M. Schiek

762 total citations
46 papers, 447 citations indexed

About

M. Schiek is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, M. Schiek has authored 46 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 13 papers in Electrical and Electronic Engineering and 9 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in M. Schiek's work include Heart Rate Variability and Autonomic Control (9 papers), Neural dynamics and brain function (7 papers) and Advanced Memory and Neural Computing (6 papers). M. Schiek is often cited by papers focused on Heart Rate Variability and Autonomic Control (9 papers), Neural dynamics and brain function (7 papers) and Advanced Memory and Neural Computing (6 papers). M. Schiek collaborates with scholars based in Germany, Japan and Switzerland. M. Schiek's co-authors include Jürgen Dammers, Stefan van Waasen, U. Pietrzyk, Mikhail Zvyagintsev, Frank Boers, Klaus Mathiak, Yu Yao, Steffen Leonhardt, Guanghao Sun and Friedel Drepper and has published in prestigious journals such as NeuroImage, IEEE Transactions on Biomedical Engineering and American Journal of Physiology-Heart and Circulatory Physiology.

In The Last Decade

M. Schiek

44 papers receiving 439 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Schiek Germany 11 152 102 79 60 57 46 447
Antonio Espósito Italy 12 212 1.4× 62 0.6× 36 0.5× 56 0.9× 17 0.3× 73 551
R.C. Martins Portugal 15 72 0.5× 184 1.8× 65 0.8× 26 0.4× 125 2.2× 49 699
Samo Beguš Slovenia 11 73 0.5× 295 2.9× 196 2.5× 70 1.2× 21 0.4× 24 708
Xiefeng Cheng China 11 37 0.2× 76 0.7× 71 0.9× 31 0.5× 27 0.5× 46 389
I. A. Khovanov United Kingdom 15 117 0.8× 85 0.8× 53 0.7× 10 0.2× 281 4.9× 59 692
M. López Spain 12 224 1.5× 64 0.6× 70 0.9× 16 0.3× 19 0.3× 33 719
Thomas Burger Switzerland 16 109 0.7× 528 5.2× 59 0.7× 39 0.7× 58 1.0× 57 792
Alona Ben‐Tal New Zealand 14 101 0.7× 129 1.3× 276 3.5× 19 0.3× 26 0.5× 26 618
E. Yazgan Türkiye 13 99 0.7× 136 1.3× 144 1.8× 239 4.0× 14 0.2× 89 671
Sebastiaan P. van den Broek Netherlands 11 208 1.4× 57 0.6× 31 0.4× 179 3.0× 16 0.3× 37 578

Countries citing papers authored by M. Schiek

Since Specialization
Citations

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

Fields of papers citing papers by M. Schiek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Schiek

This figure shows the co-authorship network connecting the top 25 collaborators of M. Schiek. A scholar is included among the top collaborators of M. Schiek 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 M. Schiek. M. Schiek 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.
Robens, Markus, et al.. (2024). NoC simulation steered by NEST: McAERsim and a Noxim patch. Frontiers in Neuroscience. 18. 1371103–1371103. 1 indexed citations
2.
Robens, Markus, et al.. (2022). A Network Simulator for the Estimation of Bandwidth Load and Latency Created by Heterogeneous Spiking Neural Networks on Neuromorphic Computing Communication Networks. Journal of Low Power Electronics and Applications. 12(2). 23–23. 6 indexed citations
3.
Robens, Markus, et al.. (2022). Verification of a neuromorphic computing network simulator using experimental traffic data. Frontiers in Neuroscience. 16. 958343–958343. 1 indexed citations
4.
Robens, Markus, et al.. (2021). A Network Simulator for the Estimation of Bandwidth Load and Latency Created by Heterogeneous Spiking Neural Networks on Neuromorphic Computing Communication Networks. Universitätsbibliographie, Universität Duisburg-Essen. 320–327. 2 indexed citations
5.
Yao, Yu, Guanghao Sun, Tetsuo Kirimoto, & M. Schiek. (2019). Extracting Cardiac Information From Medical Radar Using Locally Projective Adaptive Signal Separation. Frontiers in Physiology. 10. 568–568. 8 indexed citations
6.
Schiek, M., et al.. (2018). Iterative Learning Control and Decoupling of Lorentz Force Based Actuator Systems for Turbulence Research. 2018 IEEE Conference on Control Technology and Applications (CCTA). 1265–1269.
7.
Raman, Sudhir, et al.. (2018). Variational Bayesian inversion for hierarchical unsupervised generative embedding (HUGE). NeuroImage. 179. 604–619. 5 indexed citations
8.
Yao, Yu, Guanghao Sun, Tetsuo Kirimoto, Takemi Matsui, & M. Schiek. (2017). Online state space filtering of biosignals using neural network-augmented Kalman filter. 1–5. 2 indexed citations
9.
Suslov, Sergey A., et al.. (2017). Model-Driven Development Methodology Applied to Real-Time MEG Signal Preprocessing System Design. 28–33. 1 indexed citations
10.
Abel, Dirk, et al.. (2015). Transversal surface wave control by gain switching iterative learning improving research on active turbulent flow control. RWTH Publications (RWTH Aachen). 120. 2 indexed citations
11.
Waasen, Stefan van, et al.. (2015). Entwicklung einer echtzeitigen Aktuator-Ansteuerung mit Transienten-Glättung in LabVIEW Real-Time zur Strömungsregelung durch transversale Oberflächenwellen. 3 indexed citations
12.
Yao, Yu, Johannes Schiefer, Stefan van Waasen, & M. Schiek. (2014). A non-parametric model for Ballistocardiography. 69–72. 4 indexed citations
13.
Huczkowski, P., Tomasz K. Olszewski, M. Schiek, et al.. (2013). Effect of SO2 on oxidation of metallic materials in CO2/H2O‐rich gases relevant to oxyfuel environments. Materials and Corrosion. 65(2). 121–131. 42 indexed citations
14.
Schiek, M., et al.. (2012). Analyse von Langzeitregistrierungen invasiv erhobener Bioimpedanzdaten. 1 indexed citations
15.
Hong, Ying, Mario Schlösser, A. Schnitzer, et al.. (2010). Distributed Intelligent Sensor Network for the Rehabilitation of Parkinson's Patients. IEEE Transactions on Information Technology in Biomedicine. 15(2). 268–276. 19 indexed citations
16.
Dammers, Jürgen, M. Schiek, Frank Boers, et al.. (2008). Integration of Amplitude and Phase Statistics for Complete Artifact Removal in Independent Components of Neuromagnetic Recordings. IEEE Transactions on Biomedical Engineering. 55(10). 2353–2362. 75 indexed citations
17.
18.
Zarse, Markus, Kai U. Markus, M. Schiek, et al.. (2002). Preserved Parasympathetic Cardiac Innervation after Atrioventricular Node Modification: Evidence from Circle Maps of Respiratory Sinus Arrhythmia. Journal of Interventional Cardiac Electrophysiology. 7(2). 157–163. 3 indexed citations
19.
Drepper, Friedel, et al.. (1998). One-dimensional, nonlinear determinism characterizes heart rate pattern during paced respiration. American Journal of Physiology-Heart and Circulatory Physiology. 275(3). H1092–H1102. 22 indexed citations
20.
Schiek, M., et al.. (1995). [Mathematical model of "respiratory sinus arrhythmia"].. PubMed. 145(17-18). 492–4. 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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