A. Macerata

1.3k citations
70 papers · 1.0k · h-index 17

Impact in

Papers in

A. Macerata

64 papers receiving 975 citations

Peers

A. Macerata
Comparison fields: 5 of 107
  • Cardiology and Cardiovascular Medicine 629
  • Equine 24
  • Signal Processing 98
  • Cognitive Neuroscience 163
  • Health Information Management 26
Replace M. Varanini with:
M. Varanini Italy
Joachim A. Behar Israel
N. Ty Smith United States
M.G. Signorini Italy
Jarosław Piskorski Poland
Peter Walter Kamen Australia
Rodrigo Varejão Andreão Brazil
Katerina Hnatkova United Kingdom
Petra Barthel Germany
Kang-Ming Chang Taiwan
A. Macerata relative to M. Varanini Italy M. Varanini's profile →
Citations per field
00.5×8.7×
M. Varanini · 1×
Citations per year

Countries citing papers authored by A. Macerata

Since Specialization
Citations

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

Fields of papers citing papers by A. Macerata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside A. Macerata, 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 A. Macerata Line = papers co-authored together A. Macerata links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001188
2 199691
3 201478
4 199972
5 200558
6 200445
7
A multi-step approach for non-invasive fetal ECG analysis
201339
8 200639
9 201332
10 200232
11 201330
12 200829
13 198925
14 201623
15 200820
16 200217
17 200216
18 198813
19
Can hypnosis modify the sympathetic-parasympathetic balance at heart level?
199213
20 199412

About A. Macerata

A. Macerata is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering, Surgery, Health Information Management and Cognitive Neuroscience, having authored 70 papers that have together received 1.0k indexed citations. Recurring topics across this work include Heart Rate Variability and Autonomic Control (29 papers), Non-Invasive Vital Sign Monitoring (15 papers), ECG Monitoring and Analysis (15 papers), Electronic Health Records Systems (8 papers), Healthcare Technology and Patient Monitoring (7 papers), Cardiovascular Syncope and Autonomic Disorders (6 papers), EEG and Brain-Computer Interfaces (5 papers) and Cardiac Imaging and Diagnostics (5 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (629 citations), Equine (24 citations), Signal Processing (98 citations), Cognitive Neuroscience (163 citations) and Health Information Management (26 citations). A. Macerata has collaborated with scholars based in Italy, Sweden and Greece. Frequent co-authors include Michele Emdin, M. Varanini, R. Balocchi, Carlo Marchesi, Clara Carpeggiani, Antonio L’Abbate, Amalia Gastaldelli, Stefania Camastra, Ele Ferrannini and Andrea Natali. Their work appears in journals such as Clinical Autonomic Research, Experimental Brain Research, Journal of Voice, Chaos An Interdisciplinary Journal of Nonlinear Science and International Journal of Cardiology.

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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