H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 40 Citations 5,769 103 World Ranking 1882 National Ranking 43

Overview

What is he best known for?

The fields of study he is best known for:

  • Electrical engineering
  • Amplifier
  • Artificial intelligence

The scientist’s investigation covers issues in Electronic engineering, Electrical engineering, Communication channel, CMOS and Noise. His studies in Electronic engineering integrate themes in fields like Wireless, Analog signal, Noise, Wearable computer and Signal compression. His is involved in several facets of Electrical engineering study, as is seen by his studies on Input impedance, Electrical impedance and Amplifier.

His CMOS research includes themes of Instrumentation amplifier, Chopper, Electronic circuit and Low-power electronics. His work in Instrumentation amplifier covers topics such as Application-specific integrated circuit which are related to areas like Ambulatory EEG. His Chopper research focuses on Capacitive coupling and how it relates to Analog-to-digital converter, Digital control and Gain stage.

His most cited work include:

  • A 60 $\mu$ W 60 nV/ $\surd$ Hz Readout Front-End for Portable Biopotential Acquisition Systems (347 citations)
  • A 200 $\mu$ W Eight-Channel EEG Acquisition ASIC for Ambulatory EEG Systems (202 citations)
  • An implantable 455-active-electrode 52-channel CMOS neural probe (176 citations)

What are the main themes of his work throughout his whole career to date?

Electronic engineering, Electrical engineering, CMOS, Signal and Wireless are his primary areas of study. His Electronic engineering research incorporates elements of Instrumentation amplifier, Electrical impedance, Amplifier and Analog signal. His work on Voltage, Electronic circuit, Noise and Chopper as part of general Electrical engineering research is often related to Front and back ends, thus linking different fields of science.

His biological study spans a wide range of topics, including Dynamic range, Transistor and Low-power electronics. Refet Firat Yazicioglu interconnects Artificial intelligence, Artifact reduction, Computer vision and Artifact in the investigation of issues within Signal. His studies deal with areas such as Energy harvesting and Wearable computer as well as Wireless.

He most often published in these fields:

  • Electronic engineering (51.15%)
  • Electrical engineering (38.17%)
  • CMOS (17.56%)

What were the highlights of his more recent work (between 2013-2018)?

  • Electronic engineering (51.15%)
  • Electrical engineering (38.17%)
  • Signal (17.56%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Electronic engineering, Electrical engineering, Signal, Amplifier and CMOS. He studies Electronic engineering, focusing on Application-specific integrated circuit in particular. His research integrates issues of Wireless and Successive approximation ADC in his study of Application-specific integrated circuit.

His Electrical engineering study deals with Communication channel intersecting with Signal compression. His Signal research includes elements of Chopper, Artifact reduction and Artificial intelligence. His studies deal with areas such as Dynamic range, Artificial neural network, Active devices and Transistor, Soi cmos as well as CMOS.

Between 2013 and 2018, his most popular works were:

  • A Configurable and Low-Power Mixed Signal SoC for Portable ECG Monitoring Applications (123 citations)
  • A 345 µW Multi-Sensor Biomedical SoC With Bio-Impedance, 3-Channel ECG, Motion Artifact Reduction, and Integrated DSP (119 citations)
  • A Neural Probe With Up to 966 Electrodes and Up to 384 Configurable Channels in 0.13 $\mu$m SOI CMOS (70 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Amplifier
  • Artificial intelligence

His primary areas of study are Electrical engineering, Electronic engineering, CMOS, Communication channel and Noise. His study looks at the relationship between Electrical engineering and fields such as ARM architecture, as well as how they intersect with chemical problems. His specific area of interest is Electronic engineering, where Refet Firat Yazicioglu studies Application-specific integrated circuit.

Refet Firat Yazicioglu usually deals with Application-specific integrated circuit and limits it to topics linked to Feature extraction and Wireless. His CMOS study combines topics in areas such as Transistor and Soi cmos. His work deals with themes such as Pulse-width modulation, Wearable computer and Analog signal, which intersect with Electrical impedance.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

A 60 $\mu$ W 60 nV/ $\surd$ Hz Readout Front-End for Portable Biopotential Acquisition Systems

R.F. Yazicioglu;P. Merken;R. Puers;C. Van Hoof.
IEEE Journal of Solid-state Circuits (2007)

515 Citations

A 200 $\mu$ W Eight-Channel EEG Acquisition ASIC for Ambulatory EEG Systems

R.F. Yazicioglu;P. Merken;R. Puers;C. Van Hoof.
IEEE Journal of Solid-state Circuits (2008)

318 Citations

A 30 $\mu$ W Analog Signal Processor ASIC for Portable Biopotential Signal Monitoring

Refet Firat Yazicioglu;Sunyoung Kim;Tom Torfs;Hyejung Kim.
IEEE Journal of Solid-state Circuits (2011)

252 Citations

A $160~\mu { m W}$ 8-Channel Active Electrode System for EEG Monitoring

Jiawei Xu;R. F. Yazicioglu;B. Grundlehner;P. Harpe.
IEEE Transactions on Biomedical Circuits and Systems (2011)

230 Citations

An implantable 455-active-electrode 52-channel CMOS neural probe

Carolina Mora Lopez;Alexandru Andrei;Srinjoy Mitra;Marleen Welkenhuysen.
international solid-state circuits conference (2013)

227 Citations

Human++: autonomous wireless sensors for body area networks

B. Gyselinckx;C. Van Hoof;J. Ryckaert;R.F. Yazicioglu.
custom integrated circuits conference (2005)

226 Citations

A Configurable and Low-Power Mixed Signal SoC for Portable ECG Monitoring Applications

Hyejung Kim;Sunyoung Kim;Nick Van Helleputte;Antonio Artes.
IEEE Transactions on Biomedical Circuits and Systems (2014)

222 Citations

ECG Signal Compression and Classification Algorithm With Quad Level Vector for ECG Holter System

Hyejung Kim;R.F. Yazicioglu;P. Merken;C. Van Hoof.
international conference of the ieee engineering in medicine and biology society (2010)

186 Citations

A 345 µW Multi-Sensor Biomedical SoC With Bio-Impedance, 3-Channel ECG, Motion Artifact Reduction, and Integrated DSP

Nick Van Helleputte;Mario Konijnenburg;Julia Pettine;Dong-Woo Jee.
IEEE Journal of Solid-state Circuits (2015)

158 Citations

A 160μA biopotential acquisition ASIC with fully integrated IA and motion-artifact suppression

Nick Van Helleputte;Sunyoung Kim;Hyejung Kim;Jong Pal Kim.
international solid-state circuits conference (2012)

145 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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