MODEE-LID: Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Hurta:2023:DDECS,

• author = "Martin Hurta and Vojtech Mrazek and Michaela Drahosova and Lukas Sekanina",
• booktitle = "2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)",
• title = "{MODEE-LID:} Multiobjective Design of Energy-Efficient Hardware Accelerators for Levodopa-Induced Dyskinesia Classifiers",
• year = "2023",
• pages = "155--160",
• 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 percent.",
• keywords = "genetic algorithms, genetic programming, Drugs, Energy consumption, Wearable computers, Estimation, Feature extraction, Energy efficiency, levodopa-induced dyskinesia, energy efficient, hardware accelerator, multiobjective design",
• DOI = "doi:10.1109/DDECS57882.2023.10139399",
• ISSN = "2473-2117",
• month = may,
• notes = "Also known as \cite{10139399}",

}

Genetic Programming entries for Martin Hurta Vojtech Mrazek Michaela Sikulova Lukas Sekanina

Citations