Giovanni D’Addio

2.6k total citations
145 papers, 1.7k citations indexed

About

Giovanni D’Addio is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Cognitive Neuroscience. According to data from OpenAlex, Giovanni D’Addio has authored 145 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Biomedical Engineering, 53 papers in Cardiology and Cardiovascular Medicine and 25 papers in Cognitive Neuroscience. Recurrent topics in Giovanni D’Addio's work include Heart Rate Variability and Autonomic Control (48 papers), Muscle activation and electromyography studies (25 papers) and Non-Invasive Vital Sign Monitoring (22 papers). Giovanni D’Addio is often cited by papers focused on Heart Rate Variability and Autonomic Control (48 papers), Muscle activation and electromyography studies (25 papers) and Non-Invasive Vital Sign Monitoring (22 papers). Giovanni D’Addio collaborates with scholars based in Italy, Australia and United States. Giovanni D’Addio's co-authors include Mario Cesarelli, Leandro Donisi, Giuseppe Cesarelli, Armando Coccia, Roberto Maestri, Gaetano Pagano, Paolo Bifulco, Carlo Ricciardi, Federica Amitrano and Gian Domenico Pinna and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and European Respiratory Journal.

In The Last Decade

Giovanni D’Addio

130 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Giovanni D’Addio Italy 22 651 581 250 234 183 145 1.7k
Jurandir Nadal Brazil 20 572 0.9× 277 0.5× 205 0.8× 376 1.6× 126 0.7× 109 1.5k
Sandro Fioretti Italy 26 1.2k 1.8× 393 0.7× 378 1.5× 511 2.2× 93 0.5× 175 2.1k
Francesco Di Nardo Italy 23 828 1.3× 312 0.5× 235 0.9× 263 1.1× 47 0.3× 129 1.6k
Jennifer M. Yentes United States 18 457 0.7× 294 0.5× 302 1.2× 468 2.0× 40 0.2× 54 1.5k
Denise McGrath Ireland 19 589 0.9× 229 0.4× 339 1.4× 577 2.5× 52 0.3× 48 1.7k
Richard K. Shields United States 35 1.2k 1.9× 225 0.4× 274 1.1× 161 0.7× 250 1.4× 157 4.3k
Anthony P. Marsh United States 40 769 1.2× 342 0.6× 237 0.9× 695 3.0× 46 0.3× 109 4.0k
Maria Romano Italy 23 513 0.8× 330 0.6× 138 0.6× 87 0.4× 82 0.4× 100 1.4k
Justin J. Kavanagh Australia 22 948 1.5× 173 0.3× 236 0.9× 811 3.5× 205 1.1× 80 2.2k
Johannes B. Bussmann Netherlands 30 679 1.0× 133 0.2× 133 0.5× 360 1.5× 272 1.5× 54 2.5k

Countries citing papers authored by Giovanni D’Addio

Since Specialization
Citations

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

Fields of papers citing papers by Giovanni D’Addio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Giovanni D’Addio. 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 Giovanni D’Addio. The network helps show where Giovanni D’Addio may publish in the future.

Co-authorship network of co-authors of Giovanni D’Addio

This figure shows the co-authorship network connecting the top 25 collaborators of Giovanni D’Addio. A scholar is included among the top collaborators of Giovanni D’Addio 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 Giovanni D’Addio. Giovanni D’Addio 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.
Iuppariello, Luigi, Giovanni D’Addio, Maria Romano, et al.. (2025). Analysis of reaching movements of upper arm in robot assisted exercises. 38(2). 116–127.
2.
3.
Ferraro, Simona Del, et al.. (2025). On the Enhancement of the Long-Term Washability of e-Textile Realized with Electrically Conductive Graphene-Based Inks. Polymers. 17(7). 904–904. 1 indexed citations
4.
Falcone, Tommaso, et al.. (2024). Deep learning algorithms for the recognition of human movements in work activities. Gait & Posture. 114. S20–S21.
5.
Bevilacqua, Vitoantonio, et al.. (2024). A Novel Framework Based on Deep Learning Architecture for Continuous Human Activity Recognition with Inertial Sensors. Sensors. 24(7). 2199–2199. 8 indexed citations
6.
Colucci, Simona, Gaetano Pagano, Maria Aliani, et al.. (2024). Enhancing Survival Analysis Model Selection through XAI(t) in Healthcare. Applied Sciences. 14(14). 6084–6084. 5 indexed citations
7.
Coccia, Armando, et al.. (2024). Biomechanical Effects of Using a Passive Exoskeleton for the Upper Limb in Industrial Manufacturing Activities: A Pilot Study. Sensors. 24(5). 1445–1445. 12 indexed citations
8.
Coccia, Armando, et al.. (2024). Experimental Development and Validation of an E-Textile Sleeve for Surface Electromyography. SHILAP Revista de lepidopterología. 40–40. 2 indexed citations
9.
Amitrano, Federica, et al.. (2024). Measuring Surface Electromyography with Textile Electrodes in a Smart Leg Sleeve. Sensors. 24(9). 2763–2763. 2 indexed citations
10.
Cesarelli, Giuseppe, Leandro Donisi, Francesco Amato, et al.. (2023). Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 1056–1063. 13 indexed citations
11.
Ponsiglione, Alfonso Maria, Carlo Ricciardi, Francesco Amato, et al.. (2022). Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease. Sensors. 22(5). 1708–1708. 11 indexed citations
12.
D’Addio, Giovanni, Leandro Donisi, Giuseppe Cesarelli, et al.. (2021). Extracting Features from Poincaré Plots to Distinguish Congestive Heart Failure Patients According to NYHA Classes. Bioengineering. 8(10). 138–138. 20 indexed citations
13.
Coccia, Armando, Federica Amitrano, Leandro Donisi, et al.. (2021). Design and validation of an e-textile-based wearable system for remote health monitoring. ACTA IMEKO. 10(2). 220–220. 15 indexed citations
14.
Esposito, Daniele, Sergio Savino, Emilio Andreozzi, et al.. (2021). Evaluation of Grip Force and Energy Efficiency of the “Federica” Hand. Machines. 9(2). 25–25. 13 indexed citations
15.
Cesarelli, Giuseppe, Leandro Donisi, Armando Coccia, et al.. (2021). The E-Textile for Biomedical Applications: A Systematic Review of Literature. Diagnostics. 11(12). 2263–2263. 19 indexed citations
16.
17.
D’Addio, Giovanni, et al.. (2019). Development of a Prototype E-Textile Sock. PubMed. 2019. 1749–1752. 19 indexed citations
18.
Iuppariello, Luigi, Giovanni D’Addio, Bernardo Lanzillo, et al.. (2019). A novel approach to estimate the upper limb reaching movement in three-dimensional space. Informatics in Medicine Unlocked. 15. 100155–100155. 10 indexed citations
19.
D’Addio, Giovanni, Graziamaria Corbi, Mario Cesarelli, et al.. (2017). Aging and cardiac autonomic control in chronic heart failure: methods and clinical implications. 65(1). 38–47. 2 indexed citations
20.
Accardo, Agostino, et al.. (2010). Relationship between fractal dimension and power-law exponent of heart rate variability in normal and heart failure subjects. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 37. 935–938. 16 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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