Publication Details
MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers
Mrázek Vojtěch, Ing., Ph.D. (DCSY)
Drahošová Michaela, Ing., Ph.D. (DCSY)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
levodopa-induced dyskinesia, energy efficient, hardware accelerator, multiobjective design
Taking levodopa, a drug used to treat symptoms of Parkinson's disease, is often
connected with severe side effects, known as Levodopa-induced dyskinesia (LID).
It can fluctuate in severity throughout the day and thus is difficult to classify
during a short period of a physician's visit. A low-power wearable classifier
enabling long-term and continuous LID classification would thus significantly
help with LID detection and dosage adjustment. This paper deals with an automated
design of energy-efficient hardware accelerators of LID classifiers that can be
implemented in wearable devices. The accelerator consists of a feature extractor
and a classification circuit co-designed using genetic programming (GP). We also
introduce and evaluate a fast and accurate energy consumption estimation method
for the target architecture of considered classifiers. In a multiobjective design
scenario, GP evolves solutions showing the best trade-offs between accuracy and
energy. Compared to the state-of-the-art solutions, the proposed method leads to
classifiers showing a comparable accuracy while the energy consumption is reduced
by 49 %.
@inproceedings{BUT184451,
author="Martin {Hurta} and Vojtěch {Mrázek} and Michaela {Drahošová} and Lukáš {Sekanina}",
title="MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers",
booktitle="2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)",
year="2023",
pages="155--160",
publisher="Institute of Electrical and Electronics Engineers",
address="Tallinn",
doi="10.1109/DDECS57882.2023.10139399",
isbn="979-8-3503-3277-3",
url="https://ieeexplore.ieee.org/document/10139399"
}