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29 - Reducing the implant footprint: low-area neural recording

from Part VI - Brain interfaces

Published online by Cambridge University Press:  05 September 2015

By
Rikky Muller ,
Simone Gambini  and
Jan M. Rabaey
Edited by
Sandro Carrara  and
Krzysztof Iniewski
Rikky Muller
Affiliation:
University of California, Berkeley
Simone Gambini
Affiliation:
University of Melbourne
Jan M. Rabaey
Affiliation:
University of California, Berkeley
Sandro Carrara
Affiliation:
École Polytechnique Fédérale de Lausanne
Krzysztof Iniewski
Affiliation:
Redlen Technologies Inc., Canada
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Summary

Introduction to motor prosthetics

Fritsch and Hitzig first discovered the motor cortex in 1870 [1], althoughthe best-known experimental mapping of the motor cortex dates back toPenfield’s experiments in 1937 [2] using electrical stimulation toactivate muscle groups in patients undergoing surgery for epilepsy. It wasnot until the 1980s, over 100 years since the discovery of the motor cortex,that population coding [3] was proposed and thus the beginnings of decodingneural signals in the motor cortex into their corresponding motorfunction.

In 1998 the first human was implanted with a brain–machine interface(BMI) of high enough quality to simulate movement and demonstratedtwo-dimensional control of a mouse cursor [4],[5]. Since then, there hasbeen an explosion of demonstrations of motor prosthetic control of computercursors and robotic arms by both primates and humans. In the last year, thesame group demonstrated robotic arm control with four degrees of freedom ina tetraplegic patient [6]. These demonstrations mark a significant step inbringing BMIs from the research arena to viable medical devices, but anumber of technological hurdles must still be overcome to make this areality.

A simplified diagram of a BMI system is exemplified in Figure 29.1. A fullBMI system involves a recording device to take signals directly from themotor cortex.

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Type
Chapter
Information
Handbook of Bioelectronics
Directly Interfacing Electronics and Biological Systems
 , pp. 352 - 364
Publisher: Cambridge University Press
Print publication year: 2015

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