Joe Paradiso

19 papers receiving 1.0k citations

Hit Papers

Gait Analysis Using a Shoe-Integrated Wireless Sensor System20082026201420202008100200300400500

Peers

Joe Paradiso
Comparison fields: 5 of 112
  • Biomedical Engineering 492
  • Human-Computer Interaction 340
  • Computer Vision and Pattern Recognition 282
  • Cognitive Neuroscience 205
  • Physical Therapy, Sports Therapy and Rehabilitation 197
Replace Ari Y. Benbasat with:
Ari Y. Benbasat United States
Marc Bächlin Switzerland
Yu‐Liang Hsu Taiwan
Peter B. Shull China
Franck Multon France
Gabriele Bleser Germany
Albert Samà Spain
Nicola Carbonaro Italy
F. Lorussi Italy
Sunghoon Ivan Lee United States
Joe Paradiso relative to Ari Y. Benbasat United States Ari Y. Benbasat's profile →
Citations per field
00.5×2.9×
Ari Y. Benbasat · 1×
Citations per year

Countries citing papers authored by Joe Paradiso

Since Specialization
Citations

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

Fields of papers citing papers by Joe Paradiso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joe Paradiso

This figure shows the co-authorship network connecting the top 25 collaborators of Joe Paradiso. A scholar is included among the top collaborators of Joe Paradiso 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 Joe Paradiso. Joe Paradiso is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 4
2 1
3 11
4 1
5 3
6
Proceedings of the Seventh International Conference on the Internet of Things (IOT 2017)
6
7 39
8 1
9 59
10 3
11 5
12
Gait Analysis Using a Shoe-Integrated Wireless Sensor Systembreakdown →
545
13 7
14
Proceedings of the 5th international conference on Information processing in sensor networks
95
15 4
16 37
17 69
18 199
19 17

About Joe Paradiso

Joe Paradiso is a scholar working on Human-Computer Interaction, General Dentistry and Cognitive Neuroscience, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Music Technology and Sound Studies (5 papers), Interactive and Immersive Displays (5 papers) and Tactile and Sensory Interactions (5 papers). The work is most often cited by research in Human-Computer Interaction (340 citations), Physical Therapy, Sports Therapy and Rehabilitation (197 citations) and Computer Vision and Pattern Recognition (282 citations). Joe Paradiso has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Ari Y. Benbasat, Donna Moxley Scarborough, Stacy Bamberg, David E. Krebs, Hiroshi Ishii, Craig Wisneski, Phillip B. Gibbons, Stephen B. Wicker, John A. Stankovic and Pattie Maes. Their work appears in journals such as IBM Systems Journal, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and IEEE Transactions on Information Technology in Biomedicine.

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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