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Recent advances in wearable sensing technologies have favored the search for reliable and objective methods of estimating motor symptoms and complications of Parkinson's disease (PD). In this paper, we present a complete system of motor assessment composed of Shimmer3 inertial measurement modules aimed to classify a series of daily life activities performed by PD patients and detect the occurrence...
In this paper, we present an activity classification-based algorithm for the automatic detection of Levodopa Induced Dyskinesia in Parkinson's Disease (PD) patients. Two PD patients experiencing motor fluctuations related to chronic Levodopa therapy performed a protocol of simple daily life activities on at least two different occasions. A Random Forest classifier was able to classify the performed...
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