Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor-Reference-Cited by-同舟云学术

Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor

Published:2019-05 Issue:3 Volume:23 Page:1022-1031
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Acharya Sayandeep^ORCID,Mongan William M.^ORCID,Rasheed Ilhaan,Liu Yuqiao,Anday Endla,Dion Genevieve,Fontecchio Adam,Kurzweg Timothy,Dandekar Kapil R.^ORCID

Funder

National Science Foundation

National Institute of Biomedical Imaging and Bioengineering

Commonwealth of Pennsylvania

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Link

https://ieeexplore.ieee.org/ielaam/6221020/8705605/8416727-aam.pdf

Cited by 22 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The impact of contextual factors on the performance of human breath monitoring using flexible UHF RFID temperature sensing yarn and its underlying mechanisms;Sensors and Actuators A: Physical;2024-09

2. A Review of Patient Bed Sensors for Monitoring of Vital Signs;Sensors;2024-07-23

3. A Fusion Algorithm Based on a Constant Velocity Model for Improving the Measurement of Saccade Parameters with Electrooculography;Sensors;2024-01-15

4. Design and Implementation of Low-Cost Respiratory Rate Measurement Device;Arabian Journal for Science and Engineering;2023-12-28

5. Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology;Pediatric Research;2023-01