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基于深度学习的可穿戴光体积描记术的动态房颤监测Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning |
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| 课程网址: | http://videolectures.net/kdd2019_voisin_shen_aliamiri/ |
| 主讲教师: | Maxime Voisin |
| 开课单位: | 斯坦福大学 |
| 开课时间: | 2020-03-02 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We develop an algorithm that accurately detects Atrial Fibrillation (AF) episodes from photoplethysmograms (PPG) recorded in ambulatory free-living conditions. We collect and annotate a dataset containing more than 4000 hours of PPG recorded from a wrist-worn device. Using a 50-layer convolutional neural network, we achieve a test AUC of 95% in presence of motion artifacts inherent to PPG signals. Such continuous and accurate detection of AF has the potential to transform consumer wearable devices into clinically useful medical monitoring tools. |
| 关 键 词: | 基于深度学习; 可穿戴光体积描记术; 动态房颤监测; 光容积描记图 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-09-15：cyh |
| 最后编审: | 2022-09-19：cyh |
| 阅读次数: | 28 |