Anouk Van de Vel

734 total citations
20 papers, 595 citations indexed

About

Anouk Van de Vel is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine and Psychiatry and Mental health. According to data from OpenAlex, Anouk Van de Vel has authored 20 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 9 papers in Cardiology and Cardiovascular Medicine and 8 papers in Psychiatry and Mental health. Recurrent topics in Anouk Van de Vel's work include EEG and Brain-Computer Interfaces (19 papers), Epilepsy research and treatment (8 papers) and ECG Monitoring and Analysis (7 papers). Anouk Van de Vel is often cited by papers focused on EEG and Brain-Computer Interfaces (19 papers), Epilepsy research and treatment (8 papers) and ECG Monitoring and Analysis (7 papers). Anouk Van de Vel collaborates with scholars based in Belgium and United States. Anouk Van de Vel's co-authors include Berten Ceulemans, Sabine Van Huffel, Bart Vanrumste, Bert Bonroy, Lieven Lagae, Kris Cuppens, Katrien Jansen, Lieven Lagae, Kristien Wouters and Katrien Smets and has published in prestigious journals such as IEEE Journal of Biomedical and Health Informatics, Epilepsy & Behavior and Artificial Intelligence in Medicine.

In The Last Decade

Anouk Van de Vel

20 papers receiving 582 citations

Peers

Anouk Van de Vel

PMH

CCM

CMN

Kris Cuppens Belgium

Lieven Lagae Belgium

Mona Nasseri United States

Evy Cleeren Belgium

Isa Conradsen Denmark

Rima El Atrache United States

Thomas De Cooman Belgium

Tilmann Kluge Austria

Kaat Vandecasteele Belgium

Petr Klimeš Czechia

Kris Cuppens Belgium

Anouk Van de Vel

372 ×0.8

253 ×0.8

PMH

78 ×0.7

CCM

126 ×1.2

60 ×0.8

CMN

Citations per year, relative to Anouk Van de Vel Anouk Van de Vel (= 1×) peers Kris Cuppens

Countries citing papers authored by Anouk Van de Vel

Since Specialization

Citations

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

Fields of papers citing papers by Anouk Van de Vel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anouk Van de Vel. 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 Anouk Van de Vel. The network helps show where Anouk Van de Vel may publish in the future.

Co-authorship network of co-authors of Anouk Van de Vel

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

All Works

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20 of 20 papers shown

Vel, Anouk Van de, et al.. (2019). The clinical and genetic spectrum in infants with (an) unprovoked cluster(s) of focal seizures. European Journal of Paediatric Neurology. 24. 148–153. 5 indexed citations

Cooman, Thomas De, Carolina Varon, Anouk Van de Vel, et al.. (2018). Adaptive nocturnal seizure detection using heart rate and low-complexity novelty detection. Seizure. 59. 48–53. 22 indexed citations

Cooman, Thomas De, Carolina Varon, Anouk Van de Vel, et al.. (2018). Comparison and combination of electrocardiogram, electromyogram and accelerometry for tonic-clonic seizure detection in children. Lirias (KU Leuven). 438–441. 5 indexed citations

Cooman, Thomas De, Carolina Varon, Anouk Van de Vel, et al.. (2017). Semi-Supervised One-Class Transfer Learning for Heart Rate Based Epileptic Seizure Detection. Computing in cardiology. 9 indexed citations

Vel, Anouk Van de, Kris Cuppens, Bert Bonroy, et al.. (2016). Feature selection methods for accelerometry-based seizure detection in children. Medical & Biological Engineering & Computing. 55(1). 151–165. 14 indexed citations

Vel, Anouk Van de, Kris Cuppens, Bert Bonroy, et al.. (2016). Non-EEG seizure detection systems and potential SUDEP prevention: State of the art. Seizure. 41. 141–153. 95 indexed citations

Vel, Anouk Van de, Katrien Smets, Kristien Wouters, & Berten Ceulemans. (2016). Automated non-EEG based seizure detection: Do users have a say?. Epilepsy & Behavior. 62. 121–128. 55 indexed citations

Vel, Anouk Van de, Bert Bonroy, Kris Cuppens, et al.. (2016). Long-term accelerometry-triggered video monitoring and detection of tonic–clonic and clonic seizures in a home environment: Pilot study. Epilepsy & Behavior Case Reports. 5. 66–71. 18 indexed citations

Vel, Anouk Van de, Bert Bonroy, Berten Ceulemans, et al.. (2015). Automated Detection of Tonic–Clonic Seizures Using 3-D Accelerometry and Surface Electromyography in Pediatric Patients. IEEE Journal of Biomedical and Health Informatics. 20(5). 1333–1341. 72 indexed citations

10.

Cooman, Thomas De, Anouk Van de Vel, Berten Ceulemans, et al.. (2015). Online detection of tonic-clonic seizures in pediatric patients using ECG and low-complexity incremental novelty detection. PubMed. 12. 5597–5600. 9 indexed citations

11.

Vel, Anouk Van de, Kristien Verhaert, & Berten Ceulemans. (2014). Critical evaluation of four different seizure detection systems tested on one patient with focal and generalized tonic and clonic seizures. Epilepsy & Behavior. 37. 91–94. 27 indexed citations

12.

Vel, Anouk Van de, Bert Bonroy, Berten Ceulemans, et al.. (2014). Detection of epileptic convulsions from accelerometry signals through machine learning approach. 1–6. 6 indexed citations

13.

Vel, Anouk Van de, Kris Cuppens, Bert Bonroy, et al.. (2013). Non-EEG seizure-detection systems and potential SUDEP prevention: State of the art. Seizure. 22(5). 345–355. 84 indexed citations

14.

Luca, Stijn, Peter Karsmakers, Kris Cuppens, et al.. (2013). Detecting rare events using extreme value statistics applied to epileptic convulsions in children. Artificial Intelligence in Medicine. 60(2). 89–96. 26 indexed citations

15.

Cuppens, Kris, Peter Karsmakers, Anouk Van de Vel, et al.. (2013). Accelerometry-Based Home Monitoring for Detection of Nocturnal Hypermotor Seizures Based on Novelty Detection. IEEE Journal of Biomedical and Health Informatics. 18(3). 1026–1033. 52 indexed citations

16.

Cuppens, Kris, Peter Karsmakers, Anouk Van de Vel, et al.. (2013). Handling Unbalanced Data in Nocturnal Epileptic Seizure Detection using Accelerometers. 447–452. 2 indexed citations

17.

Vel, Anouk Van de, Kris Cuppens, Bert Bonroy, et al.. (2012). Long-term home monitoring of hypermotor seizures by patient-worn accelerometers. Epilepsy & Behavior. 26(1). 118–125. 45 indexed citations

18.

Cuppens, Kris, Chih‐Wei Chen, Anouk Van de Vel, et al.. (2012). Using spatio-temporal interest points (STIP) for myoclonic jerk detection in nocturnal video. PubMed. 2012. 4454–4457. 35 indexed citations

19.

Cuppens, Kris, Bert Bonroy, Anouk Van de Vel, et al.. (2012). AUTOMATIC VIDEO DETECTION OF NOCTURNAL EPILEPTIC MOVEMENT BASED ON MOTION TRACKS. Lirias (KU Leuven). 342–345. 3 indexed citations

20.

Cuppens, Kris, Chih‐Wei Chen, Anouk Van de Vel, et al.. (2012). Integrating video and accelerometer signals for nocturnal epileptic seizure detection. 161–164. 11 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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