Literature DB >> 30582551

A 0.338 cm3, Artifact-Free, 64-Contact Neuromodulation Platform for Simultaneous Stimulation and Sensing.

Dejan Rozgic, Vahagn Hokhikyan, Wenlong Jiang, Ippei Akita, Sina Basir-Kazeruni, Hariprasad Chandrakumar, Dejan Markovic.   

Abstract

Neuromodulation (NM) is the alteration of nervous tissue function through targeted delivery of a stimulus, such as electrical stimulation, into the affected neurological sites in the body. We present a bidirectional NM interface that features 100 mVpp linear input range and ability to sense data concurrent with stimulation (without blanking). The system includes a flexible 8-driver-to-64-contact custom waveform stimulator able to deliver up to 5.1 mA per driver and a 64-contact sensing unit with online blind artifact rejection unit. This artifact rejection unit removes stimulation artifacts from recorded data and allows extraction of neural biomarkers. The NM interface also features an efficient, integrated power management unit that can support various power delivery options. The proposed 64-contact interface satisfies design requirements of human-grade brain implants at unprecedented level of electronic miniaturization compared to state-of-the-art.

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Year:  2018        PMID: 30582551     DOI: 10.1109/TBCAS.2018.2889040

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  7 in total

1.  A Bidirectional Neural Interface SoC With Adaptive IIR Stimulation Artifact Cancelers.

Authors:  Aria Samiei; Hossein Hashemi
Journal:  IEEE J Solid-State Circuits       Date:  2021-02-09       Impact factor: 6.126

2.  Concurrent stimulation and sensing in bi-directional brain interfaces: a multi-site translational experience.

Authors:  Juan Ansó; Moaad Benjaber; Brandon Parks; Samuel Parker; Carina Renate Oehrn; Matthew Petrucci; Ro'ee Gilron; Simon Little; Robert Wilt; Helen Bronte-Stewart; Aysegul Gunduz; David Borton; Philip A Starr; Timothy Denison
Journal:  J Neural Eng       Date:  2022-03-31       Impact factor: 5.043

Review 3.  Closed-Loop Neural Prostheses With On-Chip Intelligence: A Review and a Low-Latency Machine Learning Model for Brain State Detection.

Authors:  Bingzhao Zhu; Uisub Shin; Mahsa Shoaran
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2021-12-09       Impact factor: 3.833

4.  Design and Testing of Stimulation and Myoelectric Recording Modules in an Implanted Distributed Neuroprosthetic System.

Authors:  Nathaniel Makowski; Alexandru Campean; Joris Lambrecht; James Buckett; James Coburn; Ronald Hart; Michael Miller; Fred Montague; Timothy Crish; Michael Fu; Kevin Kilgore; P Hunter Peckham; Brian Smith
Journal:  IEEE Trans Biomed Circuits Syst       Date:  2021-05-25       Impact factor: 5.234

5.  A Neural Recording and Stimulation Chip with Artifact Suppression for Biomedical Devices.

Authors:  Xu Liu; Juzhe Li; Tao Chen; Wensi Wang; Minkyu Je
Journal:  J Healthc Eng       Date:  2021-08-27       Impact factor: 2.682

6.  Very High Bit Rate Near-Field Communication with Low-Interference Coils and Digital Single-Bit Sampling Transceivers for Biomedical Sensor Systems.

Authors:  Sebastian Stoecklin; Elias Rosch; Adnan Yousaf; Leonhard Reindl
Journal:  Sensors (Basel)       Date:  2020-10-23       Impact factor: 3.576

7.  Methods for Lowering the Power Consumption of OS-Based Adaptive Deep Brain Stimulation Controllers.

Authors:  Roberto Rodriguez-Zurrunero; Alvaro Araujo; Madeleine M Lowery
Journal:  Sensors (Basel)       Date:  2021-03-28       Impact factor: 3.576

  7 in total

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