IP Library Granted Patent US 10,238,330
Granted Patent B2
US 10,238,330 · App. 14/900,283 · Granted Mar 26, 2019

Method of indicating the probability of psychogenic non-epileptic seizures

Inventors: Isa Conradsen (København S, DK); Kim Gomme Gommesen (Odense N, DK)
Assignee: Brain Sentinel, Inc.
A61B5/4094A61B5/0488A61B5/11A61B5/7275A61B5/7282G06F19/00A61B5/0002A61B5/0022A61B5/6824A61B2562/0219
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Quick Facts
Patent No.
US 10,238,330
App. No.
14/900,283
Granted
Mar 26, 2019
Kind
B2
Abstract

A method and system for detecting a probability of psychogenic non-epileptic seizures using a portable battery powered device placed on the body of a patient and a device for manually logging detected seizures within a time period. The device may, advantageously, have a seizure detection algorithm which automatically records seizures detected within that time period. The two sets of data may then be transferred to a another device where the logged time stamps are matched to the recorded time stamps for determining if the detected seizure is a generalized tonic-clonic seizure (GTCS) or might be a psychogenic nonepileptic seizure (PNES). This provides a cheap and simple method for registering a probability of PNES by using a seizure detection device having an EMG-sensor or an accelerometer.

Claims (25)

1. A method of indicating the probability of non-epileptic seizures, wherein the method comprises the steps of:

automatically recording patient data over a predetermined time period using a portable seizure detection device placed on a patient's body, wherein the portable seizure detection device comprises at least one sensor unit measuring at least one parameter on the patient's body, the portable seizure detection device configured for detection of seizures;

transmitting the recorded data from the portable seizure detection device to a data processor for further analysis;

operating the portable seizure detection device in a non-alarm mode in which the at least one parameter is compared to at least one threshold value for determining whether a seizure is present or not, in order to provide non-alarm mode recorded data indicating the presence of any detected seizures;

receiving manually logged data comprising at least a first time stamp of at least one seizure within the predetermined time period,

comparing the non-alarm mode recorded data to the manually logged data in the data processor, and

determining if the non-alarm mode recorded data matches the manually logged data or not in order to determine said probability of non-epileptic seizures.

2. A method according to claim 1 , further comprising automatically detecting at least one seizure within the predetermined time period with the portable seizure detection device and recording at least a second time stamp of the at least one seizure detected by the portable seizure detection device, and comparing the second time stamp to the first time stamp to determine if the second time stamp matches the first time stamp or not.

3. A method according to claim 1 , wherein the at least one sensor unit measures one of an electromyographic signal and an acceleration signal.

4. A method according to claim 3 , wherein said one of an electromyographic signal and an acceleration signal is measured on at least one of a limb and skeletal muscle of the patient.

5. A method according to claim 3 , wherein the portable seizure detection device calculates a root-mean-square value of the at least one parameter within at least one time window and compares the root-mean-square-value to the at least one threshold value.

6. A method according to claim 3 , wherein the portable seizure detection device transforms the at least one parameter into both a frequency domain and a time domain, and compares at least one calculated value from each of the frequency and time domains to the at least one threshold value.

7. A method according to claim 3 , wherein the portable seizure detection device extracts at least one predetermined pattern from the at least one parameter, and compares the at least one pattern to the at least one threshold value.

8. A method according to claim 1 , wherein the signal from the at least sensor unit is transmitted directly to base unit recorded in the base unit.

9. A method according to claim 1 , wherein the patient manually logs the data or at least one subject monitoring the patient manually logs the data.

10. A system for indicating the probability of non-epileptic seizures, comprising:

a portable seizure detection device configured to be placed on a patient's body, wherein the portable seizure detection device comprises at least one sensor unit configured to measure at least one parameter on the patient's body, and is configured to automatically record data over a predetermined time period;

a computer unit configured to be coupled to the portable seizure detection device and comprising a data processor configured to analyze data recorded over said predetermined time period; and

a data logger configured for manually logging data comprising at least a first time stamp of at least one seizure within the predetermined time period time period, and

wherein the portable seizure detection device is configured to operate in a non-alarm mode in which the at least one parameter is compared to at least one threshold value for determining whether a seizure is present or not, in order to provide non-alarm recorded data indicating the presence of any detected seizures; and

wherein the computer unit is configured to compare the non-alarm recorded data with the manually logged data and determine if the recorded data matches the manually logged data or not in order to determine said probability of non-epileptic seizures.

11. A system according to claim 10 , wherein the portable seizure detection device is configured to automatically detect at least one seizure within the predetermined time period and to record at least a second time stamp of the at least one seizure, and wherein the computer unit is configured to compare the second time stamp to the first time stamp to determine if the second time stamp matches the first time stamp or not.

12. A system according to claim 8 , wherein the at least one sensor unit is one of an electromyographic sensor and an accelerometer, and wherein the portable seizure detection device is configured to detect said seizure based on the signal from the electromyographic sensor or accelerometer.

13. A system according to claim 10 , wherein the portable seizure detection device is configured to transmit a signal from the at least one sensor unit directly to a base unit which is configured to record said signal.

14. A system according to claim 10 , wherein one of portable seizure detection device and the computer unit comprises a data logger configured for manually logging the data.

Assignments (5)
SECURITY INTEREST Recorded Aug 8, 2022
From: NOVELA NEUROTECHNOLOGIES, INC.
To: HCV INVESTMENTS, LLC
Reel/Frame 060746/0143 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 1, 2022
From: HCV INVESTMENTS, LLC
To: NOVELA NEUROTECHNOLOGY
Reel/Frame 060065/0971 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 27, 2022
From: BRAIN SENTINEL, INC.
To: HCV INVESTMENTS, LLC
Reel/Frame 060043/0697 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 29, 2018
From: ICTALCARE A/S
To: BRAIN SENTINEL, INC.
Reel/Frame 044759/0410 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 21, 2015
From: CONRADSEN, ISA; GOMMESEN, KIM GOMME
To: ICTALCARE A/S
Reel/Frame 037339/0541 →
Priority Claims (1)
DK 2013 70337 · Jun 21, 2013 · national
Continuity (1)
Related Publication 20160296156A1 · Oct 13, 2016