Lorenzo Turicchia

Contact

Dr. Turicchia’s work spans the intersection of bioelectronics, computer science, and medicine, with a focus on creating technologies that analyze, restore, and support human health. In 2002, he joined the Analog VLSI and Biological Systems Group at the Massachusetts Institute of Technology (MIT), where he completed his doctoral research, continued as a postdoctoral researcher in bioelectronics, and was later appointed to the position of Research Scientist.

His work has included applications in (1) cochlear implants (bionic ears) for the hearing impaired, (2) visual prostheses for the blind, (3) speech prostheses for individuals with severe communication disabilities, (4) neural decoding techniques for prosthetic devices for individuals with paralysis, and (5) bioelectronics for wearable medical devices. A central goal throughout this work has been to deepen our understanding of how the brain and body function through novel signal-processing and machine-learning/artificial-intelligence techniques.

The publication record includes more than 50 publicly listed scholarly publications, with publicly visible records showing over 1,000 scientific citations. The work has also received attention beyond the scientific literature through coverage in outlets including The New York Times, MIT Technology Review, EE Times, Science Letter, IEEE Spectrum, Harvard Medicine, Biotech Business Week, US Fed News, R&D Magazine, SPIE Newsroom, Corriere della Sera, Il Sole 24 Ore, RAI (Superquark), Men’s Health, and other public-facing sites, along with thousands of visible article views and downloads, including more than 3,000 downloads of a single paper (L. Turicchia et al., “An FFT-Based Companding Front End”).

The patent portfolio includes more than 100 patent citations from 38 companies and research organizations, including major companies, medical-device firms, and research institutions such as Microsoft, Samsung, Boeing, Qualcomm, IBM, Dolby, Philips, Broadcom, Mitsubishi Electric, Masimo, ZOLL Medical, Fresenius Medical Care, Advanced Bionics, Second Sight, Brain Corporation, MED-EL, Cornell University, Princeton University, Georgia Tech Research Corporation, the University of Illinois, the University of Texas System, and the Bionics Institute of Australia.

In addition to his research, he has served as an Associate Editor of the IEEE Transactions on Information Technology in Biomedicine (T-ITB), as a member of both the Society for Neuroscience and the American Telemedicine Association, and as an active contributor to numerous scientific conferences in roles such as Conference Chair and Technical Program Committee Member. He is also a member of the Sleep Research Society.

SELECTED PUBLICATIONS

Selected Journal Articles (out of 16)

1. Efficient Universal Computing Architectures for Decoding Neural Activity Rapoport, Turicchia, Wattanapanitch, Davidson, and Sarpeshkar, PLoS ONE. View Article

This work introduced an energy-efficient neural-decoding architecture aimed at making brain-computer systems more practical for prosthetics and assistive neurotechnology.
View Summary

The study presented a universal computing framework for decoding neural activity while reducing hardware complexity and power consumption. By emphasizing efficient logic operations, the architecture addressed constraints that are especially important for implantable and portable neuroprosthetic systems. The work advanced the engineering foundations of brain-computer systems by showing how neural decoding could be implemented in a more scalable and resource-aware way. Its broader significance lies in supporting future assistive devices that depend on reliable, low-power communication between neural signals and external device control.

2. An Articulatory Silicon Vocal Tract for Speech and Hearing Prostheses Wee, Turicchia, and Sarpeshkar, IEEE Transactions on Biomedical Circuits and Systems.Invited paper, one of four out of 83 submissions View Article

This invited work advanced low-power speech-prosthesis research by building a silicon system inspired by how the human vocal tract produces speech.
View Summary

The paper described an articulatory silicon vocal tract that reproduced important features of human speech generation in integrated-circuit form. By turning vocal-tract dynamics into compact low-power hardware, the work opened new directions for speech prostheses and assistive communication devices. It also showed how models from speech science can guide practical biomedical-circuit design. Its longer-term importance lies in linking speech production, bio-inspired electronics, and assistive-device engineering in one hardware platform.

3. Sensing and Computing in Wearable Robots Turicchia and Li, IEEE Transactions on Information Technology in Biomedicine.Guest Editorial View Article

This guest editorial highlighted the growing role of wearable robots that combine sensing and computation to support health, rehabilitation, and human assistance.
View Summary

This guest editorial highlighted the growing importance of wearable robots that combine sensing and computation to better interact with the human body. It framed the field as an important direction for rehabilitation, assistance, and health-related applications. Wearable robotic systems become far more useful when sensing, interpretation, and real-time response are designed together.

4. Ultralow-Power Electronics for Cardiac Monitoring Turicchia, Do Valle, Bohorquez, Sanchez, Misra, Fay, Tavakoli, and Sarpeshkar, IEEE Transactions on Circuits and Systems I.Invited paper View Article

This paper advanced a complete ultra-low-power approach to cardiac monitoring, combining system-level design with what was then the lowest-power actively grounded EKG amplifier built so far, to help make long-term, lightweight, and lower-maintenance monitoring more practical.
View Summary

This work focused on reducing the power required for cardiac monitoring without losing the signal quality needed for practical use. Rather than improving only one circuit block, it addressed the broader challenge of how a low-power cardiac-monitoring system can be designed for long-term and more accessible use. A particularly important result was the inclusion of the lowest-power actively grounded EKG amplifier built so far, which strengthened the feasibility of compact and energy-efficient monitoring hardware. Overall, the paper helped show how careful circuit and system design could move cardiac monitoring toward lighter, lower-maintenance devices suitable for prolonged use.

5. An Ultra-Low-Power Pulse Oximeter Implemented with an Energy-Efficient Transimpedance Amplifier Tavakoli, Turicchia, and Sarpeshkar, IEEE Transactions on Biomedical Circuits and Systems.Second most accessed article in the February 2010 IEEE Transactions on Biomedical Circuits and Systems View Article

This paper advanced wearable oxygen monitoring with a single-chip pulse oximeter whose power consumption was about an order of magnitude below commercial implementations.
View Summary

This study presented an analog single-chip pulse oximeter with a total power dissipation of 4.8 mW, showing that pulse-oximetry hardware could be made dramatically more energy efficient. The work addressed one of the main barriers to portable and continuous monitoring: the power cost of reliable optical sensing. Its importance lies in demonstrating that clinically useful oxygen-monitoring electronics could be redesigned for much smaller, lower-power wearable devices.

6. A Low-Power Battery-Free Tag for Body Sensor Networks Mandal, Turicchia, and Sarpeshkar, IEEE Pervasive Computing. View Article

This paper showed how battery-free wearable sensing could make physiological monitoring more accessible and less burdensome to maintain.
View Summary

The work introduced a battery-free platform for body-sensor-network applications based on RF energy harvesting, custom integrated circuitry, and physiological sensing. It showed how low-power design could support wearable monitoring while reducing size, cost, and maintenance burdens. By combining sensing, alarm generation, and harvested power in a compact platform, the study helped push biomedical electronics toward more pervasive and practical deployment. Its broader importance lies in suggesting new ways to support continuous patient monitoring outside conventional clinical settings.

7. An Analog Integrated-Circuit Vocal Tract Wee, Turicchia, and Sarpeshkar, IEEE Transactions on Biomedical Circuits and Systems. View Article

This paper presented the first experimental integrated-circuit vocal tract, showing that models of human speech production could be realized in ultra-low-power hardware for future assistive speech systems.
View Summary

This work translated key features of human speech production into an analog integrated circuit, creating what the paper described as the first experimental integrated-circuit vocal tract. The 275-µW chip showed that real-time speech-production models could be implemented with very low power in compact hardware. The result helped establish a practical foundation for future speech prostheses and other assistive communication technologies inspired by how the vocal tract actually works.

8. An FFT-Based Companding Front End for Noise-Robust Automatic Speech Recognition Raj, Turicchia, Schmidt-Nielsen, and Sarpeshkar, EURASIP Journal on Audio, Speech, and Music Processing. View Article

This work introduced an auditory-inspired signal-processing front end designed to make machine listening more robust in noisy real-world environments.
View Summary

The study described an FFT-based companding method for preprocessing sound in a way that preserves important features while improving robustness to background noise. Inspired by masking and tone-suppression phenomena in the auditory system, the approach linked biological insight with practical front-end design. Although developed in the context of automatic speech recognition, its broader value is in robust audio analysis and machine listening under difficult acoustic conditions. Its significance lies in showing how auditory principles can guide more dependable listening systems in the presence of noise.

9. Evaluation of Companding-Based Spectral Enhancement Using Simulated Cochlear-Implant Processing Oxenham, Simonson, Turicchia, and Sarpeshkar, The Journal of the Acoustical Society of America (JASA). View Article

This paper tested whether a new sound-enhancement strategy could improve how speech is represented under cochlear-implant-like listening conditions.
View Summary

The study tested a time-domain spectral-enhancement approach using simulated cochlear-implant processing and perceptual evaluation. Rather than proposing an algorithm alone, it asked whether the method produced meaningful listening benefits under conditions relevant to implant users. That made the work important as a bridge between signal-processing theory and auditory outcome assessment. Its broader contribution lies in helping identify which engineering strategies are most likely to matter in real hearing-assistive contexts.

10. A Bio-Inspired Companding Strategy for Spectral Enhancement Turicchia and Sarpeshkar, IEEE Transactions on Speech and Audio Processing. View Article

This paper proposed an auditory-inspired method for enhancing sound while preserving important detail in noisy listening conditions.
View Summary

The work presented a companding strategy for spectral enhancement inspired by mechanisms in the auditory system. Instead of simply amplifying sound, the method aimed to preserve contrast and emphasize informative components in a biologically grounded way. The paper helped establish companding as a useful framework for perceptually informed, noise-robust signal enhancement. Its wider significance lies in showing how ideas from hearing science can guide engineered algorithms for audio analysis and hearing technologies.

11. An Ultra-Low-Power Programmable Analog Bionic Ear Processor Sarpeshkar, Salthouse, Sit, Baker, Zhak, Lu, Turicchia, and Balster, IEEE Transactions on Biomedical Engineering. View Article

This paper introduced an ultra-low-power bionic ear processor that reduced power consumption by a factor of 25, helping move cochlear implants closer to long-life, fully implantable systems.
View Summary

This work presented a programmable analog cochlear-implant processor that operated at just 211 µW while maintaining a 77-dB dynamic range. It showed that biologically inspired analog sound processing could achieve major energy savings without giving up practical performance. By demonstrating a 25-fold reduction in power consumption, the paper helped define a more realistic path toward smaller, longer-lasting cochlear-implant hardware.

12. Mathematical Phenomenology of Neural Stimulation by Periodic Fields Balduzzo, Ferro Milone, Minelli, Pittaro-Cadore, and Turicchia, Nonlinear Dynamics Psychol Life Sci. View Article

This paper explored how periodic electric fields may influence neural synchronization, coherence, and rhythmic brain activity, using mathematical models to connect stimulation effects with brain dynamics relevant to EEG.
View Summary

This work used mathematical models to study how periodic electric-field stimulation can affect collective neural behavior. It focused on synchronization, coherence, and rhythmic activity rather than only on single neurons, helping connect stimulation fields to broader brain dynamics. EEG rhythms are part of the wider context of the paper, while the main contribution is showing how periodic stimulation may shape coordinated neural activity and support more realistic modeling of stimulation effects.

13. Otoacoustic Emissions from Residual Oscillations of the Cochlear Basilar Membrane in a Human Ear Model Nobili, Vetešník, Turicchia, and Mammano, J Assoc Res Otolaryngol.. View Article

This paper helped clarify the inner-ear mechanisms behind otoacoustic-emission testing, supporting noninvasive methods used to assess cochlear function and hearing.
View Summary

This work used a human inner-ear model to study the cochlear mechanisms underlying otoacoustic emissions, which are widely used in noninvasive hearing assessment. By helping explain how these signals arise within the cochlea, the paper strengthened the interpretation of tests used to evaluate inner-ear function. Its broader relevance is clinical: better understanding of otoacoustic-emission measurements can improve hearing screening and assessment.

Selected Conference Proceedings (out of 24)

1. Ultra-Low-Power Electronics for Non-invasive Medical Monitoring Turicchia, Mandal, Tavakoli, Fay, Misra, Bohorquez, Sanchez, and Sarpeshkar, Proceedings of the IEEE Custom Integrated Circuits Conference.Invited paper; rated among the highest quality papers by the IEEE CICC 2009 review panel View Article

This invited conference paper showed how very low-power electronics can make non-invasive medical monitoring more practical for continuous, everyday use.
View Summary

The paper presented circuit and system strategies for non-invasive physiological monitoring with strong emphasis on low power and practical deployment. It addressed core constraints for wearable and home-based systems, including energy use, signal quality, portability, and overall integration. By focusing on architectures suitable for long-duration operation, the work helped move medical monitoring closer to continuous use outside traditional clinical settings. Its broader value lies in supporting more accessible platforms for preventive and longitudinal care.

2. A Low-Power Imager and Compression Algorithms for a Brain-Machine Visual Prosthesis for the Blind Turicchia, O'Halloran, Kumar, and Sarpeshkar, Proceedings of SPIE.Invited paper View Article

This invited paper explored how low-power imaging and efficient data compression could support visual prostheses designed to help restore useful vision.
View Summary

The paper described a low-power imager together with compression algorithms for a brain-machine visual prosthesis. It focused on reducing both sensing and data-handling burdens, which are major constraints in implantable and wearable neuroprosthetic systems. By combining image capture with efficient signal representation, the work advanced a practical systems approach to artificial vision rather than treating hardware and processing separately. Its longer-term importance lies in supporting prosthetic platforms that must balance visual function, power efficiency, and implementation feasibility.

3. An Analog Bionic Ear Processor with Zero-Crossing Detection Sarpeshkar, Baker, Salthouse, Sit, Turicchia, and Zhak, Proceedings of the IEEE International Solid State Circuits Conference (ISSCC). View Article

This conference paper presented a low-power bionic-ear processor inspired by how the auditory system works, with the goal of supporting better hearing-restoration hardware.
View Summary

The work reported an analog bionic-ear processor incorporating zero-crossing detection within a low-power auditory-processing architecture. It contributed to cochlear-implant engineering by showing how biologically motivated processing ideas can be implemented directly in efficient hardware rather than relying on more power-intensive computation. More broadly, it reflected a neuromorphic strategy of translating auditory-system principles into circuits with direct implant relevance. Its significance lies in strengthening the hardware foundation for long-lasting, resource-efficient hearing prostheses.

4. A Companding Front End for Noise-Robust Automatic Speech Recognition Guiness, Raj, Nielsen, Turicchia, and Sarpeshkar, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing.Rated among the top papers in its category by the IEEE Signal Processing Society View Article

This paper introduced an auditory-inspired signal-processing front end designed to make machine listening more reliable in noisy everyday environments.
View Summary

The paper presented a companding front end for robust audio analysis in the presence of background noise. Drawing on auditory-inspired processing, it aimed to preserve useful acoustic information while improving system robustness before higher-level interpretation. The work connected biologically motivated signal processing with broader machine-listening challenges in real environments, where noise can strongly degrade performance. Its broader contribution lies in advancing front-end strategies for more dependable audio understanding in practical, noisy settings.

5. Evaluation of Strategies for Noise Reduction in Cochlear Implants Loizou, Kasturi, Turicchia, Sarpeshkar, Dorman, and Spahr, Conference on Implantable Auditory Prostheses. View Article

This conference contribution examined noise-reduction strategies for cochlear implants, focusing on whether signal-processing methods lead to meaningful improvements in hearing.
View Summary

The work evaluated strategies for reducing noise in cochlear-implant processing, an issue directly tied to speech understanding in difficult listening environments. Rather than focusing on algorithm design alone, it addressed how enhancement approaches perform in a context relevant to implant users. That made the contribution important as a bridge between engineering concepts and auditory outcome assessment. Its broader value lies in helping identify which processing strategies are most likely to improve real hearing-assistive performance.

PATENTS AND PATENT APPLICATIONS

View detailed patent-family analysis and citation impact

Patent list

  1. L. Turicchia and R. Sarpeshkar, “System and Method for Spectral Enhancement Employing Compression and Expansion,” United States Patent 7787640, published August 31, 2010. US-7787640
  2. L. Turicchia, S. Mandal, and R. Sarpeshkar, “A Wearable System for Monitoring Physiological Signals,” U.S. Patent Application filed February 4, 2010, published August 5, 2010. U.S. Utility Application Serial No. 12/700,214. United States Patent Application No. US-2010-0198094-A1.
  3. R. Sarpeshkar, L. Turicchia, and S. Mandal, “Advanced Coding Strategies for Visual Prostheses,” International Patent Application PCT/US2009/053102 (WO/2010/017448A1), filed August 7, 2009, published February 11, 2010.
  4. B. Ramakrishnan, B. Schmidt-Nielsen, L. Turicchia, and R. Sarpeshkar, “Method and System for FFT-Based Companding for Automatic Speech Recognition,” United States Patent 7672842, published March 3, 2010. US-7672842
  5. R. Sarpeshkar, L. Turicchia, and S. Mandal, “Advanced Coding Strategies for Visual Prostheses,” U.S. Patent Application filed August 7, 2009, published February 11, 2010. US-2010-0036457
  6. L. Turicchia, S. Mandal, and R. Sarpeshkar, “A Wearable System for Monitoring Physiological Signals,” U.S. Provisional Patent Application No. 61/149,801, filed on February 4, 2009.
  7. R. Sarpeshkar and L. Turicchia, “Cardiovascular Signal Processing Apparatus and Method Employing Feedback,” U.S. Provisional Patent Application, filed September 2008.
  8. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “Speech Processing Apparatus and Method Employing Feedback,” U.S. Patent Application filed August 15, 2008.
  9. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “Speech Processing Apparatus and Method Employing Feedback,” International Patent Application PCT/US08/73240 (WO/2009/023807), filed August 18, 2008, published February 19, 2009.
  10. B. Ramakrishnan, B. Schmidt-Nielsen, L. Turicchia, and R. Sarpeshkar, “Method and System for FFT-Based Companding for Automatic Speech Recognition,” U.S. Patent Application Number 11/493,196, published January 31, 2008. US-2008-0027708A1
  11. L. Turicchia and R. Sarpeshkar, “System and Method for Spectral Enhancement Employing Compression and Expansion,” U.S. Patent Application 10/830,561, published December 16, 2004. US-2004-0252850-A1
  12. L. Turicchia and R. Sarpeshkar, “System and Method for Spectral Enhancement Employing Compression and Expansion,” International Patent Application PCT/US2004/012674 (WO/2004/097799), published November 11, 2004.
  13. L. Turicchia and R. Sarpeshkar, “System and Method for Spectral Enhancement Employing Compression and Expansion,” European Patent Application No. 1618559, published January 25, 2006. EP-2004-0760369
  14. R. Sarpeshkar and L. Turicchia, “System and Method for Distributed Gain Control,” U.S. Patent No. 7,415,118, published August 19, 2008. US-7,415,118-B2
  15. R. Sarpeshkar and L. Turicchia, “System and Method for Distributed Gain Control,” U.S. Patent Application No. 10/625,360, published July 15, 2004. US-2004-0136545-A1
  16. R. Sarpeshkar and L. Turicchia, “System and Method for Distributed Gain Control for Spectrum Enhancement,” International Patent Application No. PCT/US2003/022795 (WO/2004/010417), published January 29, 2004.
  17. R. Sarpeshkar and L. Turicchia, “System and Method for Distributed Gain Control for Spectrum Enhancement,” European Patent Application No. 1529281, published November 29, 2006. EP-2003-0765863

SELECTED PROFESSIONAL SERVICE FOR SCIENTIFIC JOURNALS

  1. IEEE Transactions on Biomedical Circuits and Systems (TBCAS)
  2. The Journal of the Acoustical Society of America (JASA)
  3. IEEE Transactions on Signal Processing (TSP)
  4. IEEE Transactions on Audio, Speech and Language Processing (TASLP)
  5. IEEE Transactions on Information Technology in Biomedicine (T-ITB)
  6. Annals of Biomedical Engineering
  7. Speech Communication (SPECOM)
  8. Journal of Vibration and Control (JVC)

EXTENDED PUBLICATION LIST

Journal Articles

  1. B. I. Rapoport, L. Turicchia, W. Wattanapanitch, T. J. Davidson, R. Sarpeshkar, “Efficient Universal Computing Architectures for Decoding Neural Activity,” PLoS ONE, Vol. 7, No. 9, 2012.
  2. K. H. Wee, L. Turicchia and R. Sarpeshkar, “An Articulatory Silicon Vocal Tract for Speech and Hearing Prostheses,” IEEE Transactions on Biomedical Circuits and Systems, Invited Paper (4 out of 83 submissions), Vol. 5, No. 4, pp. 339-346, July 2011. DOI: 10.1109/TBCAS.2011.2159858, ISSN: 1932-4545.
  3. L. Turicchia and G. Li, “Sensing and Computing in Wearable Robots,” Transactions on Information Technology in Biomedicine, Guest Editorial, Vol. 15, No. 4, pp. 503-504, July 2011. DOI: 10.1109/TITB.2011.2160245, ISSN: 1089 -7771.
  4. L. Turicchia, B. Do Valle, J. Bohorquez, W. Sanchez, V. Misra, L. Fay, M. Tavakoli, and R. Sarpeshkar, “Ultralow-Power Electronics for Cardiac Monitoring,” Invited Paper, IEEE Transactions on Circuits and Systems I. Vol. 57, No. 9, pp. 2279-2290, 2010. DOI: 10.1109/TCSI.2010.2071610, ISSN: 1549-8328.
  5. M. Tavakoli, L. Turicchia, and R. Sarpeshkar, “An Ultra-Low-Power Pulse Oximeter Implemented with an Energy-Efficient Transimpedance Amplifier,” IEEE Transactions on Biomedical Circuits and Systems, Vol. 4, No. 1, pp. 27-38, 2010. DOI: 10.1109/TBCAS.2009.2033035, ISSN: 1932-4545. (Second top accessed article in the February 2010 IEEE Transactions on Biomedical Circuits and Systems.)
  6. S. Mandal, L. Turicchia, and R. Sarpeshkar, “A Low-Power Battery-Free Tag for Body Sensor Networks,” IEEE Pervasive Computing, Vol. 9, No. 1, pp. 71-77, 2010. DOI: 10.1109/MPRV.2010.1, ISSN: 1536-1268.
  7. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “An Analog Integrated-Circuit Vocal Tract,” IEEE Transactions on Biomedical Circuits and Systems, Vol. 2, No. 4, pp. 316-327, 2008. DOI: 10.1109/TBCAS.2008.2005296, ISSN: 1932-4545.
  8. B. Raj, L. Turicchia, B. Schmidt-Nielsen, and R. Sarpeshkar, “An FFT-Based Companding Front End for Noise-Robust Automatic Speech Recognition,” EURASIP Journal on Audio, Speech, and Music Processing, Vol. 2007, Article ID 65420, 13 pages, 2007. DOI: 10.1155/2007/65420, ISSN: 1687-4714.
  9. A. Oxenham, A. Simonson, L. Turicchia, and R. Sarpeshkar, “Evaluation of Companding-Based Spectral Enhancement Using Simulated Cochlear-Implant Processing,” The Journal of the Acoustical Society of America, Vol. 121, No. 3, pp. 1709-1716, 2007. DOI: 10.1121/1.2434757, ISSN: 0001-4966.
  10. L. Turicchia and R. Sarpeshkar, “A Bio-Inspired Companding Strategy for Spectral Enhancement,” IEEE Transactions on Speech and Audio Processing, Vol. 13, No. 2, pp. 243-253, 2005. DOI: 10.1109/TSA.2004.841044, ISSN: 1063-6676.
  11. R. Sarpeshkar, C. Salthouse, J.J. Sit, M. Baker, S. Zhak, T. Lu, L. Turicchia, and S. Balster, “An Ultra-Low-Power Programmable Analog Bionic Ear Processor,” IEEE Transactions on Biomedical Engineering, Vol. 52, No. 4, pp. 711-727, 2005. DOI: 10.1109/TBME.2005.844043, ISSN: 0018-9294.
  12. M. Balduzzo, F. Ferro Milone, T.A. Minelli, I. Pittaro-Cadore, and L. Turicchia, “Mathematical Phenomenology of Neural Stimulation by Periodic Fields,” Nonlinear Dynamics Psychol Life Sci, Vol. 7, No. 2, pp. 115-137, 2003. DOI: 10.1023/A:1021460730922, ISSN: 1090-0578.
  13. R. Nobili, A. Vetešník, L. Turicchia, F. Mammano, “Otoacoustic Emissions from Residual Oscillations of the Cochlear Basilar Membrane in a Human Ear Model,” J Assoc Res Otolaryngol., Vol. 4, No. 4, pp. 478-494, 2003. DOI: 10.1007/s10162-002-3055-1, ISSN: 1525-3961.
  14. M. Balduzzo, T. A. Minelli, and L. Turicchia, “Signal Analysis and Simulation of the EEG Activity,” International Journal of Chaos Theory and Applications, Vol. 4, No. 2-3, pp. 7-14, 1999. ISSN: 1453-1437.
  15. T. A. Minelli and L. Turicchia, “Progressive Coherence Patterns for Electroencephalographic phenomenology,” Nonlinear Dynamics Psychol Life Sci, Vol. 3, No. 2, pp. 129-142, 1999. DOI: 10.1023/A:1022022622251, ISSN: 1090-0578.
  16. F. Ferro Milone, T. A. Minelli, and L. Turicchia, “Neuron Synchronization and Human EEG Phenomenology Simulation,” Nonlinear Dynamics Psychol Life Sci, Vol. 2, No. 1, pp. 21-33, 1998. DOI: 10.1023/A:1022372126812, ISSN: 1090-0578.

Invited Papers

  1. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “A Speech Locked Loop for Cochlear Implants and Speech Prostheses,” Invited Paper, Proceedings of the IEEE 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2010), Rome, Italy, November 7-10, 2010. DOI: 10.1109/ISABEL.2010.5702864, ISBN: 978-1-4244-8131-6.
  2. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “Biologically inspired silicon vocal tract,” Invited Paper, SPIE Newsroom, International Society for Optics and Photonics, 3 February 2010. DOI: 10.1117/2.1201001.1807, ISSN: 1818-2259. (Second most popular article in the February 2010 SPIE Newsroom.)
  3. L. Turicchia, S. Mandal, M. Tavakoli, L. Fay, V. Misra, J. Bohorquez, W. Sanchez, and R. Sarpeshkar, “Ultra-Low-Power Electronics for Non-invasive Medical Monitoring,” Invited Paper, Proceedings of the IEEE Custom Integrated Circuits Conference (CICC 2009), San Jose, California, USA, September 13-16, 2009. DOI: 10.1109/CICC.2009.5280892, ISBN: 978-1-4244-4071-9. (Rated among the highest quality papers by the IEEE CICC 2009 review panel.)
  4. J. Bohorquez, W. Sanchez, L. Turicchia, and R. Sarpeshkar, “An Integrated-Circuit Switched-Capacitor Model and Implementation of the Heart,” Invited Paper, Proceedings of the IEEE International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2008), Aalborg, Denmark, 2008. DOI: 10.1109/ISABEL.2008.4712624, ISBN: 978-1-4244-2647-8.
  5. L. Turicchia, M. O'Halloran, D. P. Kumar, and R. Sarpeshkar, “A Low-Power Imager and Compression Algorithms for a Brain-Machine Visual Prosthesis for the Blind,” Invited Paper, in Biosensing, edited by Manijeh Razeghi, Hooman Mohseni, Proceedings of SPIE, Vol. 7035 (SPIE, Bellingham, WA 2008) 703510. DOI: 10.1117/12.797211, ISSN: 0277-786X.

Conference Proceedings

  1. R. Danial, S. S. Woo, L. Turicchia, and R. Sarpeshkar, “Analog Transistor Models of Bacterial Genetic Circuits,” Proceedings of 2011 IEEE Symposium on Biological Circuits and Systems (BioCAS), November 2011.
  2. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “Speech-coding strategies for speech prostheses,” Program No. D.18, Brain-Machine Interface, 2010 Neuroscience Meeting, San Diego, CA, Society for Neuroscience, 2010.
  3. A. I. Rapoport, W. Wattanapanitch, L. Turicchia, and R. Sarpeshkar, “Implantable neural decoding systems,” Program No. D.18, Brain-Machine Interface, 2010 Neuroscience Meeting, San Diego, CA, Society for Neuroscience, 2010.
  4. W. Wattanapanitch, D. Kumar, B. Do Valle, L. Turicchia, B. I. Rapoport, S. K. Arfin, S. Mandal, E. Hwang, R. A. Andersen, R. Sarpeshkar, “An ultra-low-power 32-channel wireless neural recording interface,” Program No. D.18, Brain-Machine Interface, 2010 Neuroscience Meeting, San Diego, CA, Society for Neuroscience, 2010.
  5. K. H. Wee, L. Turicchia, R. Sarpeshkar, “An Articulatory Speech-Prosthesis System,” Proceedings of the IEEE International Conference on Body Sensor Networks (BSN 2010), pp. 133-138, 7-9 June 2010. DOI: 10.1109/BSN.2010.29.
  6. Z. Al Bawab, L. Turicchia, R. M. Stern, and B. Raj, “Deriving Vocal Tract Shapes From ElectroMagnetic Articulograph Data Via Geometric Adaptation and Matching,” Proceedings of Interspeech 2009, International Speech Communication Association (ISCA), Brighton, U.K., September 6-10, 2009.
  7. S. Mandal, L. Turicchia, R. Sarpeshkar, “A Battery-Free Tag for Wireless Monitoring of Heart Sounds,” Proceedings of the IEEE International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2009), Berkeley, CA, USA, June 2009. DOI: 10.1109/BSN.2009.11, ISBN: 978-0-7695-3644-6.
  8. K. H. Wee, L. Turicchia, and R. Sarpeshkar, “An Analog Bionic Vocal Tract,” Proceedings of the IEEE Biomedical Circuits and Systems Conference (BioCAS 2008), pp. 281-284, Baltimore, MD, USA, 2008. DOI: 10.1109/BIOCAS.2008.4696929, ISBN: 978-1-4244-2878-6.
  9. G. Rota, L. Turicchia, R. Veit, M. Guazzelli, N. Birbaumer, and G. Dogil, “Perceptual learning of speech processed by a cochlear implant simulator—An fMRI investigation,” International Journal of Psychophysiology, Vol. 69, No. 3, pp. 225-226, 2008. DOI: 10.1016/j.ijpsycho.2008.05.072, ISSN: 0167-8760.
  10. A. Simonson, A. Oxenham, L. Turicchia, and R. Sarpeshkar, “Evaluation of companding-based spectral enhancement using simulated cochlear-implant processing”, American Auditory Society Meeting (AAS2006), Scottsdale, AZ, USA, March 5-7, 2006.
  11. R. Sarpeshkar, M. Baker, C. Salthouse, J.J. Sit, L. Turicchia, and S. Zhak, “An Analog Bionic Ear Processor with Zero-Crossing Detection,” Proceedings of the IEEE International Solid State Circuits Conference (ISSCC’05), Paper 4.2, pp. 78-79, San Francisco, CA, USA, February 6-10, 2005. DOI: 10.1109/ISSCC.2005.1493877, ISBN: 0-7803-8904-2.
  12. J. Guiness, B. Raj, B. Nielsen, L. Turicchia, and R. Sarpeshkar, “A Companding Front End for Noise-Robust Automatic Speech Recognition,” Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’05), pp. 249-252, Philadelphia, PA, USA, March 18-23, 2005. DOI: 10.1109/ICASSP.2005.1415097, ISBN: 0-7803-8874-7. (Rated among the top papers in its category by the IEEE Signal Processing Society.)
  13. P. Loizou, K. Kasturi, L. Turicchia, R. Sarpeshkar, M. Dorman, and T. Spahr, “Evaluation of the Companding and Other Strategies for Noise Reduction in Cochlear Implants,” 2005 Conference on Implantable Auditory Prostheses, Pacific Grove, CA, USA, 2005.
  14. L. Turicchia, G. Depoli, G.A. Mian, and R. Nobili, “Audio analysis by a physiological auditory model,” Proceedings of the COST G-6 Conference on Digital Audio Effects (DAFx-00), December 7-9, 2000.
  15. M. Balduzzo, F. Ferro Milone, T. A. Minelli, and L. Turicchia, “Neuron Synchronization Mathematical Phenomenology,” 9-th International Conference of The Society for Chaos Theory in Psychology & Life Science, Berkeley, CA, USA, July 1999, SCTPLS Newsletter, Vol. 6, No. 4, p. 2, July 1999.
  16. P. Amodio, T. A. Minelli, A. Pesavento, and L. Turicchia, “Rumore browniano frazionario nell'EEG dell'encefalopatia epatica,” Atti del XIV Congresso della Società Italiana di Biofisica Pura e Applicata, Genova, Italy, September 1998, (CNR, Genova 1998), p. 100.
  17. F. Ferro Milone, G. Ferro Milone, T. A Minelli, L. Turicchia, and R. Zanini, “The Windowed Spectral Coherence and the Reference Problem,” I Mediterranean Neuroscience Conference, Montpellier, France, September 1997.
  18. T. A. Minelli, and L. Turicchia, “Nonlinear Analysis and Simulation of the EEG Time Series,” 27th European Mathematical Psychology Group (EMPG) Meeting, September 1996.
  19. F. Ferro Milone, T. A. Minelli, and L. Turicchia, “A Phenomenological Model of the Brain Rhythm Generation,” Third European Congress on Systems Science, Edizioni Kappa, Rome, Italy, 1996, pp. 787-791.
  20. F. Ferro Milone, T. A. Minelli, and L. Turicchia, “Studio della coerenza del segnale EEG in soggetti normali e pazienti dementi,” V Congresso di Informatica e Neuroscienze, Siena, Italy, October 1996.

Book Chapters

  1. L. Turicchia and R. Sarpeshkar, “The Silicon Cochlea: from Biology to Bionics,” Biophysics of the Cochlea: From Molecules to Models, World Scientific Publishing Company, New Jersey, USA, pp. 417-424, 2003. ISBN: 978-981-238-304-4.
  2. R. Nobili, A. Vetešník, L. Turicchia, and F. Mammano, “Otoacoustic emissions simulated in the time-domain by a hydrodynamic model of the human cochlea,” Biophysics of the Cochlea: From Molecules to Models, World Scientific Publishing Company, New Jersey, USA, pp. 524-530, 2003. ISBN: 978-981-238-304-4.
  3. C. Gabrieli, F. Ferro Milone, G. Ferro Milone, T. A. Minelli, and L. Turicchia, “From the Mathematical Anatomy to the Mathematical Physiology of Brain Co-operative Phenomena,” Chaos, Fractals, and Models, F. Marsella Guindani and G. Salvadori (eds), pp. 406-410, Italian University Press, Italy, 1998. ISBN: 88-8258-002-4.
  4. T. A. Minelli and L. Turicchia, “Nonlinear Simulation of the Electrocortical Activity,” Nonlinear Physics: theory and experiment (Nature, Structure and Properties of Nonlinear Phenomena), pp. 551-553, World Scientific Publishing Company, New Jersey, USA, 1996. ISBN: 978-981-022-559-9.