Automated Epileptic Seizure Detection Based on Wearable ECG and PPG in a Hospital Environment
Kaat Vandecasteele,
Thomas De Cooman,
Ying Gu,
Evy Cleeren,
Kasper Claes,
Wim Van Paesschen,
Sabine Van Huffel,
Borbála Hunyadi
Affiliations
Kaat Vandecasteele
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven 3001, Belgium
Thomas De Cooman
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven 3001, Belgium
Ying Gu
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven 3001, Belgium
Evy Cleeren
KU Leuven, University Hospital, Department of Neurosciences, Leuven 3000, Belgium
Kasper Claes
UCB, Brussels 1070, Belgium
Wim Van Paesschen
KU Leuven, University Hospital, Department of Neurosciences, Leuven 3000, Belgium
Sabine Van Huffel
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven 3001, Belgium
Borbála Hunyadi
KU Leuven, Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven 3001, Belgium
Electrocardiography has added value to automatically detect seizures in temporal lobe epilepsy (TLE) patients. The wired hospital system is not suited for a long-term seizure detection system at home. To address this need, the performance of two wearable devices, based on electrocardiography (ECG) and photoplethysmography (PPG), are compared with hospital ECG using an existing seizure detection algorithm. This algorithm classifies the seizures on the basis of heart rate features, extracted from the heart rate increase. The algorithm was applied to recordings of 11 patients in a hospital setting with 701 h capturing 47 (fronto-)temporal lobe seizures. The sensitivities of the hospital system, the wearable ECG device and the wearable PPG device were respectively 57%, 70% and 32%, with corresponding false alarms per hour of 1.92, 2.11 and 1.80. Whereas seizure detection performance using the wrist-worn PPG device was considerably lower, the performance using the wearable ECG is proven to be similar to that of the hospital ECG.
