Publication detail
MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers
HURTA, M. MRÁZEK, V. DRAHOŠOVÁ, M. SEKANINA, L.
Original Title
MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers
Type
conference paper
Language
English
Original Abstract
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 %.
Keywords
levodopa-induced dyskinesia, energy efficient,
hardware accelerator, multiobjective design
Authors
HURTA, M.; MRÁZEK, V.; DRAHOŠOVÁ, M.; SEKANINA, L.
Released
3. 5. 2023
Publisher
Institute of Electrical and Electronics Engineers
Location
Tallinn
ISBN
979-8-3503-3277-3
Book
2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)
Pages from
155
Pages to
160
Pages count
6
URL
BibTex
@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"
}