L
Lorenzo Turicchia
Researcher at Massachusetts Institute of Technology
Publications - 36
Citations - 893
Lorenzo Turicchia is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Speech processing & Signal. The author has an hindex of 14, co-authored 36 publications receiving 845 citations. Previous affiliations of Lorenzo Turicchia include University of Udine & University of Padua.
Papers
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Journal ArticleDOI
An ultra-low-power programmable analog bionic ear processor
Rahul Sarpeshkar,Christopher Salthouse,Ji-Jon Sit,M.W. Baker,Serhii M. Zhak,Timothy K. Lu,Lorenzo Turicchia,S. Balster +7 more
TL;DR: A programmable analog bionic ear (cochlear implant) processor in a 1.5-/spl mu/m BiCMOS technology with a power consumption that is lower than state-of-the-art analog-to-digital (A/D)-then-DSP designs by a factor of 25 and robust operation of the processor in the high-RF-noise environment typical of cochlear implants systems.
Journal ArticleDOI
An Ultra-Low-Power Pulse Oximeter Implemented With an Energy-Efficient Transimpedance Amplifier
TL;DR: In this paper, an analog single-chip pulse oximeter with 4.8mW total power dissipation is presented, which is an order of magnitude below the measurements on commercial implementations.
Proceedings ArticleDOI
An analog bionic ear processor with zero-crossing detection
Rahul Sarpeshkar,M.W. Baker,Christopher Salthouse,Ji-Jon Sit,Lorenzo Turicchia,Serhii M. Zhak +5 more
TL;DR: In this article, a 75 dB 251 /spl mu/W analog speech processor is described that preserves the performance, robustness, and programmability needed for deaf patients at a reduced power consumption compared to that of implementations with A/D and DSP.
Patent
Coding for visual prostheses
TL;DR: In this paper, a visual prosthesis codes visual signals into electrical stimulation patterns for the creation of artificial vision using image compression techniques, temporal coding strategies, continuous interleaved sampling (CIS), and/or radar or sonar data.
Journal ArticleDOI
A bio-inspired companding strategy for spectral enhancement
TL;DR: The companding strategy simulates the two-tone suppression phenomena of the auditory system and implements a soft local winner-take-all-like enhancement of the input spectrum that performs multichannel syllabic compression without degrading spectral contrast.