Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Powering mm-Size Wireless Implants for Brain-Machine Interfaces

Michael Mark

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2011-130
December 12, 2011

http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-130.pdf

Over the last couple of years, Brain-Machine Interfaces (BMI) based on microelectrode arrays have been shown to have the potential to substantially improve the quality of life for people suffering from debilitating conditions such as spinal cord injuries or limb loss. One of the most critical parts of a BMI system is the neural sensor. It is ideally implanted underneath the skull, reads out neural signals from the brain and transmits them wirelessly to a receiver outside the skull. The requirements on the electronics of such a sensor are extremely stringent, especially with respect to size and power consumption. Ideally, the overall size of the implanted sensor node is limited by the size of the sensor itself, rather than the electronics and the power source. This work investigates powering options for implants of sizes ranging from 10 mm by 10 mm down to 1 mm by 1 mm. Wireless power transfer is identified as the most promising option of doing so and is investigated in detail. It is shown, that for a given implant antenna size, an optimum combination of external antenna and frequency of operation exists that minimizes the overall link loss. In combination with limitations on the maximum transmit and received power due to health concerns, the maximum power available to mm-size implants as a function of size is derived. Two different AC-to-DC conversion circuit topologies, covering the expected input power and frequency range, are analyzed in detail and design guidelines for each are given. Finally, a 1 mm^3 proof-of-concept implementation of a wirelessly powered neural transponder is presented. It was tested in air and in animal and provides enough extra DC power to power a neural sensor front-end while supporting a 2 Mbps radio link. The presented tag is the smallest wireless neural tag reported to date and prooves the feasibility of remotely powered mm-size wireless neural implants.

Advisor: Jan M. Rabaey


BibTeX citation:

@phdthesis{Mark:EECS-2011-130,
    Author = {Mark, Michael},
    Title = {Powering mm-Size Wireless Implants for Brain-Machine Interfaces},
    School = {EECS Department, University of California, Berkeley},
    Year = {2011},
    Month = {Dec},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-130.html},
    Number = {UCB/EECS-2011-130},
    Abstract = {Over the last couple of years, Brain-Machine Interfaces (BMI) based on microelectrode arrays have been shown to have the potential to substantially improve the quality of life for people suffering from debilitating conditions such as spinal cord injuries or limb loss. One of the most critical parts of a BMI system is the neural sensor. It is ideally implanted underneath the skull, reads out neural signals from the brain and transmits them wirelessly to a receiver outside the skull. The requirements on the electronics of such a sensor are extremely stringent, especially with respect to size and power consumption. Ideally, the overall size of the implanted sensor node is limited by the size of the sensor itself, rather than the electronics and the power source. 

This work investigates powering options for implants of sizes ranging from 10 mm by 10 mm down to 1 mm by 1 mm. Wireless power transfer is  identified as the most promising option of doing so and is investigated in detail. It is shown, that for a given implant antenna size, an optimum  combination of external antenna and frequency of operation exists that minimizes the overall link loss. In combination with limitations on the maximum transmit and received power due to health concerns, the maximum power available to mm-size implants as a function of size is derived. Two different AC-to-DC conversion circuit topologies, covering the expected input power and frequency range, are analyzed in detail and design guidelines for each are given. 

Finally, a 1 mm^3  proof-of-concept implementation of a wirelessly powered neural transponder is presented. It was tested in air and in animal and provides enough extra DC power to power a neural sensor front-end while supporting a 2 Mbps radio link.  The presented tag is the smallest wireless neural tag reported to date and prooves the feasibility of remotely powered mm-size wireless neural implants.}
}

EndNote citation:

%0 Thesis
%A Mark, Michael
%T Powering mm-Size Wireless Implants for Brain-Machine Interfaces
%I EECS Department, University of California, Berkeley
%D 2011
%8 December 12
%@ UCB/EECS-2011-130
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-130.html
%F Mark:EECS-2011-130