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Efficient k-NN Implementation for Real-Time Detection of Cough Events in Smartphones

  • Published:2018-09 Issue:5 Volume:22 Page:1662-1671
  • ISSN:2168-2194
  • Container-title:IEEE Journal of Biomedical and Health Informatics
  • language:
  • Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Hoyos-Barcelo CarlosORCID,Monge-Alvarez JesusORCID,Zeeshan Shakir MuhammadORCID,Alcaraz-Calero Jose-Maria,Casaseca-de-la-Higuera PabloORCID

Funder

Digital Health & Care Institute Scotland

Factory Research Project SmartCough/MacMasters

NHS Research Scotland through Edinburgh Clinical Research Facility

Cancer Research U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Cited by 29 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. Internet of robotic things for independent living: Critical analysis and future directions;Internet of Things;2024-04

2. Feature evaluation of accelerometry signals for cough detection;Frontiers in Digital Health;2024-03-22

3. CASCO: A Contactless Cough Screening System Based on Audio Signal Processing;Advances in Computer Graphics;2023-12-24

4. Learning to Classify Cough Sounds with Dictionary-Guided Meta-Learning;2023 RIVF International Conference on Computing and Communication Technologies (RIVF);2023-12-23

5. Feasibility of Cough Detection and Classification Using Artificial Intelligence in an Ambulatory Setting with a Ceiling Mounted Microphone;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06
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