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Study to Validate Novel Seizure-Detection Algorithm

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赞助商
Overwatch Digital Health
合作者
Bracane Company

关键词

抽象

The specificity and sensitivity of a novel seizure-detection mobile software application with a generalized tonic/clonic seizure detection algorithm (Motor Seizure Detection Algorithm [mSDA]) installed on a wearable device to be worn by the subject. The software will be tested using subjects from a patient population in an epilepsy monitoring unit (EMU) undergoing video and electroencephalograph (VEEG) observation. The number of generalized major motor seizures detected by the mSDA will be compared with those detected by VEEG.

描述

Seizures are paroxysmal, abnormal behaviors which usually are associated with altered awareness and amnesia. The frequency of seizures is not easily documented. The individual who suffers from seizures may be unaware that a seizure is occurring. Many seizures, including generalized major motor seizures, have stereotyped, vigorous motor activity associated with the events.

Currently, accurate seizure detection relies on EEG and video which are limited by time, size and mobility. Seizure detection can also use biomarkers such as movement patterns described by gyroscopes. These devices can monitor patterns of movement which correspond to the activity during seizures and kept in a log of seizures without patient input. The log can be used to notify patients or caregivers of seizures.

This study is to determine the accuracy of a system using a commercial, wearable device linked to a computer algorithm based in the cloud which stores the movement pattern and notifies the patient and others of a generalized major motor seizure. The accuracy will be determined by a comparison of the system detections to simultaneously recorded video electroencephalogram, considered the "gold standard" of seizure detection.

日期

最后验证: 01/31/2020
首次提交: 02/23/2020
提交的预估入学人数: 02/26/2020
首次发布: 03/01/2020
上次提交的更新: 02/26/2020
最近更新发布: 03/01/2020
实际学习开始日期: 02/29/2020
预计主要完成日期: 09/30/2020
预计完成日期: 11/30/2020

状况或疾病

Seizures, Motor
Seizures
Seizure Disorder
Epilepsy
Epileptic Seizures
Epileptic

干预/治疗

Device: Single Arm

-

手臂组

干预/治疗
Other: Single Arm
This is a single-arm study. All subjects enrolled in the study will wear the device during stay in the EMU.
Device: Single Arm
A seizure detection algorithm installed on a propriety mobile application to be used on a commercially available watch with a gyroscope to detect movement.

资格标准

有资格学习的年龄 18 Years 至 18 Years
有资格学习的性别All
接受健康志愿者
标准

Inclusion Criteria:

1. Provision of signed and dated informed consent form.

2. Stated willingness to comply with all study procedures and availability for the duration of the study.

3. Meets the standard of care criteria for admission to an epilepsy monitoring unit (EMU).

4. Male or female.

5. Aged 18 and above.

6. The patient has experienced at least one generalized major motor seizure prior to admission.

7. Agreement to wear a wristwatch throughout the duration of the study on the left wrist.

8. Ability to cancel false positive alarms via interaction with the application on the watch.

Exclusion Criteria:

1. Concurrent physiological diseases with movement disorders (Parkinson's, tremor, ataxia, Huntington's, paralysis of the upper body, pseudo-seizures).

2. Known allergic reactions to components of the (watch materials).

3. Treatment with another investigational drug or other intervention within the study

4. Children under the age of 18.

5. Women who are pregnant or nursing.

6. Inability to give consent to the study.

7. Active skin infection or rash on the upper extremities

结果

主要结果指标

1. Sensitivity [1 to 5 days]

Number of major motor seizure detections by algorithm with detection by video encephalogram data.

次要成果指标

1. False positive rate [1 to 5 days]

Total number of false positives and number of false positives per day.

2. Mean detection latency [1 to 5 days]

Time between algorithm detection and application notification

3. Notifications [1 to 5 days]

Total number of seizure notifications received on subject's assigned email

4. Cancellations [1 to 5 days]

Total number of cancellations of false positive alerts made by the subject.

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