Grzeskowiak Caitlin L, Dumanis Sonya B
Epilepsy Foundation of America, Greater Landover, MD, United States.
Coalition for Aligning Science, Chevy Chase, MD, United States.
Front Neurol. 2021 Sep 20;12:717428. doi: 10.3389/fneur.2021.717428. eCollection 2021.
Accurate seizure forecasting is emerging as a near-term possibility due to recent advancements in machine learning and EEG technology improvements. Large-scale data curation and new data element collection through consumer wearables and digital health tools such as longitudinal seizure diary data has uncovered new possibilities for personalized algorithm development that may be used to predict the likelihood of future seizures. The Epilepsy Foundation recognized the unmet need for development in seizure forecasting following a 2016 survey where an overwhelming majority of respondents across all seizure types and frequencies reported that unpredictability of seizures had the strongest impact on their life while living with or caring for someone living with epilepsy. In early 2021, the Epilepsy Foundation conducted an updated survey among those living with epilepsies and/or their caregivers to better understand the use-cases that best suit the needs of our community as seizure forecast research advances. These results will provide researchers with insight into user-acceptance of using a forecasting tool and incorporation into their daily life. Ultimately, this input from people living with epilepsy and caregivers will provide timely feedback on what the community needs are and ensure researchers and companies first and foremost consider these needs in seizure forecasting tools/product development.
由于机器学习的最新进展和脑电图(EEG)技术的改进,准确的癫痫发作预测正成为近期可能实现的目标。通过消费者可穿戴设备和数字健康工具(如纵向癫痫发作日记数据)进行大规模数据整理和新数据元素收集,为个性化算法开发带来了新的可能性,这些算法可用于预测未来癫痫发作的可能性。癫痫基金会在2016年的一项调查后认识到癫痫发作预测领域存在未满足的发展需求,在该调查中,所有癫痫发作类型和频率的绝大多数受访者都表示,癫痫发作的不可预测性对他们自己或照顾癫痫患者的生活影响最大。2021年初,癫痫基金会对癫痫患者和/或其护理人员进行了一项更新调查,以更好地了解随着癫痫发作预测研究的推进,最适合我们社区需求的用例。这些结果将为研究人员提供关于用户对使用预测工具的接受程度以及将其融入日常生活情况的见解。最终,癫痫患者和护理人员的这些意见将及时反馈社区的需求,并确保研究人员和公司在癫痫发作预测工具/产品开发中首先考虑这些需求。