Towards Feasible Home ECG Monitoring: AI-Driven Detection of Clinically Critical Arrhythmias Using Single-Lead Signals.

Hsu CH, Hsieh JC, Su PY, Yang CC

DOI: 10.3390/bioengineering13030317
Published: 2026 Mar 10
Container: Bioengineering (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/bioengineering13030317,
  title = {Towards Feasible Home ECG Monitoring: AI-Driven Detection of Clinically Critical Arrhythmias Using Single-Lead Signals.},
  author = {Hsu CH and Hsieh JC and Su PY and Yang CC},
  year = {2026},
  journal = {Bioengineering (Basel, Switzerland)},
  doi = {10.3390/bioengineering13030317},
  url = {https://doi.org/10.3390/bioengineering13030317}
}

RIS

TY  - JOUR
TI  - Towards Feasible Home ECG Monitoring: AI-Driven Detection of Clinically Critical Arrhythmias Using Single-Lead Signals.
AU  - Hsu CH
AU  - Hsieh JC
AU  - Su PY
AU  - Yang CC
PY  - 2026
JO  - Bioengineering (Basel, Switzerland)
DO  - 10.3390/bioengineering13030317
UR  - https://doi.org/10.3390/bioengineering13030317
ER  -

APA

CH, H., JC, H., PY, S., & CC, Y. (2026). Towards Feasible Home ECG Monitoring: AI-Driven Detection of Clinically Critical Arrhythmias Using Single-Lead Signals.. Bioengineering (Basel, Switzerland). https://doi.org/10.3390/bioengineering13030317

Source records

pubmed · retrieved 2026-09-26T06:06:50.409Z