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Mohamad Sawan

Bio: Mohamad Sawan is an academic researcher from Westlake University. The author has contributed to research in topics: CMOS & Amplifier. The author has an hindex of 45, co-authored 746 publications receiving 9752 citations. Previous affiliations of Mohamad Sawan include École Normale Supérieure & McGill University.


Papers
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TL;DR: The design features a mixed-signal integrated circuit (IC) that handles conditioning, digitization, and time-division multiplexing of neural signals, and a digital IC that provides control, bandwidth reduction, and data communications for telemetry toward a remote host.
Abstract: We present a multichip structure assembled with a medical-grade stainless-steel microelectrode array intended for neural recordings from multiple channels. The design features a mixed-signal integrated circuit (IC) that handles conditioning, digitization, and time-division multiplexing of neural signals, and a digital IC that provides control, bandwidth reduction, and data communications for telemetry toward a remote host. Bandwidth reduction is achieved through action potential detection and complete capture of waveforms by means of onchip data buffering. The adopted architecture uses high parallelism and low-power building blocks for safety and long-term implantability. Both ICs are fabricated in a CMOS 0.18-mum process and are subsequently mounted on the base of the microelectrode array. The chips are stacked according to a vertical integration approach for better compactness. The presented device integrates 16 channels, and is scalable to hundreds of recording channels. Its performance was validated on a testbench with synthetic neural signals. The proposed interface presents a power consumption of 138 muW per channel, a size of 2.30 mm2, and achieves a bandwidth reduction factor of up to 48 with typical recordings.

208 citations

Journal ArticleDOI
TL;DR: This invited paper covers several techniques and methods employed to build high reliability circuits and systems dedicated to implement advanced implantable and wirelessly controlled smart medical devices such as sensors and microstimulateurs.
Abstract: Innovative circuits and systems techniques are required to build advanced smart medical devices (SMD). The high reliability and very low power consumption are among the main criteria that must be given priority to implement in such implantable and wirelessly controlled microsystems. A typical device is composed of several integrated modules to be assembled on a thin substrate providing placement flexibility in the body. Monitoring of electrode-tissue interface condition is needed for enhanced safety, and for enabling troubleshooting after implantation. In order to improve controllability and observability, fully integrated binary phase-shift-keying (BPSK) demodulation combined with a passive modulation method allows full-duplex data high data rate communication between external controllers and implants. Case studies such as peripheral nerve interfaces to recuperate bladder functions, cortical multichannel stimulator, as well as cortical monitoring devices are reported.

202 citations

Journal ArticleDOI
TL;DR: In this review, the latest developments of applications of AI in biomedicine, including disease diagnostics, living assistance, biomedical information processing, and biomedical research are summarized.

198 citations

Journal ArticleDOI
TL;DR: A fully integrated binary phase-shift keying (BPSK) demodulator, which is based on a hard-limited COSTAS loop topology, dedicated to such implantable medical devices, which may improve the controllability and observability of the overall implanted system.
Abstract: During the past decades, research has progressed on the biomedical implantable electronic devices that require power and data communication through wireless inductive links. In this paper, we present a fully integrated binary phase-shift keying (BPSK) demodulator, which is based on a hard-limited COSTAS loop topology, dedicated to such implantable medical devices. The experimental results of the proposed demodulator show a data transmission rate of 1.12 Mbps, less than 0.7 mW consumption under a supply voltage of 1.8 V, and silicon area of 0.2 mm/sup 2/ in the Taiwan Semiconductor Manufacturing Company (TSMC) CMOS 0.18-/spl mu/m technology. The transmitter satisfies the requirement of applications relative to high forward-transferring data rate, such as cortical stimulation. Moreover, the employment of BPSK demodulation along with a passive modulation method allows full-duplex data communication between an external controller and the implantable device, which may improve the controllability and observability of the overall implanted system.

182 citations

Journal ArticleDOI
TL;DR: A theoretical analysis of the efficiency of power transfer and phase-shift-keying communications through an inductive link and it is shown that the coplanar geometry approach is better suited for displacement tolerance.
Abstract: Biomedical implants require wireless power and bidirectional data transfer. We pursue our previous work on a novel topology for a multiple carrier inductive link by presenting the fabricated coils. We show that the coplanar geometry approach is better suited for displacement tolerance. We provide a theoretical analysis of the efficiency of power transfer and phase-shift-keying communications through an inductive link. An efficiency of up to 61% has been achieved experimentally for power transfer and a data rate of 4.16 Mb/s with a bit-error rate of less than 2 × 10-6 has been obtained with our fabricated offset quadrature phase-shift keying modules due to the inductive link optimization presented in this paper.

179 citations


Cited by
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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations