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The EpiWatch Monitoring System is a prescription, software-only mobile medical application intended for use with a compatible wrist-worn device as an adjunct to seizure monitoring of adults and children ages 5 and up in home or healthcare settings during periods of rest.

The EpiWatch Monitoring System continuously records, stores, displays, and transfers data from the compatible wristworn device's built-in physiological-based sensors to support review by healthcare professionals, and people with epilepsy (PWE) or at risk of epilepsy.

When the EpiWatch Monitoring System detects and logs physiological patterns associated with generalized tonic-clonic seizures (TCS), the EpiWatch Monitoring System application alerts the identified caregiver(s) to notify of detected possible seizure events.

The EpiWatch Monitoring System is a non-electroencephalogram (non-EEG) physiological signalbased seizure monitoring system. It is similar to other legally-marketated non-electroencephalogram (non-EEG) physiological signal-based seizure monitoring systems.

The EpiWatch Monitoring System consists of a software-only mobile medical application intended for use with a compatible wrist-worn device as an adjunct to seizure monitoring of adults and children ages 5 and up.

EpiWatch Monitoring System is a software platform composed of:

• A compatible wrist-worn device, (e.g. an Apple Watch)
• A mobile application running on smartphones called the "EpiWatch Monitoring System . App".

The wrist-worn device continuously collects raw data via specific sensors, and feeds consolidated physiological data to the EpiWatch app via APIs. Utilizing a proprietary algorithm, EpiWatch analyzes and assesses the physiological data and determines if there is suspected generalized tonicclonic seizure activity (TCS). The EpiWatch algorithm has been validated through testing, using the gold-standard video electroencephalogram (vEEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, of epilepsy patients experiencing TCSs in hospital Epilepsy Monitoring Units.

When a likely TCS is detected, the EpiWatch Monitoring System App communicates to the EpiWatch Cloud which initiates, through an external provider, a voice call, email and an SMS text message (notification parameters are set by the user at contact setup) to summon the attention of caregiver(s).

In addition to initiating alerts, the EpiWatch app also continuously receives all the sensor data collected by the wrist worn device. The EpiWatch App is also responsible for transmitting-over a cellular data plan or Wi-Fi connection-the API data, device information, and computed physiological parameters to the EpiWatch Cloud for further review and storage, which allows seizure reports and other features added to alerting. It also provides necessary information about the state of the system.

Here's a detailed breakdown of the EpiWatch Monitoring System's acceptance criteria and the study proving it, based on the provided document:

Acceptance Criteria and Device Performance

Note: The document only provides the reported device performance and does not explicitly state pre-defined acceptance criteria values for these metrics. However, these reported values are used as the basis for the substantial equivalence claim. The corrected PPA values are applied to account for extreme probability values and multiple seizures per patient, using the method of Saha et al. (2016).

Study Details

Based on the provided document, here's the information about the study that proves the device meets the acceptance criteria:

1. Sample size used for the test set and the data provenance:

   • Test Set Size: 242 subjects, with a total of 16,189 hours of study monitoring.
   • Data Provenance: The study was conducted in Epilepsy Monitoring Units (EMU) at six geographically diverse trial sites. The patients were in-patients experiencing TCSs. This suggests a prospective collection of data within a controlled clinical environment in the United States (implied by FDA submission and diverse trial sites without specifying other countries).
   • Exclusions: EMU patients with Lennox-Gastaut syndrome or Rett syndrome were excluded from analysis.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: Not explicitly stated, but the ground truth was "confirmed by the central panel" which was "designed by a group of epileptologists at a top level 4 epilepsy center."
   • Qualifications of Experts: Group of epileptologists at a top level 4 epilepsy center. General qualifications for "epileptologists" include specialized training and expertise in epilepsy. "Top level 4 epilepsy center" implies they are highly qualified and recognized in the field.

3. Adjudication method for the test set:

   • The ground truth was "confirmed by the central panel" and was based on "the gold-standard video electroencephalogram (vEEG) methodology." The specific adjudication method (e.g., 2+1, 3+1) used by the central panel is not explicitly stated.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, a MRMC comparative effectiveness study was not explicitly mentioned as being performed to compare human readers' performance with and without AI assistance. The study focuses on the standalone performance of the EpiWatch algorithm.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

   • Yes, a standalone study was performed. The clinical study "evaluate[d] the performance of the EpiWatch algorithm for detecting TCSs," indicating it assessed the algorithm's performance independent of human-in-the-loop assistance for detection. The alerts are sent to caregivers, but the detection itself is algorithm-driven.

6. The type of ground truth used:

   • Expert Consensus and Pathology (vEEG): The ground truth was established by a "central panel" using "gold-standard video electroencephalogram (vEEG) methodology." vEEG is a clinical gold standard for diagnosing and classifying seizures, providing both electrophysiological and behavioral (video) evidence, which can be interpreted by experts to confirm seizure events. This falls under both expert consensus and a form of diagnostic/pathological evidence.

7. The sample size for the training set:

   • The document does not specify the sample size used for the training set. It only details the clinical study performed for performance evaluation (test set).

8. How the ground truth for the training set was established:

   • As the training set size is not provided, the method for establishing its ground truth is also not specified in this document. However, given the nature of the device, it would likely involve similar methodologies (e.g., vEEG interpreted by epileptologists), but this is not explicitly stated.

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