The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities

Adam Świtoński; Magdalena Stawarz; Magdalena Boczarska-Jedynak; Aleksander Sieroń; Andrzej Polański; Konrad Wojciechowski

The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities

Adam Świtoński
, Magdalena Stawarz
, Magdalena Boczarska-Jedynak
, Aleksander Sieroń
, Andrzej Polański
, Konrad Wojciechowski

Katedra Grafiki, Wizji Komputerowej i Systemów Cyfrowych (RAU/RAU6)

Polish-Japanese Academy of Information Technology
Medical University of Silesia in Katowice

Wyniki badań: Wkład do czasopisma › Artykuł › recenzja

3 Cytowania z bazy Scopus

Abstrakt

The analysis of effectiveness of deep brain stimulation and pharmacological treatment in Parkinson disease is presented. It is based on an examination of discriminative properties of distinctive motion features. The feature extraction and selection of kinematical motion data is carried out. The attribute ranking with entropy based attribute evaluation and greedy hill climbing search with assessment of an average inner class dissimilarity are applied. The obtained results show that deep brain stimulation has greater impact on investigated motion activities.

Język oryginału	angielski
Strony (od–do)	103-106
Liczba stron	4
Czasopismo	Przeglad Elektrotechniczny
Tom	88
Numer wydania	12 B
Status publikacji	Opublikowano - 2012

Obszary tematyczne ASJC Scopus

Inżynieria elektryczna i elektroniczna

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

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title = "The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities",

abstract = "The analysis of effectiveness of deep brain stimulation and pharmacological treatment in Parkinson disease is presented. It is based on an examination of discriminative properties of distinctive motion features. The feature extraction and selection of kinematical motion data is carried out. The attribute ranking with entropy based attribute evaluation and greedy hill climbing search with assessment of an average inner class dissimilarity are applied. The obtained results show that deep brain stimulation has greater impact on investigated motion activities.",

keywords = "Feature extraction, Feature selection, Motion capture, Parkinson diseases, Supervised machine learning",

author = "Adam {\'S}wito{\'n}ski and Magdalena Stawarz and Magdalena Boczarska-Jedynak and Aleksander Siero{\'n} and Andrzej Pola{\'n}ski and Konrad Wojciechowski",

year = "2012",

language = "English",

volume = "88",

pages = "103--106",

journal = "Przeglad Elektrotechniczny",

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TY - JOUR

T1 - The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities

AU - Świtoński, Adam

AU - Stawarz, Magdalena

AU - Boczarska-Jedynak, Magdalena

AU - Sieroń, Aleksander

AU - Polański, Andrzej

AU - Wojciechowski, Konrad

PY - 2012

Y1 - 2012

N2 - The analysis of effectiveness of deep brain stimulation and pharmacological treatment in Parkinson disease is presented. It is based on an examination of discriminative properties of distinctive motion features. The feature extraction and selection of kinematical motion data is carried out. The attribute ranking with entropy based attribute evaluation and greedy hill climbing search with assessment of an average inner class dissimilarity are applied. The obtained results show that deep brain stimulation has greater impact on investigated motion activities.

AB - The analysis of effectiveness of deep brain stimulation and pharmacological treatment in Parkinson disease is presented. It is based on an examination of discriminative properties of distinctive motion features. The feature extraction and selection of kinematical motion data is carried out. The attribute ranking with entropy based attribute evaluation and greedy hill climbing search with assessment of an average inner class dissimilarity are applied. The obtained results show that deep brain stimulation has greater impact on investigated motion activities.

KW - Feature extraction

KW - Feature selection

KW - Motion capture

KW - Parkinson diseases

KW - Supervised machine learning

UR - https://www.scopus.com/pages/publications/84870709633

M3 - Article

AN - SCOPUS:84870709633

SN - 0033-2097

VL - 88

SP - 103

EP - 106

JO - Przeglad Elektrotechniczny

JF - Przeglad Elektrotechniczny

IS - 12 B

ER -

The effectiveness of applied treatment in Parkinson disease based on feature selection of motion activities

Abstrakt

Obszary tematyczne ASJC Scopus

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Fingerprint

Cytowanie