Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments
BIOMEDICAL ENGINEERING ONLINE
Machado, A. R., Zaidan, H. C., Souza Paixao, A. P., Cavalheiro, G. L., Monteiro Oliveira, F. H., Ferreira Barbosa Junior, J. A., Naves, K., Pereira, A. A., Pereira, J. M., Pouratian, N., Zhuo, X., O'Keeffe, A., Sharim, J., Bordelon, Y., Yang, L., Vieira, M. F., Andrade, A. O.
2016; 15
Abstract
Over the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson's disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy.In this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon's map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification.The results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively.This research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.
View details for DOI 10.1186/s12938-016-0290-y
View details for Web of Science ID 000391062100001
View details for PubMedID 28038673
View details for PubMedCentralID PMC5203727
Abstract
Mitochondrial dysfunction has been implicated in the pathogenesis of Parkinson's disease (PD), but the cause of this dysfunction is unclear.Platelet mitochondrial complex I and I/III (nicotinamide adenine dinucleotide cytochrome c reductase, NCCR) activities were measured in early PD patients and matched controls enrolled in a population-based case-control study. Ambient agricultural pesticide exposures were assessed with a geographic information system and California Pesticide Use Registry.In contrast to some previous reports, we found no differences in complex I and I/III activities in subjects with PD and controls. We did find that NCCR activity correlated with subjects' exposure to pesticides known to inhibit mitochondrial activity regardless of their diagnosis.Electron transport chain (ETC) activity is not altered in PD in this well-characterized cohort when compared with community-matched controls but appears to be affected by environmental toxins, such as mitochondria-inhibiting pesticides.
View details for DOI 10.1002/mds.26164
View details for Web of Science ID 000354731500021
View details for PubMedID 25757798
