Standard

Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data. / Conradsen, Isa; Beniczky, Sándor; Wolf, Peter; Kjaer, Troels W.; Sams, Thomas; Sørensen, Helge Bjarup Dissing.

In: Computer Methods and Programs in Biomedicine, Vol. 107, No. 2, 2012, p. 97–110.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Harvard

APA

CBE

MLA

Vancouver

Author

Conradsen, Isa; Beniczky, Sándor; Wolf, Peter; Kjaer, Troels W.; Sams, Thomas; Sørensen, Helge Bjarup Dissing / Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data.

In: Computer Methods and Programs in Biomedicine, Vol. 107, No. 2, 2012, p. 97–110.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Bibtex

@article{2cba2ae67c434129935da4ca4a3d8c56,
title = "Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data",
keywords = "Support vector machine learning, Movement sensors, Epilepsy, Surface EMG sensors, Wavelet packet, Seizure detection",
publisher = "Elsevier Ireland Ltd",
author = "Isa Conradsen and Sándor Beniczky and Peter Wolf and Kjaer, {Troels W.} and Thomas Sams and Sørensen, {Helge Bjarup Dissing}",
year = "2012",
doi = "10.1016/j.cmpb.2011.06.005",
volume = "107",
number = "2",
pages = "97–110",
journal = "Computer Methods and Programs in Biomedicine",
issn = "0169-2607",

}

RIS

TY - JOUR

T1 - Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data

A1 - Conradsen,Isa

A1 - Beniczky,Sándor

A1 - Wolf,Peter

A1 - Kjaer,Troels W.

A1 - Sams,Thomas

A1 - Sørensen,Helge Bjarup Dissing

AU - Conradsen,Isa

AU - Beniczky,Sándor

AU - Wolf,Peter

AU - Kjaer,Troels W.

AU - Sams,Thomas

AU - Sørensen,Helge Bjarup Dissing

PB - Elsevier Ireland Ltd

PY - 2012

Y1 - 2012

N2 - The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi- modal detection system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data.

AB - The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet packet transformation (WPT). Based on the extracted features all data segments were classified using a support vector machine (SVM) algorithm as simulated seizure or normal activity. A case study of the seizure from the patient showed that the simulated seizures were visually similar to the epileptic one. The multi-modal intelligent seizure acquisition (MISA) system showed high sensitivity, short detection latency and low false detection rate. The results showed superiority of the multi- modal detection system compared to the uni-modal one. The presented system has a promising potential for seizure detection based on multi-modal data.

KW - Support vector machine learning

KW - Movement sensors

KW - Epilepsy

KW - Surface EMG sensors

KW - Wavelet packet

KW - Seizure detection

U2 - 10.1016/j.cmpb.2011.06.005

DO - 10.1016/j.cmpb.2011.06.005

JO - Computer Methods and Programs in Biomedicine

JF - Computer Methods and Programs in Biomedicine

SN - 0169-2607

IS - 2

VL - 107

SP - 97

EP - 110

ER -