Stephen Intille

146 papers receiving 6.2k citations

Stephen Intille's Hit Papers

Talk2Care: An LLM-based Voice Assistant for Communication between Healthcare Providers and Older Adults 2024 · 57 citations
570+6+12Years since publication100200300

Peers

Stephen Intille
Comparison fields: 5 of 167
  • Applied Psychology 721
  • Human-Computer Interaction 822
  • Computer Vision and Pattern Recognition 2.2k
  • Information Systems and Management 355
  • Transportation 282
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Citations per year

Countries citing papers authored by Stephen Intille

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Intille

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 149 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007336
2
Health and the Mobile Phone
Hit paper breakdown →
2008331
3 1999325
4
Activity Recognition Using a Single Accelerometer Placed at the Wrist or Ankle
Hit paper breakdown →
2013277
5 2002255
6 2005248
7 1999244
8 2013180
9 2002157
10 2015136
11 2019125
12 2005124
13 2015122
14 2010119
15
A framework for recognizing multi-agent action from visual evidence
1999114
16 2004113
17 2001111
18 2003110
19 2010107
20 201594

About Stephen Intille

Stephen Intille is a scholar working on Computer Vision and Pattern Recognition, General Health Professions, Physiology, Human-Computer Interaction and Applied Psychology, having authored 149 papers that have together received 6.6k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (33 papers), Physical Activity and Health (26 papers), Mobile Health and mHealth Applications (25 papers), Innovative Human-Technology Interaction (17 papers), Behavioral Health and Interventions (16 papers), Mental Health Research Topics (14 papers), Obesity, Physical Activity, Diet (12 papers) and Digital Mental Health Interventions (9 papers). The work is most often cited by research in Applied Psychology (721 citations), Human-Computer Interaction (822 citations), Computer Vision and Pattern Recognition (2.2k citations), Information Systems and Management (355 citations) and Transportation (282 citations). Stephen Intille has collaborated with scholars based in United States, Italy and Mexico. Frequent co-authors include Aaron Bobick, Genevieve F. Dunton, William L. Haskell, Fahd Albinali, Mary E. Rosenberger, Yue Liao, Kevin Patrick, Emmanuel Munguia Tapia, Kent Larson and Andrea Mannini. Their work appears in journals such as Medicine & Science in Sports & Exercise, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Journal of Physical Activity and Health, Translational Behavioral Medicine and IEEE Pervasive Computing.

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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