19  Seizure Detection Devices

NoteAbout this page

This page provides general information about seizure detection devices to help families understand what is available. It is not medical advice, and the inclusion of any device here is not an endorsement or recommendation. Talk to your child’s neurologist about whether a device makes sense for your situation and which type might be most appropriate.

Many families wonder whether there is a device that can alert them when a seizure is happening, especially at night. Seizure detection devices are wearable or environmental monitoring tools that use sensors to detect physical changes that may occur during a seizure, such as unusual movements, muscle activity, or changes in heart rate, and send an alert to a caregiver’s phone or another device.

Although seizure detection devices can alert caregivers to some seizures, it remains unknown whether their use reduces the risk of SUDEP (sudden unexpected death in epilepsy). No device has been proven to prevent SUDEP, and none is cleared or approved by the United States Food and Drug Administration (FDA) for this purpose13. These devices are intended to support supervision, not replace it.

19.1 Who Might Benefit Most?

Seizure detection devices are most commonly considered for people who have generalized tonic-clonic (convulsive) seizures, especially when seizures occur during sleep, happen unexpectedly, or are difficult for caregivers to recognize. They may be less helpful for seizure types that do not involve significant movement, such as many focal seizures or absence seizures.

Whether a device is worthwhile depends on a child’s seizure type, seizure frequency, age, and the specific safety concerns of the family.

19.2 What Types of Devices Are Available?

Wrist-worn devices look like a watch or fitness tracker. They detect seizures by measuring movement, skin changes associated with sweating, and heart rate. The best-studied option in this category is the Embrace2 watch by Empatica, which is FDA-cleared for monitoring generalized tonic-clonic seizures4. In published studies, detection rates for generalized tonic-clonic seizures have generally ranged from approximately 90-100%, although performance varies between individuals and some seizures may still be missed. Reported false alarm rates in home settings are typically fewer than 0.5 per day5,6. The device sends alerts through a smartphone app to designated caregivers and includes GPS location sharing. A monthly subscription fee is required.

Armband devices are worn on the upper arm and use sensors to measure muscle activity during seizures. The EpiCare device (Danish Care Technology) uses electromyography (EMG) to detect muscle activity associated with convulsive seizures. It is approved for medical use in Europe but is not FDA-cleared in the United States. Published studies have reported detection rates ranging from approximately 76-94% for generalized tonic-clonic seizures4,7. Alerts can be sent by phone call, text message, or email. False alarm rates tend to be higher during periods of physical activity7.

Smartwatch apps work with watches you may already own, such as an Apple Watch or compatible Android watch. Apps such as SeizAlarm and EpiMonitor use the watch’s built-in movement and heart rate sensors to detect possible seizures. These options tend to be lower cost, although fewer have undergone rigorous validation studies compared with dedicated seizure detection devices. Some smartwatch-based seizure detection systems have recently received FDA clearance for tonic-clonic seizure detection in patients aged 5 years and older, but published performance data remain more limited8.

Under-mattress monitors sit beneath the mattress and detect movement during sleep without requiring the person to wear anything. Examples include the Emfit Movement Monitor and similar bed-based monitoring systems. These devices detect repetitive movements that may be consistent with a convulsive seizure and alert a caregiver911. Because they rely on movement, they are primarily useful for seizures that occur during sleep.

Video monitors use a camera to watch for unusual movement during sleep. The SAMi Sleep Activity Monitor is one example of a video-based monitoring system that alerts caregivers when it detects abnormal movement patterns12. Some systems also store video clips that can be reviewed later.

19.3 How Well Do These Devices Work?

For generalized tonic-clonic (convulsive) seizures, the best-studied wearable devices detect many events, with reported detection rates often exceeding 90% in research studies13. They generally perform best during sleep or periods of rest.

A false alarm occurs when the device sends an alert even though no seizure has occurred. Depending on the device and the person’s activity level, false alarm rates range from very infrequent to several alerts per day. Children tend to have more false alarms than adults, often during active play, vigorous exercise, toothbrushing, or other repetitive movements.

Current devices are much less reliable for focal seizures (seizures that start in one part of the brain without major convulsive movement) and absence seizures (brief staring spells). If your child has these seizure types, discuss with your neurologist whether a detection device is likely to be helpful.

In surveys of real-world users, most people report detection performance similar to what was expected based on published studies, and many continue using their device long-term14. There is often a brief adjustment period while learning how to use the device and manage false alarms.

19.4 What Should I Consider When Looking at Devices?

Factors worth thinking through include your child’s seizure type (devices perform best for generalized tonic-clonic seizures), age and activity level (younger, more active children tend to generate more false alarms), whether your child will wear the device consistently, the cost, and whether the device has been clinically validated with published accuracy data.

Devices that have received regulatory clearance, such as FDA clearance in the United States or CE marking in Europe, have undergone formal review processes. However, the requirements and evidence standards differ between regions.

Some devices are covered by insurance. The Danny Did Foundation offers information about seizure safety devices and may provide financial assistance or discounts for eligible families.

19.5 A Note on Seizure Diary Apps

Separate from detection devices, there are several free apps designed to help families track and record seizures. These do not detect seizures automatically. You enter the information yourself after a seizure occurs. Popular options include Epilepsy Journal, EpiDiary, and SeizureTracker15. They allow you to log when seizures happen, how long they last, what type they were, and possible triggers. This information can be very helpful to bring to your child’s neurology appointments.

19.6 Talking to Your Doctor

Before purchasing a seizure detection device, it is worth discussing with your child’s neurologist whether a device would be appropriate given your child’s specific seizure type, when seizures typically occur, and what safety concerns are driving the question. Your neurologist can also advise on which devices have the best evidence for your situation, whether nighttime-only use makes sense, and whether your insurance is likely to cover any portion of the cost.

References

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Devinsky O, Hesdorffer DC, Thurman DJ, Lhatoo S, Richerson G. Sudden unexpected death in epilepsy: Epidemiology, mechanisms, and prevention. The Lancet Neurology. 2016; 15(10):1075–88.
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Maguire MJ, Jackson CF, Marson AG, Nevitt SJ. Treatments for the prevention of Sudden Unexpected Death in Epilepsy (SUDEP). Cochrane Epilepsy Group, editor. Cochrane Database of Systematic Reviews [Internet]. 2020 [cited 2026]; 2020(4). Available from: http://doi.wiley.com/10.1002/14651858.CD011792.pub3
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Naganur V, Sivathamboo S, Chen Z, Kusmakar S, Antonic-Baker A, O’Brien TJ, et al. Automated seizure detection with noninvasive wearable devices: A systematic review and meta-analysis. Epilepsia. 2022; 63(8):1930–41.
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