H-Index & Metrics Best Publications
Chris Van Hoof

Chris Van Hoof

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 40 Citations 6,949 244 World Ranking 1844 National Ranking 41

Overview

What is he best known for?

The fields of study he is best known for:

  • Electrical engineering
  • Artificial intelligence
  • Optics

Chris Van Hoof focuses on Electrical engineering, Electronic engineering, Wearable computer, Wireless and Energy. His studies in Electrical engineering integrate themes in fields like Optoelectronics, Communication channel, ARM architecture and Thermoelectric generator. His work deals with themes such as Analog signal, Noise, Electrical impedance, Input impedance and Chopper, which intersect with Electronic engineering.

His Wearable technology study in the realm of Wearable computer interacts with subjects such as Block. The various areas that he examines in his Wireless study include Computer hardware, Battery, Wireless sensor network, Embedded system and Building automation. His study looks at the relationship between Energy and fields such as Generator, as well as how they intersect with chemical problems.

His most cited work include:

  • Energy Harvesting for Autonomous Wireless Sensor Networks (472 citations)
  • Harvesting energy from the motion of human limbs: the design and analysis of an impact-based piezoelectric generator (214 citations)
  • Harvesting energy from the motion of human limbs: the design and analysis of an impact-based piezoelectric generator (214 citations)

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

Optoelectronics, Electronic engineering, Electrical engineering, CMOS and Optics are his primary areas of study. His study in Optoelectronics is interdisciplinary in nature, drawing from both Layer and Detector. Chris Van Hoof has researched Electronic engineering in several fields, including Input impedance and Artificial intelligence.

He has included themes like Energy harvesting and Wearable computer in his Electrical engineering study. Many of his studies on Wearable computer involve topics that are commonly interrelated, such as Wireless. His research on CMOS frequently links to adjacent areas such as Pixel.

He most often published in these fields:

  • Optoelectronics (24.51%)
  • Electronic engineering (18.60%)
  • Electrical engineering (18.82%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (9.19%)
  • Photoplethysmogram (3.06%)
  • Wearable computer (9.85%)

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

The scientist’s investigation covers issues in Artificial intelligence, Photoplethysmogram, Wearable computer, Optics and Heart rate. His Artificial intelligence research includes elements of Autocorrelation, Computer vision and Pattern recognition. His Wearable computer study combines topics from a wide range of disciplines, such as Wireless, Computer hardware, Battery, Human–computer interaction and Form factor.

His Optics study deals with Thin film intersecting with Vignetting. His studies deal with areas such as Electrocardiography and Physical medicine and rehabilitation as well as Heart rate. His Signal study combines topics from a wide range of disciplines, such as Wireless sensor network and Deep learning.

Between 2018 and 2021, his most popular works were:

  • CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment (53 citations)
  • Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor (40 citations)
  • Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor (40 citations)

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

  • Electrical engineering
  • Artificial intelligence
  • Optics

His primary scientific interests are in Artificial intelligence, Radar, Signal, Photoplethysmogram and Pattern recognition. His Artificial intelligence research integrates issues from Ecg signal, Computer vision and Sensitivity. When carried out as part of a general Computer vision research project, his work on Tracking is frequently linked to work in Vital signs, therefore connecting diverse disciplines of study.

His Radar research incorporates themes from Baseband and Track. He has researched Signal in several fields, including Noise, Multiple modalities and Motion. His Photoplethysmogram research is multidisciplinary, incorporating elements of Latency, Artificial neural network, Electrocardiography, Blood pressure monitoring and Biomedical engineering.

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.

Best Publications

Energy Harvesting for Autonomous Wireless Sensor Networks

Rudd J.M. Vullers;Rob van Schaijk;Hubregt J. Visser;Julien Penders.
IEEE Solid-State Circuits Magazine (2010)

644 Citations

Harvesting energy from the motion of human limbs: the design and analysis of an impact-based piezoelectric generator

Michael Renaud;Paolo Fiorini;Rob van Schaijk;Chris van Hoof;Chris van Hoof.
Smart Materials and Structures (2009)

292 Citations

Prostate-specific antigen immunosensing based on mixed self-assembled monolayers, camel antibodies and colloidal gold enhanced sandwich assays

Lieven Huang;Gunter Reekmans;Dirk Saerens;Jean-Michel Friedt.
Biosensors and Bioelectronics (2005)

260 Citations

Realization of a wearable miniaturized thermoelectric generator for human body applications

Ziyang Wang;Vladimir Leonov;Paolo Fiorini;Chris Van Hoof.
Sensors and Actuators A-physical (2009)

252 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 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

5μW-to-10mW input power range inductive boost converter for indoor photovoltaic energy harvesting with integrated maximum power point tracking algorithm

Yifeng Qiu;Chris Van Liempd;Bert Op het Veld;Peter G Blanken.
international solid-state circuits conference (2011)

165 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

Soft, Comfortable Polymer Dry Electrodes for High Quality ECG and EEG Recording

Yun Hsuan Chen;Maaike Op de Beeck;Luc Vanderheyden;Evelien Carrette.
Sensors (2014)

148 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

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Best Scientists Citing Chris Van Hoof

Refet Firat Yazicioglu

Refet Firat Yazicioglu

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Kwangwoon University

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Georgia Institute of Technology

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István Ulbert

Pázmány Péter Catholic University

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Yong Lian

Shanghai Jiao Tong University

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Chengkuo Lee

National University of Singapore

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Michael De Volder

University of Cambridge

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Wayne State University

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Benton H. Calhoun

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