(251 days)
Not Found
Yes
The device name itself, "REMI-AI Rapid Detection Module (REMI-AI RDM)", explicitly includes "AI". The description also mentions that the device "has been trained to recognize" seizure characteristics, which is a common characteristic of ML algorithms. Furthermore, the document includes sections detailing the training and test sets used, which are essential components of ML model development and validation.
No
The device is described as a "physiological signal monitor" that "does not make any diagnostic conclusion about the subject's condition" and "does not make any treatment or management recommendations." Its primary function is to provide notifications of potential electrographic seizures to qualified clinicians, who then exercise professional judgment. This indicates it is a diagnostic/monitoring tool, not one that directly treats or prevents a disease or condition.
No.
The "Intended Use" section explicitly states, "REMI-AI RDM does not make any diagnostic conclusion about the subject's condition and is intended as a physiological signal monitor."
No
The device is described as a "seizure detection module which is integrated into the REMI Remote EEG Monitoring System". While the module itself is software, it is explicitly part of a larger system that includes hardware (the REMI System and REMI wireless EEG sensors). The 510(k) summary describes the analysis of EEG data collected by these sensors, indicating a dependency on hardware components for data acquisition.
Based on the provided information, the REMI-AI Rapid Detection Module (REMI-AI RDM) is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the collection, preparation, and examination of specimens taken from the human body (such as blood, urine, or tissue) to provide information for the diagnosis, treatment, or prevention of disease.
- REMI-AI RDM Function: The REMI-AI RDM analyzes EEG data, which is a physiological signal recorded from the patient's scalp. It does not analyze specimens taken from the body.
- Intended Use: The intended use is to provide notifications of potential electrographic seizures based on the analysis of EEG data. It explicitly states that it "does not make any diagnostic conclusion about the subject's condition and is intended as a physiological signal monitor."
Therefore, the REMI-AI RDM falls under the category of a physiological monitoring device, not an In Vitro Diagnostic device.
Yes
The letter explicitly states, "The REMI-AI RDM has been cleared by the US FDA with an Authorized PCCP."
Intended Use / Indications for Use
The REMI-AI Rapid Detection Module (REMI-AI RDM) is a seizure detection module which is integrated into the REMI Remote EEG Monitoring System and is only indicated for use within non-ICU (Intensive Care Unit) healthcare settings. REMI-AI RDM has not been validated for and is not indicated for detection of electrographic status epilepticus.
REMI-AI RDM conducts automated analysis of REMI EEG data in near real-time and provides notifications of potential electrographic seizures (events) through the REMI System when seizure prevalence of 10% or greater (indicating seizure activity of at least 30 seconds within a 5-minute rolling window) is detected. When seizure prevalence is displayed, the notification also displays the corresponding event detection confidence. Notifications are intended to be used by qualified clinicians who will exercise professional judgment in their application. Detected events are also annotated in the associated REMI EEG record as an aide to the qualified physician's REMI EEG review.
Delays of up to several minutes may occur between the detection of an event and the generation of an event notification, and are thus not a substitute for real-time monitoring. REMI-AI RDM does not make any diagnostic conclusion about the subject's condition and is intended as a physiological signal monitor. REMI-AI RDM is indicated for use with adult and pediatric patients (6+ years).
Product codes (comma separated list FDA assigned to the subject device)
OMB
Device Description
REMI-AI RDM conducts automated analysis of EEG data collected by the REMI System in near real-time. REMI-AI RDM provides notifications of the prevalence and confidence of potential electrographic seizures, having a combined prevalence of 10% or greater, which correlates with a duration of at least 30 seconds of activity within a rolling 5 minute window of EEG.
REMI-AI RDM notifications are presented through the REMI Mobile software application, and are intended to be used by qualified clinicians who will exercise professional judgment in their interpretation. Notifications include the prevalence and confidence value for the event and are marked in the associated EEG record in order to assist qualified clinicians in their assessment.
REMI-AI RDM notifications identify when a section of EEG is consistent with seizure characteristics it has been trained to recognize. When a notification is presented, clinical context and facility procedures should inform next steps in patient evaluation and management. REMI-AI RDM does not make any treatment or management recommendations.
Delays of up to several minutes may occur between the start of an event, the detection of an event and the generation of an event notification, and are thus not a substitute for real-time monitoring.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
REMI-AI RDM conducts automated analysis of REMI EEG data in near real-time and provides notifications of potential electrographic seizures (events) through the REMI System when seizure prevalence of 10% or greater (indicating seizure activity of at least 30 seconds within a 5-minute rolling window) is detected.
The algorithm was tested against a clinical reference to ensure it meets clinical performance requirements
The algorithm ability to identify potential electrographic seizure events within an indicated patient population.
The REMI-AI RDM Authorized PCCP outlines authorized modifications intended to improve algorithm performance through expansion of the training data and/or through optimizations of the algorithm.
Input Imaging Modality
EEG data acquired from REMI Sensors placed on a patient's scalp. REMI Sensors are a component of the REMI Remote EEG Monitoring System.
Anatomical Site
Patient's scalp
Indicated Patient Age Range
Adult and pediatric patients (6+ years).
Intended User / Care Setting
Qualified clinicians who will exercise professional judgment in their application.
Non-ICU (Intensive Care Unit) healthcare settings.
Description of the training set, sample size, data source, and annotation protocol
EEG data from adult and pediatric patients was used to train the REMI-AI RDM algorithm to identify potential electrographic seizure events in a broad patient population.
Patients at these sites wore REMI wireless EEG sensors at bilateral frontal and temporoparietal scalp sites alongside standard-of-care 19-channel, full-montaqe, video-EEG for up to 7 continuous days in Epilepsy Monitoring Units (EMUs) or for up to 3 continuous days during at-home ambulatory EEG monitoring.
Training patient records: 117 total (82 seizure patients, 35 non-seizure patients).
Age demographics for training set:
Child ( 70% and of a False Alarm Rate (FAR) 70% (with a calculated 95% Cl lower bound of 78.9%) and FAR
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).
0
October 17, 2024
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Epitel, Inc Christopher Phillips VP. Regulatory Affairs and Ouality 465 S 400 E Suite 250 Salt Lake City, Utah 84111
Re: K240408
Trade/Device Name: REMI-AI Rapid Detection Module (REMI-AI RDM) Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OMB Dated: September 16, 2024 Received: September 17, 2024
Dear Christopher Phillips:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP). Under section 515C(b)(1) of the Act, a new premarket notification is not
1
required for a change to a device cleared under section 510(k) of the Act, if such change is consistent with an established PCCP granted pursuant to section 515C(b)(2) of the Act. Under 21 CFR 807.81(a)(3), a new premarket notification is required if there is a major change or modification in the intended use of a device, or if there is a change or modification in a device that could significantly affect the safety or effectiveness of the device, e.g., a significant change or modification in design, material, chemical composition, energy source, or manufacturing process. Accordingly, if deviations from the established PCCP result in a major change or modification in the intended use of the device, or result in a change or modification in the device that could significantly affect the safety or effectiveness of the a new premarket notification would be required consistent with section 515C(b)(1) of the Act and 21 CFR 807.81(a)(3). Failure to submit such a premarket submission would constitute adulteration and misbranding under sections 501(f)(1)(B) and 502(o) of the Act, respectively.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
2
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Jay R. Gupta -S
Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional, and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
3
Indications for Use
Submission Number (if known)
Device Name
REMI-AI Rapid Detection Module (REMI-AI RDM)
Indications for Use (Describe)
The REMI-AI Rapid Detection Module (REMI-AI RDM) is a seizure detection module which is integrated into the REMI Remote EEG Monitoring System and is only indicated for use within non-ICU (Intensive Care Unit) healthcare settings. REMI-AI RDM has not been validated for and is not indicated for detection of electrographic status epilepticus.
REMI-AI RDM conducts automated analysis of REMI EEG data in near real-time and provides notifications of potential electrographic seizures (events) through the REMI System when seizure prevalence of 10% or greater (indicating seizure activity of at least 30 seconds within a 5-minute rolling window) is detected. When seizure prevalence is displayed, the notification also displays the corresponding event detection confidence. Notifications are intended to be used by qualified clinicians who will exercise professional judgment in their application. Detected events are also annotated in the associated REMI EEG record as an aide to the qualified physician's REMI EEG review.
Delays of up to several minutes may occur between the detection of an event and the generation of an event notification, and are thus not a substitute for real-time monitoring. REMI-AI RDM does not make any diagnostic conclusion about the subject's condition and is intended as a physiological signal monitor. REMI-AI RDM is indicated for use with adult and pediatric patients (6+ years).
Type of Use (select one or both as applicable)
| ☑ Prescription Use (21 CFR 801 Subpart D) | |
|---|---|
| -- | -------------------------------------------------------- |
ver-The-Counter Use (21 CFR 801 Subpart C)
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REMI-AI Rapid Detection Module (REMI-AI RDM) 510(k) SUMMARY
1. Applicant Information
Epitel, Inc. 465 S 400 E, Suite 250 Salt Lake City, UT 84111
Contact Information
Christopher M. Phillips VP, Regulatory Affairs and Quality
Date Prepared
October 9, 2024
2. Subject Device Information
Name of Device: REMI-AI Rapid Detection Module (REMI-AI RDM) Common or Usual Name: EEG System Classification Name: Automatic Event Detection Software For Full-Montage Electroencephalograph Regulatory Class: Class II Product Code and Regulation Number: OMB - Sec. 882.1400
3. Predicate Devices
| Predicate Type | 510(k) Number | Name of Device | Name of Manufacturer |
|---|---|---|---|
| Primary Predicate | K191301 | Ceribell Pocket EEG | |
| Device | |||
| (Seizure Detection Module) | Ceribell, Inc. | ||
| Secondary Predicate | K231779 | REMI-AI Discrete Detection | |
| Module (RDM) | Epitel, Inc. |
4. Device Description
REMI-AI RDM conducts automated analysis of EEG data collected by the REMI System in near real-time. REMI-AI RDM provides notifications of the prevalence and confidence of potential electrographic seizures, having a combined prevalence of 10% or greater, which correlates with a duration of at least 30 seconds of activity within a rolling 5 minute window of EEG.
REMI-AI RDM notifications are presented through the REMI Mobile software application, and are intended to be used by qualified clinicians who will exercise professional judgment in their interpretation. Notifications include the prevalence and confidence value for the event and are marked in the associated EEG record in order to assist qualified clinicians in their assessment.
REMI-AI RDM notifications identify when a section of EEG is consistent with seizure characteristics it has been trained to recognize. When a notification is presented, clinical context and facility procedures should inform next steps in patient evaluation and management. REMI-AI RDM does not make any treatment or management recommendations.
5
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Delays of up to several minutes may occur between the start of an event, the detection of an event and the generation of an event notification, and are thus not a substitute for real-time monitoring.
5. Indications for Use
The REMI-AI Rapid Detection Module (REMI-AI RDM) is a seizure detection module which is intecrated into the REMI Remote EEG Monitoring System and is only indicated for use within non-ICU (Intensive Care Unit) healthcare settings. REMI-AI RDM has not been validated for and is not indicated for detection of electrographic status epilepticus.
REMI-AI RDM conducts automated analysis of REMI EEG data in near real-time and provides notifications of potential electrographic seizures (events) through the REMI System when seizure prevalence of 10% or greater (indicating seizure activity of at least 30 seconds within a 5-minute rolling window) is detected. When seizure prevalence is displayed. the notification also displays the corresponding event detection confidence. Notifications are intended to be used by qualified clinicians who will exercise professional judgment in their application. Detected events are also annotated in the associated REMI EEG record as an aide to the qualified physician's REMI EEG review.
Delays of up to several minutes may occur between the detection of an event and the generation of an event notification, and are thus not a substitute for real-time monitoring. REMI-Al RDM does not make any diagnostic conclusion about the subject's condition and is intended as a physiological signal monitor. REMI-AI RDM is indicated for use with adult and pediatric patients (6+ years).
6. Predicate Selection
In alignment with FDA Draft Guidance Best Practices for Selecting a Predicate Device to Support a Premarket Notification [510(k)] Submission - Draft Guidance for Industry and Food and Drug Administration Staff, appropriate predicate devices have been selected. Potential predicates were reviewed and the Ceribell Pocket EEG Seizure Detection module primary predicate device was selected as it meets or exceeds the expected safety and performance. does not have unmitigated user-related or design related safety issues, and is not associated with any design-related recalls. A secondary predicate was selected in the REMI-Al Discrete Detection Module as a secondary predicate in order to support some technological characteristics. The secondary predicate also meets or exceeds the expected safety and performance, does not have unmitigated user-related or design related safety issues, and is not associated with any design-related recalls.
7. Substantial Equivalence
REMI-AI RDM has been developed in compliance with applicable FDA requirements and guidance as well as with recognized standards. This submission includes required documentation and testing data demonstrating substantial equivalence of REMI-AI RDM to its predicate device. REMI-AI RDM has undergone Software Testing, Human Factors/Usability testing, and Clinical Validation which demonstrate that it is safe and effective for its intended use. Assessment of the technological characteristics, intended use, and conclusions drawn from the verification tests, presented in their respective sections of this submission, demonstrate that the device is as safe and effective as the leqally marketed predicate devices.
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7.1 Summary of Technological Characteristics and Substantial Equivalence to Predicate Devices
| Attribute | Subject Device
REMI-AI Rapid Detection Module | Primary Predicate Device
Ceribell Pocket EEG Device
(K191301) | Secondary Predicate Device
REMI-Al Discrete Detection Module
(K231779) |
|--------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Classification and
Regulation | Class II per 21 CFR 882.1400
Electroencephalograph | Class II per 21 CFR 882.1400
Electroencephalograph | Class II per 21 CFR 882.1400
Electroencephalograph |
| FDA Product
Code(s) | OMB - Automatic Event Detection
Software | OMB - Automatic Event Detection
Software
OMC - Reduced Montage System
GWQ - Full Montage System
GXY - Electrodes | OMB - Automatic Event Detection
Software |
| Intended Use | Analysis of EEG signal data for
detection of seizure events | Analysis of EEG signal data for
detection of seizure events | Analysis of EEG signal data for
detection of seizure events |
| Indications for Use | The REMI-AI Rapid Detection
Module (REMI-AI RDM) is a seizure
detection module which is
integrated into the REMI Remote
EEG Monitoring System and is only
indicated for use within non-ICU
(Intensive Care Unit) healthcare
settings. REMI-AI RDM has not
been validated for and is not
indicated for detection of
electrographic status epilepticus.
REMI-AI RDM conducts automated
analysis of REMI EEG data in near
real-time and provides notifications
of potential electrographic seizures
(events) through the REMI System
when seizure prevalence of 10% or
greater (indicating seizure activity of
at least 30 seconds within a 5-
minute rolling window) is detected.
When seizure prevalence is
displayed, the notification also
displays the corresponding event
detection confidence. Notifications
are intended to be used by qualified
clinicians who will exercise
professional judgment in their
application. Detected events are
also annotated in the associated
REMI EEG record as an aide to the
qualified physician's REMI EEG
review.Delays of up to several
minutes may occur between the
detection of an event and the
generation of an event notification,
and are thus not a substitute for
real-time monitoring. REMI-AI RDM
does not make any | The Ceribell Pocket EEG Device is
intended to record and store EEG
signals, and to present the EEG
signals in visual and audible
formats in real time. The visual and
audible signals assist trained
medical staff to make neurological
diagnoses. The Pocket EEG Device
is intended to be used in a
professional healthcare facility
environment.
Additionally, the EEG Recording
Viewer Software component of the
Pocket EEG Device incorporates a
Seizure Detection component that
is intended to mark previously
acquired sections of EEG
recordings in patients greater than
or equal to 18 years of age that
may correspond to electrographic
seizures in order to assist qualified
clinical practitioners in the
assessment of EEG traces. The
Seizure Detection component
provides notifications to the user
when detected seizure prevalence
is "Frequent," "Abundant," or
"Continuous," per the definitions of
the American Clinical
Neurophysiology Society Guideline
14. Notifications include an
on-screen display on the Pocket
EEG Device and the optional
sending of an e-mail message to a
clinician. Delays of up to several
minutes can occur between the
beginning of a seizure and when
the Seizure Detection notifications | The REMI-AI Discrete Detection
Module (REMI-AI DDM) is indicated
for the analysis of REMI
Remote EEG Monitoring System
electroencephalogram (EEG)
recordings.
REMI-AI DDM is
intended to be used by physicians
qualified to analyze and interpret
EEG who will exercise professional
judgment in using the information.
As an aide to the qualified
physician's REMI EEG review,
REMI-AI DDM marks previously
acquired sections of REMI EEG
that may correspond to neurological
events of interest indicative of
potential electrographic seizures
lasting at least 10 seconds in
duration. REMI-AI DDM is indicated
for use with adult and pediatric
patients (6+ years).
REMI-AI DDM does not mark REMI
EEG records in real time and does
not provide any diagnostic
conclusion about the patient's
condition to the user. |
| Attribute | Subject Device
REMI-AI Rapid Detection Module | Primary Predicate Device
Ceribell Pocket EEG Device
(K191301) | Secondary Predicate Device
REMI-AI Discrete Detection Module
(K231779) |
| | diagnostic conclusion about the
subject's condition and is intended
as a physiological signal monitor.
REMI-AI RDM is indicated for use
with adult and pediatric patients (6+
years). | will be shown to a user.
The Pocket EEG Device does not
provide any diagnostic conclusion
about the subject's condition and
Seizure Detection notifications
cannot be used as a substitute for
real time monitoring of the
underlying EEG by a trained expert. | |
| Seizure event
detection module | REMI-AI RDM is a seizure
detection module that analyzes the
last 5 minutes of EEG in a rolling
window and identifies seizure
events. | The Ceribell Pocket EEG seizure
detection module analyzes the last
5 minutes of EEG in a rolling
window and identifies seizure
events. | REMI-AI DDM detects
electrographic events in previously
acquired EEG data. |
| Seizure event
notifications | When a seizure event is detected, a
notification is generated. These
notifications are provided to the
REMI System (K230933) for
interoperable display on the REMI
Mobile software.
Notifications include identifying an
event that has been detected and
provides the prevalence values and
algorithm confidence.
Event notifications are also
annotated in the EEG record. | When a seizure event is detected, a
notification is generated. The
Seizure Detection module also
provides notifications of detected
seizure by displaying an on-screen
message on the Ceribell EEG
Recorder and the optional sending
of an email message | No notifications are generated |
| Seizure
prevalence | Seizure prevalence is calculated for
the 5-minute rolling window.
Notifications and annotations
include of:
• Prevalence values presented as
a percentage which can range
from 10% to 100%. | Seizure prevalence (defined as
seizure burden, or the percentage
of time epochs classified as
seizure) is calculated for the
5-minute rolling window.
Notifications and annotations
include of:
• Frequent seizure detected if
seizure burden is 10% (30
seconds or more)
• Abundant seizure if greater than
or equal to 50%
• Continuous if greater than or
equal to 90% | Seizure prevalence is not
calculated.
No seizure prevalence notifications
or annotations |
| Event confidence | Confidence is calculated for
detected events. Confidence is a
measure that the event is not a
false positive.
Notifications and annotations
includes of: | Event confidence is not calculated.
No event confidence included in
notifications or annotations | Confidence is calculated for
detected events. Confidence is a
measure that the event is not a
false positive.
No notifications are presented. |
| | • Event confidence presented as
Low, Moderate, High, or Very | | Annotations consist of:
• Event confidence presented as |
| Attribute | Subject Device
REMI-AI Rapid Detection Module | Primary Predicate Device
Ceribell Pocket EEG Device
(K191301) | Secondary Predicate Device
REMI-AI Discrete Detection Module
(K231779) |
| | High (along with corresponding
percentage ranges) | | Low, Moderate, High, or Very
High (along with corresponding
percentage ranges) |
| Time before
notifications may
be presented | Several minutes | Several minutes | Not applicable |
| Seizure event
review | REMI-AI RDM will annotate EEG
records to identify the detected
seizure event to aid in EEG review.
These events are provided to the
REMI System. | Ceribell EEG Portal includes a
seizure detection module that will
mark EEG records to identify the
detected seizure event to aid in
EEG review. | REMI-AI DDM will annotate EEG
records to identify the detected
seizure event to aid in EEG review.
These events are provided to the
REMI System. |
| | The REMI System stores EEG
records in a standard EEG format
for viewing in a qualified EEG
viewing software. | | The REMI System stores EEG
records in a standard EEG format
for viewing in a qualified EEG
viewing software. |
| Use environment | The REMI-AI RDM is indicated for
use in non-ICU (Intensive Care
Unit) healthcare settings. | Ceribell Pocket EEG is used in a
professional healthcare facility
environment. | The REMI-AI DDM is indicated for
use in healthcare or ambulatory
settings. |
| Software/ system
user interface | The REMI-AI RDM produces
notifications and annotations that
are provided to the REMI System
(K230933) in an interoperable way. | Pocket EEG Device EEG
Recording Viewer software | The REMI-AI DDM produces
annotations that are provided to the
REMI System (K230933) in an
interoperable way. |
| | The REMI System was cleared with
the ability to conduct interoperable
communications for transfer of EEG
data for the purpose of analysis
modules and receive the outputs of
any such analysis. | | The REMI System was cleared with
the ability to conduct interoperable
communications for transfer of EEG
data for the purpose of analysis
modules and receive the outputs of
any such analysis. |
| | The REMI System displays this
information through the REMI
Mobile medical application, and
provides the RDM outputs as
annotations in the EEG record. | | The REMI System provides the
DDM outputs as annotations in the
EEG record. |
| Algorithm inputs | EEG data acquired from REMI
Sensors placed on a patient's scalp.
REMI Sensors are a component of
the REMI Remote EEG Monitoring
System. | EEG acquired from a Ceribell EEG
headband placed on a patient's
scalp. The sensor band is another
component of the Ceribell Pocket
EEG system | EEG data acquired from REMI
Sensors placed on a patient's scalp.
REMI Sensors are a component of
the REMI Remote EEG Monitoring
System. |
| Data format
(viewer software) | Common EEG data formats(e.g.
lay-dat) viewable in qualified EEG
viewing software | Format is not publicly available.
Data is viewable in the Ceribell
EEG Portal viewing software | Common EEG data formats(e.g.
lay-dat) viewable in qualified EEG
viewing software |
| Clinical validation | Demonstrated through statistical
analysis of clinical data | Demonstrated through statistical
analysis of clinical data | Demonstrated through statistical
analysis of clinical data |
| Attribute | Subject Device
REMI-AI Rapid Detection Module | Primary Predicate Device
Ceribell Pocket EEG Device
(K191301) | Secondary Predicate Device
REMI-Al Discrete Detection Module
(K231779) |
| Predetermined
Change Control
Plan (PCCP) | PCCP included in submission | N/A | Authorized PCCP |
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8. Performance Data
REMI-AI RDM was tested to verify its design and to validate its safe and effective use for the intended population and use environments. Results of this testing, included in this premarket. notification, support a determination of substantial equivalence. Testing included the following:
| Test Type | Summary |
|---|---|
| Software Verification | Software verification testing was conducted to ensure software meets |
| specified requirements. Interoperability verification testing was conducted to | |
| ensure interoperability of REMI-AI RDM with the REMI Remote EEG | |
| Monitoring System and to ensure wireless quality of service. | |
| Clinical Validation | The algorithm was tested against a clinical reference to ensure it meets |
| clinical performance requirements (as outlined in Section 11, Clinical | |
| Validation) | |
| Human Factors Validation for | |
| REMI-AI RDM outputs | REMI-AI RDM EEG notification outputs were evaluated by representative |
| clinicians reviewers to validate usability | |
| REMI-AI RDM EEG annotation outputs were evaluated by representative | |
| epileptologist reviewers to validate usability |
REMI-AI RDM met all predetermined acceptance criteria derived from the above listed tests and demonstrated substantially equivalent performance as compared with the predicate devices.
9. Clinical Study
EEG data from adult and pediatric patients was used to 1) train the REMI-AI RDM algorithm to identify potential electrographic seizure events in a broad patient population, and 2) validate the REMI-AI RDM algorithm ability to identify potential electrographic seizure events within an indicated patient population.
Patients at these sites wore REMI wireless EEG sensors at bilateral frontal and temporoparietal scalp sites alongside standard-of-care 19-channel, full-montaqe, video-EEG for up to 7 continuous days in Epilepsy Monitoring Units (EMUs) or for up to 3 continuous days during at-home ambulatory EEG monitoring.
The REMI-AI RDM validation data set consisted of 22 patient records with 54 consensus-determined electrographic seizures lasting at least 30 seconds in duration, and 22 patient records with no consensus-determined electrographic seizures, for a total validation sample size of 44. All attempts were made to ensure diverse patient demographics. The consensus-determined electrographic seizures represented in the validation data set include:
- Focal Seizures
- Focal Evolving To Generalized Seizures
- Generalized Seizures ●
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10. Clinical Reference
EEG data used to generate a reference standard for REMI-AI RDM was collected from standard 19+channel wired 10-20 montage EEG records acquired concurrently with REMI 4-channel EEG. Prior to inclusion in the validation data set, all patients' EEG records underwent panel review by 3 independent expert epileptologists. Experts consisted of a panel of 6 epileptologists, holding certification by the American Board of Psychiatry and Neurology or certification by the American Board of Clinical Neurophysiology with Special Competency in Epilepsy Monitoring. Consensus ground truth electrographic seizure negative determinations were made using the wired EEG records when at least 2 of 3 members identified the presence or absence of an electrographic seizure event.
Training and Clinical Reference Data Overview
Demographics by age are presented in Table 10.1 below.
| Age | Train | Train Sz | Train No-Sz | Test | Test Sz | Test No-Sz |
|---|---|---|---|---|---|---|
| Child (≤21) | 47 (40%) | 32 (39%) | 15 (43%) | 21 (48%) | 11 (50%) | 10 (45%) |
| Adult (22+) | 70 (60%) | 50 (61%) | 20 (57%) | 23 (52%) | 11 (50%) | 12 (55%) |
| Total | 117 | 82 | 35 | 44 | 22 | 22 |
Table 10.1. Demographics By Age. Train is the set of patient records used to train the algorithm and Test is the set of patient records used in this validation analysis. (Sz: Seizure Patients, No-Sz: Non-Seizure Patients)
| Gender | Train | Train Sz | Train No-Sz | Test | Test Sz | Test No-Sz |
|---|---|---|---|---|---|---|
| Male | 53 (45%) | 40 (49%) | 13 (37%) | 21 (48%) | 11 (50%) | 10 (45%) |
| Female | 64 (55%) | 42 (51%) | 22 (63%) | 23 (52%) | 11 (50%) | 12 (55%) |
| Total | 117 | 82 | 35 | 44 | 22 | 22 |
Demographics by gender are presented in Table 10.2 below.
Table 10.2. Demographics by Gender. Train is the set of patient records used to train the algorithm and Test is the set of patient records used in this validation analysis. (Sz: Seizure Patients, No-Sz: Non-Seizure Patients)
A summary of electrographic seizure types included in REMI-AI RDM training and validation is presented in Table 10.3 below.
| Seizure Type | Train | Test |
|---|---|---|
| Focal | 257 (47%) | 17 (31%) |
| Focal Evolving To Generalized | 45 (8%) | 21 (39%) |
| Generalized | 243 (45%) | 16 (30%) |
| Total | 545 | 54 |
Table 10.3. Electrographic Seizure Type Count. Train is the set of patient records used to train the alqorithm and Test is the set of patient records used in this validation analysis.
A summary of the duration of seizure record data, broken down by electrographic seizure type, is presented in Table 10.4 below.
| Focal | Focal Evolving To Generalized | Generalized | ||||
|---|---|---|---|---|---|---|
| Duration (s) | Train | Test | Train | Test | Train | Test |
| 70% and of a False Alarm Rate (FAR) 70% (with a calculated 95% Cl lower bound of 78.9%) and FAR |