Publications de Cosimo Aprile | EPFL Graph Search

A 16-Channel Neural Recording System-on-Chip With CHT Feature Extraction Processor in 65-nm CMOS

Volkan Cevher, Stéphanie Lacour, Catherine Dehollain, Cosimo Aprile, Alix Esther Anne Trouillet, Emilie Cornelia Maria Revol, Yusuf Leblebici, Kerim Türe, Florian Dylan Fallegger, Arda Uran

Next generation invasive neural interfaces require fully implantable wireless systems that can record from a large number of channels simultaneously. However, transferring the recorded data from the implant to an external receiver emerges as a significant ...

2022

A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS

Volkan Cevher, Stéphanie Lacour, Catherine Dehollain, Cosimo Aprile, Alix Esther Anne Trouillet, Yusuf Leblebici, Kerim Türe, Florian Dylan Fallegger, Arda Uran

Wireless implantable neural recording chips enable multichannel data acquisition with high spatiotemporal resolution in situ. Recently, the use of machine learning approaches on neural data for diagnosis and prosthesis control have renewed the interest in ...

2021

A 161-mW 56-Gb/s ADC-Based Discrete Multitone Wireline Receiver Data-Path in 14-nm FinFET

Andreas Peter Burg, Cosimo Aprile, Yusuf Leblebici, Alessandro Cevrero, Gain Kim, Lukas Kull, Ilter Ozkaya, Thomas Toifl

This article introduces a wireline receiver (RX) data-path employing discrete multi-tone (DMT) modulation for communicating over electrical links. The DMT RX incorporates a fully digital equalization data-path, with a synthesized and automatically placed a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

A 4.8pJ/b 6Gb/s ADC-Based PAM-4 Wireline Receiver Data -Path with Cyclic Prefix in 14nm FinFET

Andreas Peter Burg, Cosimo Aprile, Yusuf Leblebici, Alessandro Cevrero, Gain Kim, Lukas Kull, Ilter Ozkaya, Thomas Toifl

This work presents an ADC-bascd receiver (RX) data-path for frame-based PAM-4 modulation with a cyclic prefix (CP). Similar to discrete multi-tone (DMT) modulation, a frame of PAM-4 symbols arc protected from the channel delay spread by the CP taps. A PAM- ...

IEEE2019

A 24 kb Single-Well Mixed 3T Gain-Cell eDRAM with Body-Bias in 28 nm FD-SOI for Refresh-Free DSP Applications

Andreas Peter Burg, Robert Giterman, Cosimo Aprile, Yusuf Leblebici, Andrea Bonetti, Jonathan Emmanuel D Narinx, Nicolas Claude Frigerio

Logic-compatible gain-cell embedded DRAM (GC-eDRAM) is an emerging alternative to conventional SRAM for memory-dominated system-on-chip (SoC) designs due to its high-density, low-power, and two-ported operation. Although GCs have a limited data retention t ...

IEEE2019

A 161mW 56Gb/s ADC-Based Discrete Multitone Wireline Receiver Data-Path in 14nm FinFET

Andreas Peter Burg, Cosimo Aprile, Yusuf Leblebici, Alessandro Cevrero, Gain Kim, Lukas Kull, Ilter Ozkaya, Thomas Toifl

IEEE2019

Adaptive Learning-Based Compressive Sampling for Low-power Wireless Implants

Volkan Cevher, Catherine Dehollain, Mahsa Shoaran, Yusuf Leblebici, Gürkan Yilmaz, Cosimo Aprile, Luca Baldassarre, Kerim Türe, Franco Maloberti

Implantable systems are nowadays being used to interface the human brain with external devices, in order to understand and potentially treat neurological disorders. The most predominant design constraints are the system’s area and power. In this paper, we ...

2018

Real-time DCT Learning-based Reconstruction of Neural Signals

Volkan Cevher, Cosimo Aprile, Rabeeh Karimi Mahabadi

Wearable and implantable body sensor network systems are one of the key technologies for continuous monitoring of patient’s vital health status such as temperature and blood pressure, and brain activity. Such devices are critical for early detection of eme ...

IEEE2018

An area and power efficient on-the-fly LBCS transformation for implantable neuronal signal acquisition systems

Volkan Cevher, Cosimo Aprile, Yusuf Leblebici, Luca Baldassarre

A power and area efficient hardware encoding system tailored for wireless implantable applications is presented. Constant medical monitoring allowed by implantable devices is the most relevant alternative to current bulky monitoring systems, which, in case ...

ASSOC COMPUTING MACHINERY2018

Learning-Based Hardware Design for Data Acquisition Systems

Cosimo Aprile

This multidisciplinary research work aims to investigate the optimized information extraction from signals or data volumes and to develop tailored hardware implementations that trade-off the complexity of data acquisition with that of data processing, conc ...

EPFL2018