title: Automated Detection of Tonic-Clonic Seizures Using 3-D Accelerometry and Surface Electromyography in Pediatric Patients.
abstract: Epileptic seizure detection is traditionally done using video/electroencephalography monitoring, which is not applicable for long-term home monitoring. In recent years, attempts have been made to detect the seizures using other modalities. In this study, we investigated the application of four accelerometers (ACM) attached to the limbs and surface electromyography (sEMG) electrodes attached to upper arms for the detection of tonic-clonic seizures. sEMG can identify the tension during the tonic phase of tonic-clonic seizure, while ACM is able to detect rhythmic patterns of the clonic phase of tonic-clonic seizures. Machine learning techniques, including feature selection and least-squares support vector machine classification, were employed for detection of tonic-clonic seizures from ACM and sEMG signals. In addition, the outputs of ACM and sEMG-based classifiers were combined using a late integration approach. The algorithms were evaluated on 1998.3 h of data recorded nocturnally in 56 patients of which seven had 22 tonic-clonic seizures. A multimodal approach resulted in a more robust detection of short and nonstereotypical seizures (91%), while the number of false alarms increased significantly compared with the use of single sEMG modality (0.28-0.5/12h). This study also showed that the choice of the recording system should be made depending on the prevailing pediatric patient-specific seizure characteristics and nonepileptic behavior.
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS, KU Leuven and iMinds IT Department, Leuven, Belgium.
authors.forename: Milica
authors.initials: M
authors.lastname: Milosevic
authors.affiliation: Department of Neurology-Paediatric Neurology, University Hospital University of Antwerp, Wilrijk, Belgium.
authors.forename: Anouk
authors.initials: A
authors.lastname: Van de Vel
authors.affiliation: MOBILAB, Thomas More Kempen, Geel, Belgium.
authors.forename: Bert
authors.initials: B
authors.lastname: Bonroy
authors.affiliation: Rehabilitation Center for Children and Youth Pulderbos, Pulderbos, Belgium.
authors.forename: Berten
authors.initials: B
authors.lastname: Ceulemans
authors.affiliation: Department of Child Neurology, University Hospital KU Leuven, Leuven, Belgium.
authors.forename: Lieven
authors.initials: L
authors.lastname: Lagae
authors.affiliation: Department of Electrical Engineering (ESAT), Advanced Integrated Sensing (AdvISe), KU Leuven, Geel, Belgium.
authors.forename: Bart
authors.initials: B
authors.lastname: Vanrumste
authors.affiliation: Department of Electrical Engineering (ESAT), STADIUS, KU Leuven and iMinds IT Department, Leuven, Belgium.
authors.forename: Sabine Van
authors.initials: SV
authors.lastname: Huffel
mesh_terms: D061725:Accelerometry / Q000379:methods*; D002648:Child; D004576:Electromyography / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D012640:Seizures / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted