Publication

Clinical Implications of Atrial Fibrillation Detection Using Wearable Devices in Patients With Cryptogenic Stroke (CANDLE-AF) Trial: Design and Rationale

Published

Frontiers in Cardiovascular Medicine 2022.04

Author

Sodam jung, Hye Ah Lee, In sook Kang, Sang Hoon Shin, YoonKyung Chang, Dong Woo Shin, Moo-Seok Park, Young Dae Kim, Hyo Suk Nam, Ji Hoe Heo, Tae-Hoon Kim, Hee Tae Yu, Jung Myung Lee, Sung Hyuk Heo, Ho Geol Woo, Jin-Kyu Park, Seung-Young Roh, Chi Kyung Kim, Young-Soo Lee, Jin Kuk Do, Dong-Hyeok Kim, Tae-Jin Song, Junbeom Park and CANDLE AF Trial investigators

Development of a deep learning algorithm for atrial fibrillation identification using single lead electrocardiogram

Published 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Sun Jung Lee, Yun Kwan Kim, Lanmi Hwang, Kyung Chul Kim, Hee Seok Song Abstract Since it is difficult to detect atrial fibrillation (AF) at an early stage, a method to identify the potential

Fast and Accurate Atrial Fibrillation Detection Using Semantic Segmentation

Published 2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Kun Wook Jo, Hoo Hyun Kim, Jong Doo Choi, Hee Seok Song Abstract We developed a deep learning model to detects atrial fibrillation by segments the morphological features of fibrillations (F wave).

Evaluation of exercise stage and amount of exercise using wearable electrocardiogram

Published 2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Jongdoo Choi, Lanmi Hwang, Kunwook Jo, WooSik Yu, Heeseok Song Abstract We developed an algorithm that identifies the exercise levels and amount of exercise with high accuracy using the wearable electrocardiogram MC100 that can

Published

Author

Read next