Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects-Reference-Cited by-同舟云学术

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Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects

Published:2015-07-02 Issue:4 Volume:2 Page:89-94
ISSN:2053-3713
Container-title:Healthcare Technology Letters
language:en
Short-container-title:Healthcare Technology Letters

Author:

Melillo Paolo¹²^ORCID,Jovic Alan³,De Luca Nicola⁴,Pecchia Leandro⁵

Affiliation:

1. Multidisciplinary Department of Medical, Surgical and Dental Sciences Second University of Naples Via S. Pansini, 5 Naples 80138 Italy

2. SHARE Project, Italian Ministry of Education Scientific Research and University Rome Italy

3. Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 HR‐10000 Zagreb Croatia

4. Department of Translational Medical Sciences University of Naples Federico II Via S. Pansini, 5 Naples 80138 Italy

5. School of Engineering University of Warwick Coventry CV4 7AL UK

Publisher

Institution of Engineering and Technology (IET)

Subject

Health Information Management,Health Informatics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/htl.2015.0012

Reference54 articles.

1. The Patient Who Falls

2. The Patient Who Falls

3. Health care and socioeconomic impact of falls in the elderly

4. Epidemiology of Falls in Older Age

Cited by 12 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. Effects of continuous supplementation of Acanthopanax senticosus Harms on the cardiac autonomic function of community-dwelling elderly individuals during resting and standing tests: a randomized controlled trial;Frontiers in Cardiovascular Medicine;2024-03-08

2. A machine learning approach to identify fall risk for older adults;Smart Health;2022-12

3. Ultra-short-term heart rate variability analysis: comparison between Poincare and frequency domain methods;IEEE Latin America Transactions;2022-01

4. A systematic mapping study for ensemble classification methods in cardiovascular disease;Artificial Intelligence Review;2020-10-01

5. Statistical Analysis on Heart Rate Variability for Graded Cardiopulmonary Groups with Different Exercise Intensities;Journal of Medical and Biological Engineering;2020-03-09

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