Dual Attention Network for Heart Rate and Respiratory Rate Estimation
Not on the map. Why?
Abstract (arXiv)
Heart rate and respiratory rate measurement is a vital step for diagnosing many diseases. Non-contact camera based physiological measurement is more accessible and convenient in Telehealth nowadays than contact instruments such as fingertip oximeters since non-contact methods reduce risk of infection. However, remote physiological signal measurement is challenging due to environment illumination variations, head motion, facial expression, etc. It's also desirable to have a unified network which could estimate both heart rate and respiratory rate to reduce system complexity and latency. We propose a convolutional neural network which leverages spatial attention and channel attention, which we call it dual attention network (DAN) to jointly estimate heart rate and respiratory rate with camera video as input. Extensive experiments demonstrate that our proposed system significantly improves heart rate and respiratory rate measurement accuracy.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 12 of its 28 references that are in the map. First posted on arXiv 31 Oct 2021.
Builds on
12 of 28 references.
References · 12
- 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
- 2017Squeeze-and-Excitation Networkscited by 4,789
- 2015Spatial Transformer Networkscited by 1,429
- 2018Dual Attention Network for Scene Segmentationcited by 1,003
- 2018TSM: Temporal Shift Module for Efficient Video Understandingcited by 856
- 2019ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networkscited by 575
- 2018DeepPhys: Video-Based Physiological Measurement Using Convolutional Attention Networkscited by 154
- 2020Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurementcited by 134
- 2019RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representationcited by 105
- 2019Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancementcited by 87
- 2017A Reproducible Study on Remote Heart Rate Measurementcited by 51
- 2018Skeleton-based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Modulecited by 13
Built on by
Citing papers per year: 2022: 1; 2023: 1.
2 papers.