Medical Design Briefs - April 2023 - 21

Neuro-Chip Manages Brain Disorders
A neural interface
identifies and suppresses
symptoms of neurological
disorders.
EPFL Lausanne, Switzerland
Researchers have combined low
power chip design, machine learning
algorithms, and soft implantable electrodes
to produce a neural interface
that can identify and suppress symptoms
of various neurological disorders.
The closed-loop neuromodulation
system-on-chip can detect and alleviate
disease symptoms. Using a 256-channel
high-resolution sensing array and an
energy-efficient machine learning processor,
the system can extract and classify
a broad set of biomarkers from real
patient data and animal models of disease
in-vivo, leading to a high degree of
accuracy in symptom prediction. The
NeuralTree system was developed by
Mahsa Shoaran of the Integrated
Neuro technologies Laboratory in the
School of Engineering in collaboration
with Stéphanie Lacour in the Laboratory
for Soft Bioelectronic.
" NeuralTree benefits from the accuracy
of a neural network and the hardware
efficiency of a decision tree algorithm, "
Shoaran says. " It's the first time
we've been able to integrate such a
complex, yet energy-efficient neural
interface for binary classification tasks,
such as seizure or tremor detection, as
well as multi-class tasks such as finger
movement classification for neuroprosthetic
applications. "
Their results were presented at
the 2022 IEEE International
Solid-State
Circuits Conference and
published in the IEEE Journal of SolidState
Circuits.1,2
Asahi_2022_MDB_Metal_printer.pdf 1 5/31/2022 9:44:52 PM
n Efficiency, Scalability,
and Versatility
NeuralTree functions by extracting neural
biomarkers - patterns of electrical signals
known to be associated with certain
neurological disorders - from brain
waves. It then classifies the signals and indicates
whether they herald an impending
epileptic seizure or Parkinsonian tremor,
for example. If a symptom is detected, a
neurostimulator - also located on the
chip - is activated, sending an electrical
pulse to block it.
Shoaran explains that NeuralTree's
unique design gives the system an unprecedented
degree of efficiency and versatility
compared to the state-of-the-art. The
chip boasts 256 input channels, compared
to 32 for previous machine learning
embedded devices, allowing more
high-resolution data to be processed on
the implant. The chip's area-efficient design
means that it is also extremely small
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Medical Design Briefs, April 2023
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Medical Design Briefs - April 2023

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