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"
}