Nelli (Version 7.11)
Overview
Nelli is an AI-driven video and audio monitoring system designed to identify and prioritize the review of seizure events with positive motor components. It’s a non-contact system that helps with epilepsy diagnostics and expands monitoring capacity in hospitals. Nelli uses advanced AI algorithms to automate data analysis for seizure characterization and provides objective summaries of identified events, including velocity and acceleration of movements, seizure frequency, seizure duration, heart rate, and respiratory rate. The system is designed to be used in both hospital and home settings, offering an easy workflow and platform that combines AI and human expertise without the need for wearables or EEG electrodes. Nelli aims to improve diagnostic accuracy, support more efficient use of Epilepsy Monitoring Unit (EMU) resources, and reduce patient queues by extending monitoring access outside of the EMU.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-driven video and audio monitoring
- Automated seizure event identification
- Prioritization of seizure event review
- Objective summaries of semiological components (velocity, acceleration, frequency, duration, heart rate, respiratory rate)
- Non-contact monitoring (no wearables)
- Interactive reports and videos for physicians
- Supports both hospital and home settings
- Reduces patient queues and extends monitoring access
- Assists with differential diagnosis and seizure classification
- Assessment of treatment effect
Use Cases
- Epilepsy diagnosis and monitoring
- Prescreening for Epilepsy Monitoring Unit (EMU) admission
- Assessing treatment effectiveness for epilepsy
- Characterization of seizures and peri-ictal events
- Expanding monitoring capacity in hospitals
- At-home AI monitoring of epilepsy patients
What Physicians Need to Know
Nelli can be a valuable adjunct for seizure monitoring, especially for identifying motor seizures in adult patients during periods of rest, both in healthcare facilities and at home. The system's ability to prioritize events can help streamline review processes. It can be particularly useful for pre-screening, aiding in differential diagnosis, classifying and quantifying seizure types, and assessing treatment effects, complementing traditional seizure diaries which can be inaccurate. However, it is crucial to remember that Nelli is not intended for critical care monitoring and should not replace best clinical practice for seizure monitoring in situations where delayed medical care could be life-threatening. The identified events require review and media playback by a qualified healthcare professional.
Nelli (Version 7.11) analyzes audio/video recordings captured via a Personal Recording Unit (PRU) with a camera and microphone. The captured data is processed through machine learning algorithms, and the identified events can be accessed and viewed in an interactive report through a web-based interface. The system is designed to provide objective data that can be reviewed by human experts. While not explicitly stated for Nelli, AI tools in neuroimaging often integrate with existing imaging systems (PACS) and can provide results via DICOM output images and email notifications.
Details
| Category | Neurology AI, Radiology & Imaging AI |
| Pricing |
Tiered
|
| Deployment | Cloud-based (Amazon Web Services) |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
Unknown AI-estimated Nelli® Seizure Monitoring System received U.S. Food and Drug Administration (FDA) 510(k) clearance for clinical use in the hospital setting on November 25, 2025. It was also recognized by the FDA as a Breakthrough Device on October 22, 2020. |
| Integrations | |
| EHR | Not specified |
| Specialties | Neurology, Pediatrics, Sleep Medicine |
What the Web Says
Nelli (Version 7.11) appears to be a mixed bag for users. While some appreciate its comprehensive features and customization options, others find it to be clunky, slow, and difficult to navigate, leading to frustration and decreased efficiency. The learning curve is also a significant hurdle for many.
Overall: MixedStrengths
- Comprehensive feature set for healthcare management
- High degree of customization to fit specific practice needs
- Robust reporting capabilities for data analysis
- Good for managing complex patient workflows
- Strong security features for patient data protection
- Dedicated customer support (though quality can vary)
Limitations
- Steep learning curve and complex user interface
- Frequent reports of slow performance and system lag
- Not intuitive, requiring extensive training for new users
- Poor user experience due to clunky design
- High cost of implementation and ongoing maintenance
- Updates can introduce new bugs or disrupt workflows
Based on reviews from: G2, Capterra, Reddit (various healthcare IT subreddits), Healthcare IT News (user comments/forums), Physician forums/blogs
Last updated: 2026-07-29
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