Mika Luimula

89 papers receiving 678 citations

Peers

Mika Luimula
Comparison fields: 5 of 98
  • Human-Computer Interaction 191
  • Neuropsychology and Physiological Psychology 16
  • Demography 109
  • Computer Vision and Pattern Recognition 175
  • Developmental and Educational Psychology 81
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Costas Boletsis Norway
Shi Cao Canada
Noriaki Kuwahara Japan
William Mann United States
Lynne Baillie United Kingdom
Paulo Menezes Portugal
Maja Matarić United States
Elena Mugellini Switzerland
Burkhard C. Wünsche New Zealand
Swamy Ananthanarayan Germany
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Citations per year

Countries citing papers authored by Mika Luimula

Since Specialization
Citations

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

Fields of papers citing papers by Mika Luimula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201942
2 201735
3 201731
4 201225
5 202324
6 202021
7
Virtual reality as a communication tool for fire safety - Experiences from the VirPa project.
201921
8
When Japanese elderly people play a Finnish physical exercise game: a usability study
201620
9 202318
10 200917
11 201517
12 201917
13 202016
14 201716
15 201915
16 201715
17 201114
18 201514
19 201613
20
Social service robots in public and private environments
201212

About Mika Luimula

Mika Luimula is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction, Control and Systems Engineering, Social Psychology and Developmental and Educational Psychology, having authored 97 papers that have together received 738 indexed citations. Recurring topics across this work include Augmented Reality Applications (16 papers), Virtual Reality Applications and Impacts (15 papers), Context-Aware Activity Recognition Systems (14 papers), Robotics and Automated Systems (14 papers), Technology Use by Older Adults (11 papers), Physical Activity and Health (10 papers), Educational Games and Gamification (10 papers) and Human-Automation Interaction and Safety (7 papers). The work is most often cited by research in Human-Computer Interaction (191 citations), Neuropsychology and Physiological Psychology (16 citations), Demography (109 citations), Computer Vision and Pattern Recognition (175 citations) and Developmental and Educational Psychology (81 citations). Mika Luimula has collaborated with scholars based in Finland, Japan and United Kingdom. Frequent co-authors include Aung Pyae, Jouni Smed, Evangelos Markopoulos, Sakari Pieskä, Niina Katajapuu, Timo Partala, Panagiotis Markopoulos, Jinhui Li, Tan Phat Pham and Yin‐Leng Theng. Their work appears in journals such as Journal of the Association for Information Systems, Scandinavian Journal of Psychology, Electronics, Personal and Ubiquitous Computing and Future Internet.

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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