可穿戴计算机
计算机科学
人工智能
医学
物理医学与康复
嵌入式系统
作者
Sándor Beniczky,Philippa J. Karoly,Ewan S. Nurse,Philippe Ryvlin,Mark Cook
出处
期刊:Epilepsia
[Wiley]
日期:2020-07-26
卷期号:62 (S2)
被引量:117
摘要
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.
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