Noninvasive detection of focal seizures in ambulatory patients

被引:23
|
作者
Ryvlin, Philippe [1 ]
Cammoun, Leila [1 ]
Hubbard, Ilona [1 ]
Ravey, France [1 ]
Beniczky, Sandor [2 ,3 ]
Atienza, David [1 ,4 ]
机构
[1] Vaud Univ Hosp, Dept Clin Neurosci, Lausanne, Switzerland
[2] Danish Epilepsy Ctr, Dept Clin Neurophysiol, Dianalund, Denmark
[3] Aarhus Univ Hosp, Dept Clin Neurophysiol, Aarhus, Denmark
[4] Swiss Fed Inst Technol Lausanne, Embedded Syst Lab, Lausanne, Switzerland
基金
瑞士国家科学基金会;
关键词
focal seizure; seizure detection; wearable devices; HEART-RATE CHANGES; HYPERMOTOR SEIZURES; EPILEPTIC SEIZURES; AUTOMATED SEIZURE; DETECTION SYSTEMS; ICTAL HYPOXEMIA; RISK-FACTORS; EEG; ACCELEROMETRY; ABNORMALITIES;
D O I
10.1111/epi.16538
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Reliably detecting focal seizures without secondary generalization during daily life activities, chronically, using convenient portable or wearable devices, would offer patients with active epilepsy a number of potential benefits, such as providing more reliable seizure count to optimize treatment and seizure forecasting, and triggering alarms to promote safeguarding interventions. However, no generic solution is currently available to reach these objectives. A number of biosignals are sensitive to specific forms of focal seizures, in particular heart rate and its variability for seizures affecting the neurovegetative system, and accelerometry for those responsible for prominent motor activity. However, most studies demonstrate high rates of false detection or poor sensitivity, with only a minority of patients benefiting from acceptable levels of accuracy. To tackle this challenging issue, several lines of technological progress are envisioned, including multimodal biosensing with cross-modal analytics, a combination of embedded and distributed self-aware machine learning, and ultra-low-power design to enable appropriate autonomy of such sophisticated portable solutions.
引用
收藏
页码:S47 / S54
页数:8
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