Reinder Haakma

1.2k total citations
55 papers, 837 citations indexed

About

Reinder Haakma is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Reinder Haakma has authored 55 papers receiving a total of 837 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 20 papers in Biomedical Engineering and 18 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Reinder Haakma's work include Non-Invasive Vital Sign Monitoring (19 papers), Heart Rate Variability and Autonomic Control (16 papers) and EEG and Brain-Computer Interfaces (12 papers). Reinder Haakma is often cited by papers focused on Non-Invasive Vital Sign Monitoring (19 papers), Heart Rate Variability and Autonomic Control (16 papers) and EEG and Brain-Computer Interfaces (12 papers). Reinder Haakma collaborates with scholars based in Netherlands, Finland and Germany. Reinder Haakma's co-authors include Ronald M. Aarts, Pedro Fonseca, Xi Long, Jérôme Foussier, Mustafa Radha, D.G. Bouwhuis, Willem‐Paul Brinkman, F.L. Engel, Sebastiaan Overeem and Peter J. J. Goossens and has published in prestigious journals such as Applied Physics Letters, BMJ Open and Journal of the Royal Statistical Society Series C (Applied Statistics).

In The Last Decade

Reinder Haakma

51 papers receiving 803 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Reinder Haakma Netherlands 16 401 377 264 183 181 55 837
Xosé A. Vila Spain 18 256 0.6× 376 1.0× 604 2.3× 73 0.4× 79 0.4× 61 1.0k
Takashi Nakamura United Kingdom 10 334 0.8× 189 0.5× 93 0.4× 70 0.4× 86 0.5× 19 534
Beena Ahmed Qatar 18 354 0.9× 189 0.5× 184 0.7× 150 0.8× 363 2.0× 105 1.2k
Ryan Runge United States 6 97 0.2× 358 0.9× 215 0.8× 102 0.6× 77 0.4× 8 976
Pedro Fonseca Netherlands 24 859 2.1× 857 2.3× 556 2.1× 673 3.7× 472 2.6× 95 1.7k
Francesca Dalia Faraci Switzerland 11 393 1.0× 186 0.5× 65 0.2× 137 0.7× 120 0.7× 30 1.1k
Remo Mueller United States 5 410 1.0× 150 0.4× 116 0.4× 378 2.1× 285 1.6× 8 823
Daniel Mobley United States 6 425 1.1× 154 0.4× 115 0.4× 411 2.2× 292 1.6× 8 811
Arturo Martínez‐Rodrigo Spain 18 562 1.4× 240 0.6× 552 2.1× 40 0.2× 349 1.9× 81 1.2k
Jan C. Brammer Netherlands 4 262 0.7× 203 0.5× 360 1.4× 20 0.1× 169 0.9× 4 732

Countries citing papers authored by Reinder Haakma

Since Specialization
Citations

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

Fields of papers citing papers by Reinder Haakma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reinder Haakma

This figure shows the co-authorship network connecting the top 25 collaborators of Reinder Haakma. A scholar is included among the top collaborators of Reinder Haakma 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 Reinder Haakma. Reinder Haakma 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.
Peri, Elisabetta, et al.. (2024). Increasing accuracy of pulse arrival time estimation in low frequency recordings. Physiological Measurement. 45(3). 03NT01–03NT01.
2.
Bak, Marieke, Mirela Habibović, Willem J. Kop, et al.. (2024). Rationale and design of the BECA project: Smartwatch-based activation of the chain of survival for out-of-hospital cardiac arrest. Resuscitation Plus. 17. 100576–100576. 9 indexed citations
3.
Regis, Marta, et al.. (2023). Model-based detection and classification of premature contractions from photoplethysmography signals. Journal of the Royal Statistical Society Series C (Applied Statistics). 72(5). 1235–1259. 2 indexed citations
4.
5.
Radha, Mustafa, Nikita B Rajani, Pedro Fonseca, et al.. (2019). Estimating blood pressure trends and the nocturnal dip from photoplethysmography. Physiological Measurement. 40(2). 25006–25006. 61 indexed citations
6.
Gilst, Merel M. van, Johannes van Dijk, Pedro Fonseca, et al.. (2019). Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring. BMJ Open. 9(11). e030996–e030996. 45 indexed citations
7.
Regis, Marta, et al.. (2019). The t linear mixed model: model formulation, identifiability and estimation. Communications in Statistics - Simulation and Computation. 51(5). 2318–2342. 3 indexed citations
8.
Radha, Mustafa, Nikita B Rajani, Pedro Fonseca, et al.. (2018). Wrist-worn blood pressure tracking in healthy free-living individuals using neural networks. arXiv (Cornell University). 2 indexed citations
9.
Regis, Marta, et al.. (2017). Determinants of perceived sleep quality in normal sleepers. Behavioral Sleep Medicine. 17(4). 388–397. 40 indexed citations
10.
Tax, Niek, Natalia Sidorova, Reinder Haakma, & Wil M. P. van der Aalst. (2016). Log-based Evaluation of Label Splits for Process Models. Procedia Computer Science. 96. 63–72. 4 indexed citations
11.
Long, Xi, et al.. (2014). Correlations between overnight breathing rate variation and subjective sleep quality scores. TU/e Research Portal. 25. 60–63. 1 indexed citations
12.
Long, Xi, Jérôme Foussier, Pedro Fonseca, Reinder Haakma, & Ronald M. Aarts. (2013). Respiration amplitude analysis for REM and NREM sleep classification. PubMed. 2013. 5017–5020. 16 indexed citations
13.
Brinkman, Willem‐Paul, Reinder Haakma, & D.G. Bouwhuis. (2008). The theoretical foundation and validity of a component-based usability questionnaire. Behaviour and Information Technology. 28(2). 121–137. 24 indexed citations
14.
Brinkman, Willem‐Paul, Reinder Haakma, & D.G. Bouwhuis. (2008). Component-Specific Usability Testing. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans. 38(5). 1143–1155. 14 indexed citations
15.
Brinkman, Willem‐Paul, Reinder Haakma, & D.G. Bouwhuis. (2004). Consistency: a factor that links the usability of individual interaction components together. A & A Case Reports. 5(10). 169–72. 3 indexed citations
16.
Brinkman, Willem‐Paul, Reinder Haakma, & D.G. Bouwhuis. (2004). USABILITY TESTING OF INTERACTION COMPONENTS Taking the Message Exchange as a Measure of Usability. TU/e Research Portal (Eindhoven University of Technology). 157–168. 5 indexed citations
17.
Brinkman, Willem‐Paul, et al.. (2004). Memory load: A factor that links the usability of individual interaction components together. TU/e Research Portal. 1 indexed citations
18.
Brinkman, Willem‐Paul, Reinder Haakma, & D.G. Bouwhuis. (2001). Usability evaluation of component-based user interfaces. TU/e Research Portal. 767–768. 2 indexed citations
19.
Haakma, Reinder. (1998). Layered feedback in user-system interaction. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 242(26). 2829–30. 6 indexed citations
20.
Engel, F.L. & Reinder Haakma. (1992). Layered approach in user-system interaction. TU/e Research Portal. 47(1). 63–80. 1 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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