https://github.com/chengding0713/awesome-ppg-af-detection
End-to-end Deep Learning from Raw Sensor Data: Atrial Fibrillation Detection using Wearables
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Photoplethysmography (PPG) is a non-invasive light-based method that has been used since the 1930s for monitoring cardiovascular activity.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
End-to-end Deep Learning from Raw Sensor Data: Atrial Fibrillation Detection using Wearables
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings
ECG Classification System for Arrhythmia Detection Using Convolutional Neural Networks
Heart Rate Estimation from Ballistocardiography Based on Hilbert Transform and Phase Vocoder
Non-contact photoplethysmogram and instantaneous heart rate estimation from infrared face video
ECG beats classification via online sparse dictionary and time pyramid matching
Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable
Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.