Hubbard Ilona, Beniczky Sandor, Ryvlin Philippe
Department of Clinical Neurosciences, Vaud University Hospital, Lausanne, Switzerland.
Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark.
Front Neurol. 2021 Oct 1;12:740743. doi: 10.3389/fneur.2021.740743. eCollection 2021.
Seizure detection, and more recently seizure forecasting, represent important avenues of clinical development in epilepsy, promoted by progress in wearable devices and mobile health (mHealth), which might help optimizing seizure control and prevention of seizure-related mortality and morbidity in persons with epilepsy. Yet, very long-term continuous monitoring of seizure-sensitive biosignals in the ambulatory setting presents a number of challenges. We herein provide an overview of these challenges and current technological landscape of mHealth devices for seizure detection. Specifically, we display, which types of sensor modalities and analytical methods are available, and give insight into current clinical practice guidelines, main outcomes of clinical validation studies, and discuss how to evaluate device performance at point-of-care facilities. We then address pitfalls which may arise in patient compliance and the need to design solutions adapted to user experience.
癫痫发作检测,以及最近的癫痫发作预测,是癫痫临床发展的重要途径,这得益于可穿戴设备和移动健康(mHealth)的进步,它们可能有助于优化癫痫控制以及预防癫痫患者的癫痫相关死亡率和发病率。然而,在动态环境中对癫痫敏感生物信号进行非常长期的连续监测存在诸多挑战。我们在此概述这些挑战以及用于癫痫发作检测的移动健康设备的当前技术状况。具体而言,我们展示了可用的传感器模式和分析方法类型,深入了解当前的临床实践指南、临床验证研究的主要结果,并讨论如何在医疗点设施评估设备性能。然后,我们探讨患者依从性方面可能出现的问题以及设计适应用户体验的解决方案的必要性。