Matteo Migliorini

540 total citations
21 papers, 392 citations indexed

About

Matteo Migliorini is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Matteo Migliorini has authored 21 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cardiology and Cardiovascular Medicine, 10 papers in Cognitive Neuroscience and 9 papers in Biomedical Engineering. Recurrent topics in Matteo Migliorini's work include EEG and Brain-Computer Interfaces (9 papers), Heart Rate Variability and Autonomic Control (8 papers) and Non-Invasive Vital Sign Monitoring (7 papers). Matteo Migliorini is often cited by papers focused on EEG and Brain-Computer Interfaces (9 papers), Heart Rate Variability and Autonomic Control (8 papers) and Non-Invasive Vital Sign Monitoring (7 papers). Matteo Migliorini collaborates with scholars based in Italy, United States and Finland. Matteo Migliorini's co-authors include Rosalind W. Picard, Giulia Regalia, Anna Maria Bianchi, Francesco Onorati, Chiara Caborni, Daniel Friedman, Elizabeth D. Mynatt, Andrew S. Blum, Ming‐Zher Poh and Jonathan Bidwell and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Neurology.

In The Last Decade

Matteo Migliorini

20 papers receiving 383 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matteo Migliorini Italy 10 218 158 98 98 53 21 392
Miho Miyajima Japan 10 214 1.0× 91 0.6× 64 0.7× 154 1.6× 41 0.8× 31 378
Deniz Tunçel Türkiye 14 127 0.6× 133 0.8× 36 0.4× 28 0.3× 50 0.9× 52 459
Vanessa Scarapicchia Canada 6 161 0.7× 133 0.8× 57 0.6× 101 1.0× 18 0.3× 12 386
Rachel E. Stirling Australia 8 265 1.2× 222 1.4× 20 0.2× 49 0.5× 16 0.3× 17 347
Akihide Kinoshita Japan 11 269 1.2× 72 0.5× 100 1.0× 155 1.6× 31 0.6× 12 466
Daniel E. Payne Australia 8 348 1.6× 243 1.5× 22 0.2× 39 0.4× 18 0.3× 9 444
Mami Fujibayashi Japan 12 49 0.2× 58 0.4× 75 0.8× 143 1.5× 47 0.9× 36 422
Kristinn Johnsen Iceland 8 282 1.3× 100 0.6× 16 0.2× 45 0.5× 37 0.7× 14 379
Rima El Atrache United States 12 373 1.7× 296 1.9× 54 0.6× 104 1.1× 24 0.5× 20 502

Countries citing papers authored by Matteo Migliorini

Since Specialization
Citations

This map shows the geographic impact of Matteo Migliorini'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 Matteo Migliorini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Migliorini more than expected).

Fields of papers citing papers by Matteo Migliorini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matteo Migliorini. 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 Matteo Migliorini. The network helps show where Matteo Migliorini may publish in the future.

Co-authorship network of co-authors of Matteo Migliorini

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Migliorini. A scholar is included among the top collaborators of Matteo Migliorini based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matteo Migliorini. Matteo Migliorini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Migliorini, Matteo, Marco Ciulu, Roberto Chignola, et al.. (2024). Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions. Foods. 13(2). 243–243. 16 indexed citations
2.
Grosso, G., Matteo Migliorini, J. Pazzini, et al.. (2024). Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection. SHILAP Revista de lepidopterología. 295. 2033–2033. 1 indexed citations
3.
Migliorini, Matteo, et al.. (2023). Chemdeg, an R package for the analysis of foods isothermal degradation kinetics. Journal of Food Engineering. 363. 111778–111778.
4.
Chen, Weixuan, et al.. (2023). Prospective clinical validation of the Empatica EmbracePlus wristband as a reflective pulse oximeter. Frontiers in Digital Health. 5. 1258915–1258915. 10 indexed citations
5.
Martini, Chiara, et al.. (2022). COVID-19 outbreak impact on health professionals: A survey on the Italian radiographer experience. Journal of medical imaging and radiation sciences. 53(2). 212–218. 3 indexed citations
6.
Martini, Chiara, et al.. (2020). Phase 3 of COVID-19: Treat your patients and care for your radiographers. A designed projection for an aware and innovative radiology department. Journal of medical imaging and radiation sciences. 51(4). 531–534. 1 indexed citations
7.
Regalia, Giulia, Matteo Migliorini, Matteo Lai, et al.. (2020). Sleep assessment by means of a wrist actigraphy-based algorithm: agreement with polysomnography in an ambulatory study on older adults. Chronobiology International. 38(3). 400–414. 15 indexed citations
8.
Picard, Rosalind W., Matteo Migliorini, Chiara Caborni, et al.. (2017). Wrist sensor reveals sympathetic hyperactivity and hypoventilation before probable SUDEP. Neurology. 89(6). 633–635. 50 indexed citations
9.
Onorati, Francesco, Giulia Regalia, Chiara Caborni, et al.. (2017). Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors. Epilepsia. 58(11). 1870–1879. 158 indexed citations
10.
Aktaruzzaman, Md, Matteo Migliorini, M. Tenhunen, et al.. (2015). The addition of entropy-based regularity parameters improves sleep stage classification based on heart rate variability. Medical & Biological Engineering & Computing. 53(5). 415–425. 28 indexed citations
11.
Cabiddu, Ramona, Renata Trimer, Audrey Borghi‐Silva, et al.. (2015). Are Complexity Metrics Reliable in Assessing HRV Control in Obese Patients During Sleep?. PLoS ONE. 10(4). e0124458–e0124458. 9 indexed citations
12.
Migliorini, Matteo, Sara Mariani, Gilles Bertschy, Markus Kosel, & Anna Maria Bianchi. (2015). Can home-monitoring of sleep predict depressive episodes in bipolar patients?. PubMed. 10. 2215–2218. 4 indexed citations
13.
Migliorini, Matteo, Sara Mariani, & Anna Maria Bianchi. (2013). Decision tree for smart feature extraction from sleep HR in bipolar patients. PubMed. 278. 5033–5036. 2 indexed citations
14.
Mariani, Sara, et al.. (2012). Optimization of Time-Variant Autoregressive Models for tracking REM - non REM transitions during sleep. PubMed. 4. 2236–2239. 2 indexed citations
15.
Migliorini, Matteo. (2012). Study of Heart Rate Variability in bipolar disorder: linear and nonlinear parameters during sleep. PubMed. 4. 22–22. 25 indexed citations
16.
Migliorini, Matteo, Ramona Cabiddu, S. Cerutti, et al.. (2011). Automatic arrhythmia detection based on heart beat interval series recorded through bed sensors during sleep. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 337–340. 4 indexed citations
17.
Migliorini, Matteo, et al.. (2010). Automatic sleep staging based on ballistocardiographic signals recorded through bed sensors. PubMed. 2010. 3273–3276. 38 indexed citations
18.
Méndez, Martín O., et al.. (2010). Evaluation of the sleep quality based on bed sensor signals: Time-variant analysis. PubMed. 240. 3994–3997. 12 indexed citations
19.
Migliorini, Matteo, et al.. (2010). Time-frequency analysis of the ballistocardiogram for sleep staging. 1 indexed citations
20.
Ramiréz, Agustín J., et al.. (1991). Non-modulating essential hypertension: renal hemodynamic effects of long-term angiotensin converting enzyme inhibition.. PubMed. 9(6). S396–7. 6 indexed citations

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.

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