nelli will continuously record audio and video while video-electroencephalography (vEEG) is recorded per typical standard of care. Events with positive motor manifestations will be independently identified, following standard clinical practice, by three epileptologists using clinical vEEG data. Nelli Software will review the audio and video data and independently identify events with positive motor manifestations. The outcomes of event identification will be compared between Epileptologists and the Nelli Software. For each category of event captured the positive percent agreement will be calculated using the exact binomial method. The primary endpoint of this study is to demonstrate that Nelli is able to identify seizures that have a positive motor component with a sensitivity of > 70%.
Study design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 99 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with suspected motor seizures that are undergoing video-EEG monitoring for routine clinical care.
Key inclusion criteria (1 listed)
- All patients undergoing video-EEG monitoring for clinical purposes who are suspected of having seizures.
Key exclusion criteria (1 listed)
- -
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 |
|---|---|---|
| NelliNelli detects and registers activity that is indicative of seizure events. Nelli captures, stores, and processes video and audio recordings from each patient. Biomarker data is collected during periods of rest for the length of an examination period, which may span several days or months (when used inside and outside of a hospital setting, respectively), as prescribed by a treating physician. | Device | – |
Primary outcome
Sensitivity of a seizure detection system
Time frame: During routine seizure monitoring in the hospital - up to one week
The primary outcome measure will be the sensitivity of the Nelli system to detect seizrues with a positive motor component in comparison to independent Neurologist review of vEEG collected in an epilepsy monitoring unit. This is a blinded comparison to the clinical gold standard (vEEG)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Feb 2026.
- Individual participant dataSharing planned: No
Related trials for Epilepsy
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Study Evaluating the Efficacy and Safety of RAP-219 in Adult Participants With Focal Seizures FOCUS-1
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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. This study is not recruiting at the moment.
Selim Benbadis, MD principal investigator
University of South Florida
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Epilepsy, run by Neuro Event Labs Inc. at 1 site in United States.
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: finished, as of the sponsor's last update on 13 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 United States. 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?
Sensitivity of a seizure detection system (time frame: During routine seizure monitoring in the hospital - up to one week). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 13 Feb 2026.