Fernando Andreotti

2.8k citations

27 papers · 1.9k indexed · 2 hit papers · h-index 16

Impact in

Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces
- Sleep and Wakefulness Research
Signal Processing top 1%
- Blind Source Separation Techniques

Papers in ⓘ

Cognitive Neuroscience 16
- EEG and Brain-Computer Interfaces 14
- Sleep and Wakefulness Research 6
Cardiology and Cardiovascular Medicine 13
- ECG Monitoring and Analysis 11
- Heart Rate Variability and Autonomic Control 3
- Cardiac Arrhythmias and Treatments 2

Co-authors: Maarten De Vos (13 shared papers)Navin Cooray (8 shared papers)Huy Phan (6 shared papers)Oliver Y. Chén (4 shared papers)Sebastian Zaunseder (9 shared papers)Joachim A. Behar (5 shared papers)Julien Oster (5 shared papers)Gari D. Clifford (4 shared papers)
Journals: Physiological Measurement (5 papers)IEEE Transactions on Biomedical Engineering (3 papers)Clinical Neurophysiology (2 papers)IEEE Transactions on Neural Systems and Rehabilitation Engineering (1 paper)Scientific Reports (1 paper)
Partner nations: United Kingdom Germany United States

In The Last Decade

Fernando Andreotti

27 papers receiving 1.9k citations

Hit Papers

align trajectories log scale

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging 2019 · 375 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2019 IEEE Transactions on Neural Systems and Rehabilitation Engineering
2018 IEEE Transactions on Biomedical Engineering

Peers

Countries citing papers authored by Fernando Andreotti

Since Specialization

Citations

This map shows the geographic impact of Fernando Andreotti's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fernando Andreotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Andreotti more than expected).

Fields of papers citing papers by Fernando Andreotti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Andreotti. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fernando Andreotti. The network helps show where Fernando Andreotti may publish in the future.

Co-authors

The 25 scholars most cited alongside Fernando Andreotti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fernando Andreotti Line = papers co-authored together Fernando Andreotti links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging IEEE Transactions on Neural Systems and Rehabilitation Engineering ·Huy Phan, Fernando Andreotti, Navin Cooray, Oliver Y. Chén, Maarten De Vos Hit paper breakdown →	2019	375
2	Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification IEEE Transactions on Biomedical Engineering ·Huy Phan, Fernando Andreotti, Navin Cooray, Oliver Y. Chén, Maarten De Vos Hit paper breakdown →	2018	329
3	An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms Physiological Measurement ·Fernando Andreotti, Joachim A. Behar, Sebastian Zaunseder, Julien Oster, Gari D. Clifford	2016	135
4	Comparing Feature Based Classifiers and Convolutional Neural Networks to Detect Arrhythmia from Short Segments of ECG Computing in cardiology ·Fernando Andreotti, Oliver Carr, Marco A. F. Pimentel, Adam Mahdi, Maarten De Vos	2017	124
5	A practical guide to non-invasive foetal electrocardiogram extraction and analysis Physiological Measurement ·Joachim A. Behar, Fernando Andreotti, Sebastian Zaunseder, Julien Oster, Gari D. Clifford	2016	105
6	Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks PubMed ·Huy Phan, Fernando Andreotti, Navin Cooray, Oliver Y. Chén, Maarten De Vos	2018	99
7	Robust fetal ECG extraction and detection from abdominal leads Physiological Measurement ·Fernando Andreotti, Maik Riedl, Tilo Himmelsbach, Daniel Wedekind, Niels Wessel, Holger Stepan, Claudia Schmieder, A Jank, Hagen Malberg, Sebastian Zaunseder	2014	81
8	An ECG simulator for generating maternal-foetal activity mixtures on abdominal ECG recordings Physiological Measurement ·Joachim A. Behar, Fernando Andreotti, Sebastian Zaunseder, Qiao Li, Julien Oster, Gari D. Clifford	2014	79
9	Multimodal heart beat detection using signal quality indices Physiological Measurement ·Alistair E. W. Johnson, Joachim A. Behar, Fernando Andreotti, Gari D. Clifford, Julien Oster	2015	78
10	Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks PubMed ·Fernando Andreotti, Huy Phan, Navin Cooray, Christine Lo, (unknown), Maarten De Vos	2018	72
11	DNN Filter Bank Improves 1-Max Pooling CNN for Single-Channel EEG Automatic Sleep Stage Classification PubMed ·Huy Phan, Fernando Andreotti, Navin Cooray, Oliver Y. Chén, Maarten De Vos	2018	66
12	Early risk assessment for COVID-19 patients from emergency department data using machine learning Scientific Reports ·Frank S. Heldt, Marcela P. Vizcaychipi, Sophie Peacock, Mattia Cinelli, Lachlan McLachlan, Fernando Andreotti, Stojan Jovanović, Robert Dürichen, N. A. Lipunova, Robert A. Fletcher, Anne Hancock, Alex McCarthy, Richard A. Pointon, Alexander Brown, James Eaton, Roberto Liddi, Lucy Mackillop, Lionel Tarassenko, Rabia Khan	2021	63
13	Detection of REM sleep behaviour disorder by automated polysomnography analysis Clinical Neurophysiology ·Navin Cooray, Fernando Andreotti, Christine Lo, Mkael Symmonds, (unknown), Maarten De Vos	2019	60
14	Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data IEEE Transactions on Biomedical Engineering ·John Prince, Fernando Andreotti, Maarten De Vos	2018	59
15	Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart Rate Estimation IEEE Transactions on Biomedical Engineering ·Fernando Andreotti, Felix Gräßer, Hagen Malberg, Sebastian Zaunseder	2017	55
16	Maternal signal estimation by Kalman filtering and Template Adaptation for fetal heart rate extraction OPUS (Augsburg University) ·Fernando Andreotti, Maik Riedl, Tilo Himmelsbach, Daniel Wedekind, Sebastian Zaunseder, Niels Wessel, Hagen Malberg	2013	25
17	Visualising Convolutional Neural Network Decisions in Automatic Sleep Scoring Kent Academic Repository (University of Kent) ·Fernando Andreotti, Huy Phan, Maarten De Vos	2018	15
18	From angiotensin-converting enzyme 2 disruption to thromboinflammatory microvascular disease: A paradigm drawn from COVID-19 International Journal of Cardiology ·Ramona Vinci, Daniela Pedicino, Fernando Andreotti, Gianluca Russo, Alessia d’Aiello, Raimondo De Cristofaro, Filippo Crea, Giovanna Liuzzo	2020	14
19	Proof of concept: Screening for REM sleep behaviour disorder with a minimal set of sensors Clinical Neurophysiology ·Navin Cooray, Fernando Andreotti, Christine Lo, Mkael Symmonds, (unknown), Maarten De Vos	2021	11
20	Linking Changes in Heart Rate Variability to Mood Changes in Daily Life Computing in cardiology ·Oliver Carr, Fernando Andreotti, Kate Saunders, Amy C. Bilderbeck, Guy Goodwin, Maarten De Vos	2017	11

About Fernando Andreotti

Fernando Andreotti is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Signal Processing and Experimental and Cognitive Psychology, having authored 27 papers that have together received 1.9k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (14 papers), ECG Monitoring and Analysis (11 papers), Sleep and Wakefulness Research (6 papers), Non-Invasive Vital Sign Monitoring (5 papers), Blind Source Separation Techniques (3 papers), COVID-19 and healthcare impacts (3 papers), Heart Rate Variability and Autonomic Control (3 papers) and Cardiac Arrhythmias and Treatments (2 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), Signal Processing (465 citations), Cardiology and Cardiovascular Medicine (733 citations), Experimental and Cognitive Psychology (316 citations) and Human-Computer Interaction (114 citations). Fernando Andreotti has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Maarten De Vos, Navin Cooray, Huy Phan, Oliver Y. Chén, Sebastian Zaunseder, Joachim A. Behar, Julien Oster, Gari D. Clifford, Hagen Malberg and Christine Lo. Their work appears in journals such as Physiological Measurement, IEEE Transactions on Biomedical Engineering, Clinical Neurophysiology, IEEE Transactions on Neural Systems and Rehabilitation Engineering and Scientific Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact