Miniature Wireless Neural Implants

Mohammad Meraj Ghanbari

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2024-195
December 1, 2024

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2024/EECS-2024-195.pdf

In this work, we present miniature wireless neural implants capable of recording and transmitting neural activity from deeply-seated peripheral nerves. In order to reduce implant-induced trauma and the likelihood of post-implant infection and to enable minimally-invasive implantation techniques, such as injection, the primary design goals of these implants are miniaturization and wireless operation in a multi-implant setting. These implants are comprised of an integrated circuit and a piezoceramic (used as an acoustic antenna). The piezoceramic, piezo, dominates the overall volume of the implant. Therefore, here, we provide a systematic design approach for the geometry of the implant piezo and operation frequency to minimize the overall volume of the implant. These miniature implants harvest energy from ultrasound wavelets launched by an external interrogator. They also communicate data through the same ultrasound link using a technique known as backscattering. A critical design aspect of an ultrasonic backscatter communication link is the response of the piezo acoustic reflection coefficient Γ with respect to the variable shunt impedance, ZE, of the implant uplink modulator. Due to the complexity of the piezo governing equations and multi-domain, electro-acoustical nature of the piezo, Γ(ZE) has often been characterized numerically and the implant uplink modulator has been designed empirically resulting in sub-optimal performance in terms of data rate and linearity. Here, we present experimentally validated closed-form expressions for Γ(ZE) under various boundary conditions. We conclude that Γ is approximately linearly proportional to the voltage across the piezo when operating at the series or parallel resonant frequencies. We further demonstrate two linear uplink backscatter modulators and incorporate them into the active rectifier of the implant ICs. One of these modulators perform end-to-end linear analog modulation, while the other implements quasi-digital m-level ASK modulator to provide immunity to carrier noise while achieving a substantially higher data rate (by a factor of log2(m)) relative to the commonly-used on-off keying modulation. Moreover, a key aspect of the wireless communication channel for these miniature neural implants is the multiple-access feature of the link. Therefore, we demonstrate integration of code-division and time-division multiple-access (CDMA and TDMA) into the uplink communication protocols of these implants. These protocols allow communications with a network of these implants using a single-element low-cost external interrogator. The functionality of both of the proposed implants are experimentally verified.

Advisor: Rikky Muller

"; ?>

BibTeX citation:

@phdthesis{Ghanbari:EECS-2024-195,
    Author = {Ghanbari, Mohammad Meraj},
    Title = {Miniature Wireless Neural Implants},
    School = {EECS Department, University of California, Berkeley},
    Year = {2024},
    Month = {Dec},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2024/EECS-2024-195.html},
    Number = {UCB/EECS-2024-195},
    Abstract = {In this work, we present miniature wireless neural implants capable of recording and transmitting neural activity from deeply-seated peripheral nerves. In order to reduce implant-induced trauma and the likelihood of post-implant infection and to enable minimally-invasive implantation techniques, such as injection, the primary design goals of these implants are miniaturization and wireless operation in a multi-implant setting.
These implants are comprised of an integrated circuit and a piezoceramic (used as an acoustic antenna). The piezoceramic, piezo, dominates the overall volume of the implant. Therefore, here, we provide a systematic design approach for the geometry of the implant piezo and operation frequency to minimize the overall volume of the implant.
These miniature implants harvest energy from ultrasound wavelets launched by an external interrogator. They also communicate data through the same ultrasound link using a technique known as backscattering. A critical design aspect of an ultrasonic backscatter communication link is the response of the piezo acoustic reflection coefficient Γ with respect to the variable shunt impedance, ZE, of the implant uplink modulator. Due to the complexity of the piezo governing equations and multi-domain, electro-acoustical nature of the piezo, Γ(ZE) has often been characterized numerically and the implant uplink modulator has been designed empirically resulting in sub-optimal performance in terms of data rate and linearity. Here, we present experimentally validated closed-form expressions for Γ(ZE) under various boundary conditions. We conclude that Γ is approximately linearly proportional to the voltage across the piezo when operating at the series or parallel resonant frequencies. We further demonstrate two linear uplink backscatter modulators and incorporate them into the active rectifier of the implant ICs. One of these modulators perform end-to-end linear analog modulation, while the other implements quasi-digital m-level ASK modulator to provide immunity to carrier noise while achieving a substantially higher data rate (by a factor of log2(m)) relative to the commonly-used on-off keying modulation.
Moreover, a key aspect of the wireless communication channel for these miniature neural implants is the multiple-access feature of the link. Therefore, we demonstrate integration of code-division and time-division multiple-access (CDMA and TDMA) into the uplink communication protocols of these implants. These protocols allow communications with a network of these implants using a single-element low-cost external interrogator. The functionality of both of the proposed implants are experimentally verified.}
}

EndNote citation:

%0 Thesis
%A Ghanbari, Mohammad Meraj
%T Miniature Wireless Neural Implants
%I EECS Department, University of California, Berkeley
%D 2024
%8 December 1
%@ UCB/EECS-2024-195
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2024/EECS-2024-195.html
%F Ghanbari:EECS-2024-195