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EpiMonitor is a prescription only medical device system composed of a wearable device "EmbracePlus" and paired mobile software application "EpiMonitor" intended as an adjunct to seizure monitoring in adults and children aged 6 and up in a home environment or healthcare facilities. The device is worn on the wrist and senses Electrodermal Activity (EDA) and motion data to detect patterns that may be associated with either primary or secondary generalized tonic clonic seizures in patients with epilepsy or at risk of having epilepsy. When a seizure event is detected, the wearable device component of EpiMonitor sends a command to a paired mobile device where the EpiMonitor App is programmed to initiate an alert to a designated caregiver. The EpiMonitor app incorporates additional detection sensitivity modes, "high" for use during periods of rest or sleeping or "low" for use during periods of low-intensity activity, in order to reduce false alarm incidents.

EpiMonitor records, stores and transmits accelerometer, EDA, peripheral skin temperature and activity data for subsequent retrospective review by a trained healthcare professional via a cloud-based software.

The EpiMonitor system consists of a wearable device and mobile application:

• A wearable medical device called EmbracePlus,
• A mobile application running on smartphones called "EpiMonitor"

The EmbracePlus is worn on the user's wrist and continuously collects raw data via specific sensors, these data are continuously analyzed by an on-board algorithm (EpiAlgo 2.1), which assesses the physiological data and determines if the user may be undergoing a generalized tonic-clonic seizure (GTCS). The EpiAlgo has been validated through testing, using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units.

When a likely GTCS is detected, EmbracePlus sends, via Bluetooth Low Energy, a message to the EpiMonitor app. The EpiMonitor app communicates to the Empatica Cloud which initiates, through the external provider a voice call and SMS text message is sent to summon the attention of user-designated caregiver(s).

In addition to initiating alerts, the EpiMonitor app also continuously receives all the raw sensor data collected by the EmbracePlus. These data are analyzed by one of the EpiMonitor app software modules, EmpaDSP (paragraph 2.3.2), which computes the additional physiological parameters, such as activity during sleep and peripheral skin temperature.

The EpiMonitor App is also responsible for transmitting, over a cellular data plan or Wi-Fi connection the sensors' raw data, device information, and computed physiological parameters to the Empatica Cloud. On the Empatica Cloud, these data are stored, and made available to healthcare providers via a specific cloud-based software called Care Monitoring Portal.

Here's a summary of the acceptance criteria and study details for EpiMonitor, based on the provided FDA clearance letter:

Acceptance Criteria and Device Performance for EpiMonitor

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state "acceptance criteria" for PPA and FAR in a table format. Instead, it presents the device's performance for these metrics, implying that these results were deemed acceptable by the FDA for clearance. For the purpose of this response, I'm interpreting the "reported device performance" as the achieved PPA and FAR values and will frame the "acceptance criteria" as the expectation for these metrics to be within reasonable clinical utility.

2. Sample Size for the Test Set and Data Provenance:

• Epilepsy Monitoring Unit (EMU) Data (Retrospective Analysis):

  • Patients for PPA: 12 patients (6-21 years old) and 12 patients (>21 years old).
  • GTCS events for PPA: 19 GTCS events (6-21 years old) and 17 GTCS events (>21 years old).
  • Patients for FAR: 80 patients (6-21 years old) and 61 patients (>21 years old).
  • Data Provenance: Retrospective analysis of previously collected clinical data from patients observed in Epilepsy Monitoring Units. The document mentions data from "epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units" for the validation of the algorithm (EpiAlgo 2.1).

• Real-World Data (Longitudinal Analysis) for Low-Sensitivity Mode:

  • Patients for PPA/FAR: 601 patients (6-21 years old) and 843 patients (>21 years old).
  • GTCS events for PPA: 1157 GTCS events (6-21 years old) and 3625 GTCS events (>21 years old).
  • Observation days for FAR: 37594.2 days (6-21 years old) and 56389.1 days (>21 years old).
  • Data Provenance: Longitudinal analysis of real-world data, based on sensor data captured using the Embrace2 wearable device. This suggests the data was collected prospectively in a real-world setting, but its analysis for this specific submission was retrospective.

3. Number of Experts Used to Establish the Ground Truth and Qualifications:

• For the initial validation of EpiAlgo 2.1 (which supports the predicate device and is used in the subject device), the ground truth was "designed by a group of epileptologists at a top level 4 epilepsy center." The exact number of epileptologists and their specific years of experience are not provided. The method mentioned is "gold-standard video-Electroencephalogram (EEG) methodology."
• For the retrospective analyses presented, "adjudicated tonic-clonic seizure data" was used, implying expert review to establish the ground truth of GTCS events. The number and qualifications of the experts performing this adjudication for the analyses presented in Tables 1-4 are not explicitly stated.

4. Adjudication Method for the Test Set:

• The document implies clinical adjudication was performed to establish "adjudicated tonic-clonic seizure data" and the "gold-standard video-Electroencephalogram (EEG) methodology." However, it does not specify a particular adjudication method such as 2+1 or 3+1 for the test set data used in these retrospective analyses. It only mentions that the data was "adjudicated."

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No MRMC comparative effectiveness study was done.
• The document describes a standalone algorithm performance without human assistance for seizure detection.

6. Standalone (Algorithm Only) Performance:

• Yes, a standalone performance evaluation of the algorithm (EpiAlgo ver 2.1) was conducted. The PPA and FAR metrics presented (Tables 1-4) reflect the performance of the algorithm without human-in-the-loop assistance for seizure detection and alerting.

7. Type of Ground Truth Used:

• Expert Consensus / Clinical Diagnosis (Video-EEG): For the initial validation of EpiAlgo 2.1, the ground truth was established using "gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists." This indicates a high standard of clinical diagnosis and expert consensus.
• Adjudicated Data: For the retrospective analyses of EMU and real-world data, "adjudicated tonic-clonic seizure data" were used, implying expert review and decision-making on seizure events.

8. Sample Size for the Training Set:

• The document does not explicitly state the sample size for the training set of EpiAlgo ver 2.1. It mentions that EpiAlgo 2.1 was validated using data from epilepsy patients in EMUs, but this typically refers to validation/test sets, not specifically the training data.

9. How the Ground Truth for the Training Set Was Established:

• The method for establishing the ground truth for the training set is not detailed in this document. It only states that the EpiAlgo "has been validated through testing, using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units." This description primarily refers to the validation data, not the data used for initial training.

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EpiMonitor is a prescription only medical device system composed of a wearable device "EmbracePlus" and paired mobile software application "EpiMonitor" intended as an adjunct to seizure monitoring in adults and children aged 6 and up in a home environment or healthcare facilities. The device is worn on the wrist and senses Electrodermal Activity (EDA) and motion data to detect patterns that may be associated with either primary or secondary generalized tonic clonic clonic clonic seizures in patients with epilepsy or at risk of having epilepsy. When a seizure event is detected, the wearable device component of EpiMonitor sends a command to a paired mobile device where the EpiMonitor App is programmed to initiate an alert to a designated caregiver. The EpiMonitor app incorporates additional detection sensitivity modes, "high" for use during periods of rest or sleeping or "low" for use during periods of low-intensity activity, in order to reduce false alarm incidents.

EpiMonitor records, stores and transmits accelerometer. EDA, peripheral skin temperature and activity data for subsequent retrospective review by a trained healthcare professional via a cloud-based software.

The EpiMonitor system consists of a wearable device and mobile application:

• A wearable medical device called EmbracePlus,
• A mobile application running on smartphones called "EpiMonitor"

The EmbracePlus is worn on the user's wrist and continuously collects raw data via specific sensors, these data are continuously analyzed by an on-board algorithm (EpiAlgo 2.1), which assesses the physiological data and determines if the user may be undergoing a generalized tonic-clonic seizure (GTCS). The EpiAlgo has been validated through testing, using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units. When a likely GTCS is detected, EmbracePlus sends, via Bluetooth Low Energy, a message to the EpiMonitor app. The EpiMonitor app communicates to the Empatica Cloud which initiates, through the external provider a voice call and SMS text message is sent to summon the attention of userdesignated caregiver(s).

In addition to initiating alerts, the EpiMonitor app also continuously receives all the raw sensor data collected by the EmbracePlus. These data are analyzed by one of the EpiMonitor app software modules, EmpaDSP (paragraph 2.3.2), which computes the additional physiological parameters, such as activity during sleep and peripheral skin temperature.

The EpiMonitor App is also responsible for transmitting, over a cellular data plan or Wi-Fi connection the sensors' raw data, device information, and computed physiological parameters to the Empatica Cloud. On the Empatica Cloud, these data are stored, and made available to healthcare providers via a specific cloud-based software called Care Monitoring Portal.

Here's a breakdown of the acceptance criteria and study details for the EpiMonitor device, derived from the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the EpiMonitor device's Low-Sensitivity mode were evaluated based on Positive Percent Agreement (PPA) for seizure detection and False Alarm Rate (FAR) for both Epilepsy Monitoring Unit (EMU) data and real-world data.

Note: The document explicitly states "Analysis of performance for the Low-Sensitivity alerting mode in the EpiMonitor system demonstrated acceptable seizure detection accuracy and a reduced rate of false alerts." This implies that the reported performance met the sponsor's internal acceptance criteria for these metrics. Specific numerical thresholds for "acceptable" are not explicitly stated within the provided text.

2. Sample Sizes Used for the Test Set and Data Provenance

For Epilepsy Monitoring Unit (EMU) Data (Retrospective Analysis):

• Seizure Detection (PPA):
  • Patients: 24 (12 for age 6-21, 12 for age >21)
  • GTCS events: 36 (19 for age 6-21, 17 for age >21)
• False Alarm Rate (FAR):
  • Patients: 141 (80 for age 6-21, 61 for age >21)
  • Days of monitoring: 241.62 (88.94 for age 6-21, 152.68 for age >21)
• Data Provenance: The data was collected from patients observed in Epilepsy Monitoring Units. The exact geographic origin (country) is not specified, but the data was from "a top level 4 epilepsy center" (mentioned in device description for original EpiAlgo validation). This was a retrospective analysis of previously collected clinical data.

For Real-World Data (Longitudinal Analysis) - based on Embrace2 wearable device:

• Seizure Detection (PPA):
  • Patients: 1444 (601 for age 6-21, 843 for age >21)
  • GTCS events: 4782 (1157 for age 6-21, 3625 for age >21)
• False Alarm Rate (FAR):
  • Patients: 1444 (601 for age 6-21, 843 for age >21)
  • Days of monitoring: 93983.3 (37594.2 for age 6-21, 56389.1 for age >21)
• Data Provenance: "real-world data" captured using the Embrace2 wearable device, likely from home settings. The exact geographic origin (country) is not specified. This was a retrospective longitudinal analysis of real-world data.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

The document states that the EpiAlgo was validated "using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center". It also refers to "adjudicated tonic-clonic seizure data" for the EMU data. This implies that epileptologists were involved in establishing the ground truth.

• Number of experts: Not explicitly stated, but referred to as "a group of epileptologists."
• Qualifications of experts: "epileptologists at a top level 4 epilepsy center." No specific experience (e.g., 10 years of experience) is detailed.

4. Adjudication Method for the Test Set

The document mentions "adjudicated tonic-clonic seizure data" for the EMU study. However, the specific adjudication method (e.g., 2+1, 3+1) is not explicitly described in the provided text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No.
• The study focuses on the performance of the algorithm itself (standalone and with different sensitivity modes), not on how human readers improve with or without AI assistance.
• The effect size of human readers improving with AI vs. without AI assistance is not applicable as this type of study was not performed.

6. Standalone (Algorithm Only) Performance Study

• Yes, a standalone study was done. The entire performance analysis for PPA and FAR presented in Tables 1-4 reflects the algorithm's performance (EpiAlgo ver 2.1) using the Low-Sensitivity mode, without human intervention in the detection process. The device detects an event, and the app initiates an alert; there's no mention of a human-in-the-loop directly influencing the detection sensitivity.

7. Type of Ground Truth Used

• Expert Consensus / Gold Standard (Video-EEG): The ground truth for seizure events was primarily established using gold-standard video-Electroencephalogram (EEG) methodology and "adjudicated tonic-clonic seizure data." This indicates expert consensus based on clinical and physiological evidence.

8. Sample Size for the Training Set

The provided text does not specify the sample size used for the training set of the EpiAlgo. It only describes the validation phases for the Low-Sensitivity mode.

9. How the Ground Truth for the Training Set Was Established

The provided text states: "The EpiAlgo has been validated through testing, using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units."

This implies that the training data's ground truth was established by epileptologists using video-EEG data from patients with generalized tonic-clonic seizures (GTCSs) in hospital Epilepsy Monitoring Units. This is consistent with clinical gold standards for seizure identification.

Ask a specific question about this device

The Embrace is a prescription only device that is indicated for use as an adjunct to seizure monitoring of adults and children age 6 and up in home or healthcare facilities during periods of rest. The device is worn on the wrist and senses Electrodermal Activity (EDA) and motion data to detect patterns that may be associated with generalized tonic clonic seizures in patients with epilepsy or at risk of having epilepsy. When a seizure event is detected, Embrace sends a command to a paired wireless device that is programmed to initiate an alert to a designated caregiver. The System records and stores data from Accelerometer, EDA, and Temperature sensors for subsequent review by a trained healthcare professional.

The Embrace is a wearable biosensor device that can capture, store, and wirelessly transmit sensor data via Bluetooth to a paired remote device. Embrace runs an on-board algorithm to continuously process sensor data and make a decision about whether the data might indicate a generalized tonic clonic seizure (GTCS). The algorithm has been validated on data, labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 6 epilepsy centers, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units. When a likely GTCS is detected, the Embrace sends a message to the Alert smartphone application, which initiates calls and texts to summon the attention of designated caregivers. The device also enables patients to manually record seizure events, and provides contextual information related to activity and sleep.

The provided document describes the FDA 510(k) clearance for the Empatica Embrace device, a non-EEG physiological signal-based seizure monitoring system. The information below is extracted and organized to answer your request.

1. Table of Acceptance Criteria and Reported Device Performance

While the document doesn't explicitly state "acceptance criteria" in a separate section with specific numerical thresholds for clearance, the performance results presented indicate the observed efficacy. The implicit acceptance criteria would be for the device to perform well enough to demonstrate substantial equivalence to the predicate device and ensure safety and effectiveness.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: 141 patients diagnosed with epilepsy.
  • 80 pediatric patients (ages 6-21 years, median: 13 years)
  • 61 adult patients (ages 22-63 years, median: 39 years)
• Data Provenance: The study was conducted in a hospital Epilepsy Monitoring Unit (EMU) setting. While the document doesn't explicitly state the country of origin, the listed submitter address is in Milan, Italy. The data is prospective as patients were enrolled and monitored during their EMU stay for the purpose of this study.
• Observed GTCS: 31 EMU patients experienced a total of 54 generalized tonic-clonic seizures (GTCSs). 110 EMU patients did not experience any seizure.
• Recorded Data: 141 patients provided overall 409 days (9,806 hours) of ACM (accelerometer) and EDA (electrodermal activity) measurements, with a median of 49.2 hours of data per patient.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Number of Experts: A "panel of three readers" was used.
• Qualifications of Experts: The ground truth was established using "the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 6 epilepsy centers." This implies the "readers" were highly qualified medical professionals experienced in epilepsy diagnosis and seizure classification, likely epileptologists, given the standard of care in EMUs. Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

The document states "relative to a panel of three readers." While it doesn't explicitly detail the adjudication method (e.g., majority vote, independent assessment with reconciliation), the phrase "panel of three readers" suggests a consensus or majority agreement approach was used to establish the ground truth from the video-EEG data. It is not explicitly stated as 2+1 or 3+1, but rather that the ground truth was derived from the consensus of these three readers.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, What Was the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance

• No MRMC comparative effectiveness study was described where human readers' performance with and without AI assistance was evaluated. This study focused on the standalone performance of the device's algorithm in detecting GTCS.

6. If a Standalone (i.e., Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Yes, a standalone performance study was done. The reported PPA and FAR metrics represent the performance of the Embrace device's algorithm in detecting GTCS events based on its internal processing of EDA and motion data, without direct human intervention in the detection process. The device sends an alert when a likely GTCS is detected, which then initiates actions by caregivers. The study evaluates the accuracy of these automated detections.

7. The Type of Ground Truth Used

• The ground truth used was expert consensus based on gold-standard video-Electroencephalogram (EEG) methodology. This is considered a high-fidelity ground truth for seizure detection in an Epilepsy Monitoring Unit (EMU) setting. Every recorded seizure was classified as epileptic.

8. The Sample Size for the Training Set

The document states: "Embrace runs an on-board algorithm to continuously process sensor data and make a decision about whether the data might indicate a generalized tonic clonic seizure (GTCS). The algorithm has been validated on data, labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 6 epilepsy centers, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units."

• The document describes the validation of the algorithm on data from specific sources but does not explicitly state the sample size used for the training set. The 141 patient dataset is specifically described as the "clinical testing" dataset, suggesting it was used for evaluation, not necessarily for training. It's common for validation data to be distinct from training data.

9. How the Ground Truth for the Training Set Was Established

• Similar to the validation set, the description implies that the data used for training (or at least development and refinement) of the algorithm was "labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 6 epilepsy centers, from epilepsy patients experiencing GTCSs in hospital Epilepsy Monitoring Units." This indicates a high-quality, expert-driven ground truth establishment process for the data used to develop and refine the algorithm.

Ask a specific question about this device

The Embrace is a prescription only device that is indicated for use as an adjunct to seizure monitoring of adults in home or healthcare facilities during periods of rest. The device is worn on the wrist, and senses Electrodermal Activity (EDA) and motion data to detect patterns that may be associated with generalized tonic seizures in patients with epilepsy or at risk of having epilepsy. When a seizure event is detected, Embrace sends a command to a paired wireless device that is programmed to initiate an alert to a designated caregiver. The System records and stores data from Accelerometers, EDA, and Temperature for subsequent review by a trained healthcare professional.

The Embrace is a wearable biosensor device that can capture, store, and wirelessly transmit sensor data via Bluetooth to a paired remote device. Embrace runs an on-board algorithm to continuously process sensor data and make a decision about whether the data might indicate a generalized tonic clonic seizure (GTC). The algorithm has been validated on data, labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCs in hospital Epilepsy Monitoring Units. When a likely GTC is detected, the Embrace sends a message to the Alert smartphone application, which initiates calls and texts to summon the attention of designated caregivers.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. A table of acceptance criteria and the reported device performance

Note on Acceptance Criteria: The document does not explicitly state numerical acceptance criteria for PPA and FAR. Instead, it reports the device's performance metrics and implicitly suggests that these values are deemed acceptable for marketing the device as "substantially equivalent" to a predicate device. The FDA typically relies on a comparison to predicate devices and clinical justification for novel devices.

2. Sample size used for the test set and the data provenance

• Sample Size for Test Set:
  • 135 patients diagnosed with epilepsy were enrolled.
  • Out of these, 22 patients experienced a total of 40 generalized tonic clonic seizures (GTCSs).
  • 113 patients did not experience any seizures during the study.
• Data Provenance:
  • Country of Origin: Not explicitly stated, but the study was conducted within an "Epilepsy Monitoring Unit (EMU)" in a "top level 4 epilepsy center," suggesting a clinical setting in a developed healthcare system (likely the US, given the FDA submission).
  • Retrospective or Prospective: The study enrolled patients and observed them for seizure events within the EMU, implying a prospective collection of data for the purpose of validating the device.

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

• Number of Experts: Three readers.
• Qualifications of Experts: They are referred to as a "panel of three readers." Although their specific qualifications (e.g., neurologists, epileptologists, years of experience) are not explicitly detailed in this document, the context of an "Epilepsy Monitoring Unit" and "gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists" strongly suggests they were highly qualified medical professionals specializing in epilepsy and EEG interpretation.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

The document mentions "relative to a panel of three readers" for PPA calculation. This implies that the ground truth was established by consensus (or agreement) among these three readers. The specific adjudication method (e.g., if at least 2 out of 3 had to agree, or if all 3 had to agree, or if a tie-breaking fourth expert was used) is not explicitly stated. However, the use of a "panel" suggests a structured review process.

5. 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

• Was an MRMC comparative effectiveness study done? No. The study described focuses on the standalone performance of the Embrace device (i.e., the algorithm's ability to detect seizures) against a human-established ground truth. It does not evaluate how human readers' performance might change with or without the device's assistance.

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

• Yes, a standalone performance study was done. The performance metrics (PPA and FAR) directly reflect the algorithm's ability to detect GTC seizures based on sensor data. The device "runs an on-board algorithm to continuously process sensor data and make a decision about whether the data might indicate a generalized tonic clonic seizure (GTC)."

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• Ground Truth Type: Expert consensus based on "gold-standard video-Electroencephalogram (EEG) methodology." This is a strong form of ground truth for epilepsy, as video-EEG is the primary method for diagnosing and classifying seizures in clinical practice. The data was "labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists."

8. The sample size for the training set

The document states, "The algorithm has been validated on data, labeled using the gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center, from epilepsy patients experiencing GTCs in hospital Epilepsy Monitoring Units."

However, it does not explicitly state the sample size of the training set. It only describes the validation set (the 135 patients). It's common for regulatory submissions to omit detailed training set information, focusing instead on the independent validation (test) set.

9. How the ground truth for the training set was established

• The ground truth for the training set (implied, as the exact set is not detailed) was established using the "gold-standard video-Electroencephalogram (EEG) methodology designed by a group of epileptologists at a top level 4 epilepsy center." This indicates that the training data was meticulously labeled by highly qualified experts using the most reliable method for seizure detection.

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