Detecting Tonic-Clonic Seizures in Multimodal Biosignal Data From Wearables: Methodology Design and Validation.
Sebastian BöttcherElisa BrunoNikolay V ManyakovNino EpitashviliKasper ClaesMartin GlasstetterSarah ThorpeSimon LeesMatthias DümpelmannKristof Van LaerhovenMark P RichardsonAndreas Schulze-Bonhagenull nullPublished in: JMIR mHealth and uHealth (2021)
We show that a gradient tree boosting machine can robustly detect TCSs from multimodal wearable data in an original data set and that even with very limited training data, supervised machine learning can achieve a high sensitivity and low false-positive rate. This methodology may offer a promising way to approach wearable-based nonconvulsive seizure detection.