Automated Levodopa-induced dyskinesia assessment

التفاصيل البيبلوغرافية
العنوان: Automated Levodopa-induced dyskinesia assessment
المؤلفون: Spyridon Konitsiotis, Dimitrios I. Fotiadis, Georgios Rigas, Markos G. Tsipouras, Panagiota Bougia, Alexandros T. Tzallas
المصدر: Scopus-Elsevier
سنة النشر: 2010
مصطلحات موضوعية: Levodopa, Dyskinesia, Drug-Induced, Computer science, Feature extraction, Acceleration, Monitoring, Ambulatory, Biosensing Techniques, Antiparkinson Agents, Automation, medicine, Humans, Computer vision, Monitoring, Ambulatory/*instrumentation/methods, Levodopa-induced dyskinesia, Models, Statistical, Levodopa/*pharmacology, business.industry, Antiparkinson Agents/pharmacology, Parkinson Disease/diagnosis, Reproducibility of Results, Parkinson Disease, Signal Processing, Computer-Assisted, Equipment Design, Dyskinesia, Drug-Induced/*physiopathology, Dyskinesia, Programming Languages, Artificial intelligence, medicine.symptom, business, Algorithms, medicine.drug
الوصف: An automated methodology for Levodopa-induced dyskinesia (LID) assessment is presented in this paper. The methodology is based on the analysis of the signals recorded from accelerometers and gyroscopes, which are placed on certain positions on the subject's body. The obtained signals are analyzed and several features are extracted. Based on these features a classification technique is used for LID detection and classification of its severity. The method has been evaluated using a group of 10 subjects. Results are presented related to each individual sensor as well as for various sensor combinations. The obtained results indicate high classification ability (93.73% classification accuracy). Conf Proc IEEE Eng Med Biol Soc
تدمد: 2375-7477
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ee0524f59b7ff39575747f59c310634Test
https://pubmed.ncbi.nlm.nih.gov/21095695Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....6ee0524f59b7ff39575747f59c310634
قاعدة البيانات: OpenAIRE