Low-power sensor interface integrated circuit design



To develop a low-power sensor interface integrated circuit to read out the data sensors developed through project 9 and project 10 and to drive the micoactuators in project 8 . To save power in CMOS technology, al low supply voltage is needed, which calls for time -based design solutions. Therefore, digitally dominant analog design techniques and time-based processing will be explored to obtain an optimal circuit architecture that has state -of-the-art figure-of -merit performance. The architectural study will be followed by the actual design, fabrication, testing and validation of a sensor readout integrated circuit. Further, the test chips will be thinned down to about 15 mm in post -processing steps during secondments. The bendability of these ultra-thin chips (UTCs) will lead to improved conformability.

Expected Results

Low-power electronics interface to read the data from sensors in the skin.


Host institution The Katholieke Universiteit Leuven

Enrolments (in Doctoral degree) The Katholieke Universiteit Leuven


Georges Gielen, Chris Van Hoof

Presentation of ESR11

PhD defense: Tentative period September 2025

My name is Mark Daniel Alea and I am born in Batangas, Philippines in 1992. I received my MS degree in Electrical Engineering from the University of the Philippines – Diliman in 2019. My thesis is entitled, “Gate current cancellation using replica PMOS and digital feedback for temperature coefficient reduction in ultra-low power voltage references”. From 2016 – 2020, I was an Analog IC Designer with Analog Devices Philippines where I worked on a nanogap sensor readout for biomedical applications.

Abstract of PhD goals

Mimicking humans, existing” electronic skin” (e-skin) systems consist of a network of sensors that measure parameters like static and dynamic forces (normal or multi-axial) and that transmit this information to central processing units to classify or interpret the tactile information. To reduce the communication bandwidth, current-skin solutions convert sensor information into” events” or ”spikes”, which is typically performed at the software level. Thus, the readout electronics are still implemented using off-the-shelf components with overdesigned precision and speed, failing to take advantage of the spatiotemporally sparse nature of the tactile information to be converted. Therefore, existing systems stand in stark contrast to the power-efficient and high spatial resolution sensing and local processing observed in the human somatosensory system.


To mimic the rich tactile information captured by the human fingertips during object manipulation, it is necessary to achieve the same power-efficient and high spatial resolution sensing and local processing. A promising approach towards this vision is by integrating a dense tactile sensor array on a custom CMOS readout chip, allowing for dense and power-efficient readout with local processing capabilities. The sensor-to-readout chip integration supports dense per-taxel connections, enabling true per-taxel sparse-sampling conversion (i.e., spikes) as performed in human afferents while also eliminating the mechanically-fragile sensor-to-readout wiring.


Deliverable 4.6 Low-power sensory readout and electronic interface
Architectural study of time-based sensor readout in CMOS. Circuit design and layout of a low-power time-based sensor interface in CMOS.

Journal Article – Upcoming
Alea, M.D.; Safa, A.; Giacomozzi, F.; Adami, A.; Temel, I.R.; Rosa, M.A.; Lorenzelli, L.; Gielen, G.
A Fingertip-Mimicking 12×16 200μm-Resolution e-skin Taxel Readout Chip with per-Taxel Spiking Readout and Embedded Receptive Field Processing

Conference Article – Upcoming
Wang, R.; Alea, M.D.; Assche, J.V.; Gielen, G.
Towards a neuromorphic tactile sensing platform

Conference Article
Alea, M.D; Safa, A.; Giacomozzi, F.; Adami, A.;  Rüya Temel, I.; Lorenzelli, L.; Gielen, G.
A Fingertip-Mimicking 12×16 200μm-Resolution e-skin Taxel Readout Chip with per-Taxel Spiking Readout and Embedded Receptive Field Processing
IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023
DOI: 10.23919/VLSITechnologyandCir57934.2023.1018534

Conference Article
Wang, J.; Alea, M.D.; Van Assche, J.; Gielen, G.G.E.
End-to-End Optimization of High-Density e-Skin Design: From Spiking Taxel Readout to Texture Classification
Design, Automation & Test in Europe Conference & Exhibition (DATE), 2023
DOI: 10.23919/DATE56975.2023.10137077

Conference Article
Alea, M.D.; Safa, A.; Van Assche, J.; Gielen, G.G.E.
Power-Efficient and Accurate Texture Sensing Using Spiking Readouts for High-Density e-Skins
IEEE Biomedical Circuits and Systems Conference (BioCAS), 2022
DOI: 10.1109/BioCAS54905.2022.9948546

Journal Article
Safa, A.; Van Assche, J.; Alea, M.; Catthoor, F.; Geilen, G.G.E.
Neuromorphic Near-Sensor Computing: From Event-Based Sensing to Edge Learning
IEEE Micro, 2022