Biomedical Engineering Department, Rochester Institute of Technology, Rochester, NY, USA.
Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA.
Med Biol Eng Comput. 2017 Sep;55(9):1659-1668. doi: 10.1007/s11517-017-1616-z. Epub 2017 Feb 9.
Infantile spasms (ISS) is a devastating epileptic syndrome that affects children under the age of 1 year. The diagnosis of ISS is based on the semiology of the seizure and the electroencephalogram (EEG) background characterized by hypsarrhythmia (HYPS). However, even skilled electrophysiologists may interpret the EEG of children with ISS differently, and commercial software or existing epilepsy detection algorithms are not helpful. Since EEG is a key factor in the diagnosis of ISS, misinterpretation could result in serious consequences including inappropriate treatment. In this paper, we developed a novel algorithm to localize the relevant electrical abnormality known as epileptic discharges (or spikes) to provide a quantitative assessment of ISS in HYPS. The proposed algorithm extracts novel time-frequency features from the EEG signals and localizes the epileptic discharges associated with ISS in HYPS using a support vector machine classifier. We evaluated the proposed method on an EEG dataset with ISS subjects and obtained an average true positive and false negative of 98 and 7%, respectively, which was a significant improvement compared to the results obtained using the clinically available software. The proposed automated method provides a quantitative assessment of ISS in HYPS, which could significantly enhance our knowledge in therapy management of ISS.
婴儿痉挛症（ISS）是一种严重的癫痫综合征，影响 1 岁以下的儿童。ISS 的诊断基于发作的症状学和以高度失律（HYPS）为特征的脑电图（EEG）背景。然而，即使是经验丰富的电生理学家也可能对患有 ISS 的儿童的脑电图有不同的解释，商业软件或现有的癫痫检测算法也无济于事。由于脑电图是诊断 ISS 的关键因素，因此错误解释可能会导致严重后果，包括治疗不当。在本文中，我们开发了一种新的算法，用于定位称为癫痫发作（或尖峰）的相关电异常，以对 HYPS 中的 ISS 进行定量评估。该算法从 EEG 信号中提取新的时频特征，并使用支持向量机分类器定位与 HYPS 中的 ISS 相关的癫痫发作。我们在包含 ISS 受试者的 EEG 数据集上评估了所提出的方法，得到的平均真阳性和假阴性率分别为 98%和 7%，与使用临床可用软件获得的结果相比有显著提高。所提出的自动方法提供了对 HYPS 中 ISS 的定量评估，这可以显著增强我们对 ISS 治疗管理的认识。
