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Nick Van Helleputte

Nick Van Helleputte

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
35
Citations
4380
World Ranking
5632
National Ranking
120

Overview

Nick Van Helleputte is affiliated with Imec in Belgium and has contributed extensively to research in engineering and medicine, with a strong focus on biomedical engineering and related subfields.

The main fields of study addressed by their work include:

  • Engineering
  • Medicine

The subfields in which they have published are:

  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Cardiology and Cardiovascular Medicine
  • Cellular and Molecular Neuroscience
  • Cognitive Neuroscience

The primary research topics covered in their publications include:

  • Non-Invasive Vital Sign Monitoring
  • Analog and Mixed-Signal Circuit Design
  • Neuroscience and Neural Engineering
  • ECG Monitoring and Analysis
  • Advanced Memory and Neural Computing
  • Heart Rate Variability and Autonomic Control
  • EEG and Brain-Computer Interfaces

Nick Van Helleputte has authored numerous research papers. Selected recent publications are:

  • A 119dB Dynamic Range Charge Counting Light-to-Digital Converter For Wearable PPG/NIRS Monitoring Applications, 2020, IEEE Transactions on Biomedical Circuits and Systems
  • Wearable Multiple Modality Bio-Signal Recording and Processing on Chip: A Review, 2020, IEEE Sensors Journal
  • Binary CorNET: Accelerator for HR Estimation From Wrist-PPG, 2020, IEEE Transactions on Biomedical Circuits and Systems
  • A 108 dB DR Δ∑-∑M Front-End With 720 mVpp Input Range and >±300 mV Offset Removal for Multi-Parameter Biopotential Recording, 2021, IEEE Transactions on Biomedical Circuits and Systems
  • A 134 DB Dynamic Range Noise Shaping Slope Light-to-Digital Converter for Wearable Chest PPG Applications, 2021, IEEE Transactions on Biomedical Circuits and Systems

Their collaborations include frequent coauthors such as:

  • Chris Van Hoof
  • Qiuyang Lin
  • Carolina Mora López
  • T.S. Fiez
  • A Greenberg

Nick Van Helleputte's work has appeared in several publication venues, with notable contributions to:

  • IEEE Journal of Solid-State Circuits
  • IEEE Transactions on Biomedical Circuits and Systems
  • IEEE Transactions on Circuits & Systems II Express Briefs
  • Innovation in Aging
  • IEEE Sensors Journal

Best Publications

  • CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment

    Dwaipayan Biswas;Luke Everson;Muqing Liu;Madhuri Panwar

  • 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

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

    Hyejung Kim;Sunyoung Kim;Nick Van Helleputte;Antonio Artes

  • Heart Rate Estimation From Wrist-Worn Photoplethysmography: A Review

    Dwaipayan Biswas;Neide Simoes-Capela;Chris Van Hoof;Nick Van Helleputte

  • A Neural Probe With Up to 966 Electrodes and Up to 384 Configurable Channels in 0.13 $\mu$m SOI CMOS

    Carolina Mora Lopez;Jan Putzeys;Bogdan Cristian Raducanu;Marco Ballini

  • Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites.

    Bogdan C. Raducanu;Refet Firat Yazicioglu;Carolina Mora Lopez;Marco Ballini

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

    Nick Van Helleputte;Sunyoung Kim;Hyejung Kim;Jong Pal Kim

  • A 160 $\mu{ m A}$ Biopotential Acquisition IC With Fully Integrated IA and Motion Artifact Suppression

    N. Van Helleputte;Sunyoung Kim;Hyejung Kim;Jong Pal Kim

  • Motion artifact reduction for wrist-worn photoplethysmograph sensors based on different wavelengths

    Yifan Zhang;Shuang Song;Rik Vullings;Dwaipayan Biswas

  • A configurable and low-power mixed signal SoC for portable ECG monitoring applications

    Hyejung Kim;Refet Firat Yazicioglu;Sunyoung Kim;Nick Van Helleputte

  • A 769 μW Battery-Powered Single-Chip SoC With BLE for Multi-Modal Vital Sign Monitoring Health Patches

    Shuang Song;Peter Vis;Chris van Liempd;Chris van Hoof

  • A Multi(bio)sensor Acquisition System With Integrated Processor, Power Management, $8 imes 8$ LED Drivers, and Simultaneously Synchronized ECG, BIO-Z, GSR, and Two PPG Readouts

    Mario Konijnenburg;Stefano Stanzione;Long Yan;Dong-Woo Jee

  • A Multimodal CMOS MEA for High-Throughput Intracellular Action Potential Measurements and Impedance Spectroscopy in Drug-Screening Applications

    Carolina Mora Lopez;Ho Sung Chun;Shiwei Wang;Laurent Berti

  • Correlation Between Electrode-Tissue Impedance and Motion Artifact in Biopotential Recordings

    D. Buxi;Sunyoung Kim;N. van Helleputte;M. Altini

  • A Reconfigurable, 130 nm CMOS 108 pJ/pulse, Fully Integrated IR-UWB Receiver for Communication and Precise Ranging

    N. Van Helleputte;M. Verhelst;W. Dehaene;G. Gielen

  • 18.3 A multi-parameter signal-acquisition SoC for connected personal health applications

    Nick Van Helleputte;Mario Konijnenburg;Hyejung Kim;Julia Pettine

  • A Compact Quad-Shank CMOS Neural Probe With 5,120 Addressable Recording Sites and 384 Fully Differential Parallel Channels

    Shiwei Wang;Carolina Mora Lopez;Seyed Kasra Garakoui;Hosung Chun

  • Neuropixels Data-Acquisition System: A Scalable Platform for Parallel Recording of 10 000+ Electrophysiological Signals

    Jan Putzeys;Silke Musa;Carolina Mora Lopez;Bogdan C. Raducanu

  • A flexible system-on-chip (SoC) for biomedical signal acquisition and processing

    N. Van Helleputte;J.M. Tomasik;W. Galjan;A. Mora-Sanchez

  • A 400 GΩ Input-Impedance Active Electrode for Non-Contact Capacitively Coupled ECG Acquisition With Large Linear-Input-Range and High CM-Interference-Tolerance

    Mingyi Chen;Ho Sung Chun;Ivan Dario Castro;Tom Torfs

  • A 119dB Dynamic Range Charge Counting Light-to-Digital Converter For Wearable PPG/NIRS Monitoring Applications

    Qiuyang Lin;Jiawei Xu;Shuang Song;Arjan Breeschoten

  • A 665 μW Silicon Photomultiplier-Based NIRS/EEG/EIT Monitoring ASIC for Wearable Functional Brain Imaging

    Jiawei Xu;Mario Konijnenburg;Shuang Song;Hyunsoo Ha

  • A reconfigurable, 0.13µm CMOS 110pJ/pulse, fully integrated IR-UWB receiver for communication and sub-cm ranging

    Marian Verhelst;Nick Van Helleputte;Georges Gielen;Wim Dehaene

Frequent Co-Authors

Refet Firat Yazicioglu
Refet Firat Yazicioglu Galvani Bioelectronics
Chris H. Kim
Chris H. Kim University of Minnesota
Robert Puers
Robert Puers KU Leuven
Wim Dehaene
Wim Dehaene KU Leuven
Patrick Ruther
Patrick Ruther University of Freiburg
Wout Joseph
Wout Joseph Ghent University

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