Assessment of response to medication in individuals with Parkinson's disease

被引:28
作者
Hssayeni, Murtadha D. [1 ]
Burack, Michelle A. [2 ]
Jimenez-Shahed, Joohi [3 ]
Ghoraani, Behnaz [1 ]
机构
[1] Florida Atlantic Univ, Dept Comp & Elect Engn & Comp Sci, Boca Raton, FL 33431 USA
[2] Univ Rochester, Med Ctr, Dept Neurol, Rochester, NY 14642 USA
[3] Baylor Coll Med, Dept Neurol, Houston, TX 77030 USA
基金
美国国家卫生研究院;
关键词
Parkinson's disease; Wearable data analysis; Feature extraction and classification; Support vector machine; LEVODOPA-INDUCED DYSKINESIA; MOTOR COMPLICATIONS; FLUCTUATIONS; ACCURACY;
D O I
10.1016/j.medengphy.2019.03.002
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Background and Objective: Motor fluctuations between akinetic (medication OFF) and mobile phases (medication ON) states are one of the most prevalent complications of patients with Parkinson's disease (PD). There is a need for a technology-based system to provide reliable information about the duration in different medication phases that can be used by the treating physician to successfully adjust therapy. Methods: Two KinetiSense motion sensors were mounted on the most affected wrist and ankle of 19 PD subjects (age: 42-77, 14 males) and collected movement signals as the participants performed seven daily living activities in their medication OFF and ON phases. A feature selection and a classification algorithm based on support vector machine with fuzzy labeling was developed to detect medication ON/OFF states using gyroscope signals. The algorithm was trained using approximately 15% of the data from four activities and tested on the remaining data. Results: The algorithm was able to detect medication ON and OFF states with 90.5% accuracy, 94.2% sensitivity, and 85.4% specificity. It performed equally well for all the activities with an average accuracy of 91.3% for the activities that were used in the training phase and 88.4% for the new activities. Conclusions: The developed sensor-based algorithm could provide objective and accurate assessment of medication states that can lead to successful adjustment of the therapy resulting in considerably improved care delivery and quality of life of PD patients. (C) 2019 IPEM. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:33 / 43
页数:11
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