Machine learning and wearable devices of the future

Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy, and we outline future development in these domains. There is published evidence for reliable detection of epileptic seizures using implanted electroencephalography (EEG) electrodes and wearable, non-EEG devices. Application of ML using the data recorded with WDs from a large number of patients could change radically the way we diagnose and manage patients with epilepsy.

Automated summary

Machine learning is increasingly being recognized as a useful tool in healthcare applications, including epilepsy, with one important application being seizure detection and prediction using wearable devices. Current evidence suggests that reliable detection of epileptic seizures can be achieved using data recorded with WDs, and the application of ML has the potential to radically change how we diagnose and manage patients with epilepsy.