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Assessment of the Emfit Mattress Sensor for Detection and Alarm of Night-time Generalized Tonic-clonic Seizures.

Assessment of the Emfit Mattress Sensor (L-4060SLC) and Monitor (DVM-GPRS-V2) and Their Acoustic and Cloud Interface Notification Capabilities as a Nocturnal Detection System for Movements Associated With Generalized Tonic-clonic Seizures.

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT02661919
Enrollment
50
Registered
2016-01-25
Start date
2019-10-01
Completion date
2020-06-30
Last updated
2019-08-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Epilepsy, Seizures

Keywords

Epilepsy, Seizure, Seizures, Mattress monitor, Bed monitor, Bed alarm, Generalized tonic-clonic seizure, GTC

Brief summary

Sudden unexpected death in epilepsy (SUDEP) is the most important epilepsy-related mode of death. The exact mechanism of SUDEP is not known. It is thought that cardiac and respiratory factors are involved. Several ways of preventing SUDEP have been identified. These include seizure control, stress reduction, physical activity, family's ability to perform CPR, and night supervision. A mattress alarm system that monitors nocturnal seizures can alert family members of night time seizure activity. Thus, a family member could provide aid and therefore potentially avoid SUDEP. The Emfit monitor is intended to perform these tasks. Investigators tested the Emfit mattress monitor DVM-GPRS-V2 in combination with the Emfit bed sensor L-4060SL in the epilepsy monitoring unit and were able to demonstrate that the device has a high predictive value for detection of generalized convulsions and that it can notify caregivers in the early stages of convulsive activity. This study will further investigate the upgraded (connected to a cloud server via an integrated cellular GPRS module) Emfit mattress monitor DVM-GPRS-V2 and the upgraded Emfit mattress sensor L-4060SLC in combination with an acoustic and new cloud-based notification system.

Interventions

DEVICEEmfit mattress sensor

Patients who are being monitored in the Epilepsy Monitoring Unit will have an Emfit mattress sensor placed under their mattress and the effectiveness of the alarm system will be tested.

Sponsors

Emfit, Corp.
Lead SponsorINDUSTRY

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 89 Years
Healthy volunteers
No

Inclusion criteria

* Overnight Epilepsy Monitoring Unit admission

Exclusion criteria

* 12 hours or shorter Epilepsy Monitoring Unit admission

Design outcomes

Primary

MeasureTime frameDescription
Alarm effectiveness22 monthsInvestigators are testing the efficacy of the Emfit mattress monitor acoustic notifications for detecting GTC seizures. During video-eeg monitoring clinically detected GTC seizures are listed. These records are compared to Emfit monitor sound notications detected at video recordings. The true-positive, false-positive and false-negative calculations are primary outcome.

Secondary

MeasureTime frameDescription
Seizure type distinction10 monthsInvestigators are testing the Emfit matters sensor acoustic notifications efficacy for detecting other than GTC type seizures (partial seizures, non-epileptic events). Investigators are testing the efficacy of the Emfit mattress monitor acoustic notifications for clinically detected seizures. During video-eeg monitoring clinically detected other than GTC type seizures are listed. These records are compared to Emfit monitor sound notications detected at video recordings. The true-positive, false-positive and false-negative calculations are outcome. False-positive notifications are excluded if patient video recording shows rhytmic movement due patient being awake and performing day-time other activity.

Countries

United States

Contacts

Primary ContactIrena I. Garić, RN, MPH
igaric@nmff.org(312) 926-1672

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026