Finger Tapping Clinimetric Score Prediction in Parkinson's Disease Using Low-Cost Accelerometers
المؤلفون المشاركون
Sharei, Hoda
Ambroise, Jérome
Crémers, Julien
Macq, Benoît
Delvaux, Valérie
Garraux, Gaëtan
Stamatakis, Julien
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-04-16
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
The motor clinical hallmarks of Parkinson's disease (PD) are usually quantified by physicians using validated clinimetric scales such as the Unified Parkinson's Disease Rating Scale (MDS-UPDRS).
However, clinical ratings are prone to subjectivity and inter-rater variability.
The PD medical community is therefore looking for a simple, inexpensive, and objective rating method.
As a first step towards this goal, a triaxial accelerometer-based system was used in a sample of 36 PD patients and 10 age-matched controls as they performed the MDS-UPDRS finger tapping (FT) task.
First, raw signals were epoched to isolate the successive single FT movements.
Next, eighteen FT task movement features were extracted, depicting MDS-UPDRS features and accelerometer specific features.
An ordinal logistic regression model and a greedy backward algorithm were used to identify the most relevant features in the prediction of MDS-UPDRS FT scores, given by 3 specialists in movement disorders (SMDs).
The Goodman-Kruskal Gamma index obtained (0.961), depicting the predictive performance of the model, is similar to those obtained between the individual scores given by the SMD (0.870 to 0.970).
The automatic prediction of MDS-UPDRS scores using the proposed system may be valuable in clinical trials designed to evaluate and modify motor disability in PD patients.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Stamatakis, Julien& Ambroise, Jérome& Crémers, Julien& Sharei, Hoda& Delvaux, Valérie& Macq, Benoît…[et al.]. 2013. Finger Tapping Clinimetric Score Prediction in Parkinson's Disease Using Low-Cost Accelerometers. Computational Intelligence and Neuroscience،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-493009
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Stamatakis, Julien…[et al.]. Finger Tapping Clinimetric Score Prediction in Parkinson's Disease Using Low-Cost Accelerometers. Computational Intelligence and Neuroscience No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-493009
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Stamatakis, Julien& Ambroise, Jérome& Crémers, Julien& Sharei, Hoda& Delvaux, Valérie& Macq, Benoît…[et al.]. Finger Tapping Clinimetric Score Prediction in Parkinson's Disease Using Low-Cost Accelerometers. Computational Intelligence and Neuroscience. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-493009
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-493009
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر