Feature visualization and classification for the discrimination between individuals with Parkinson’s disease under levodopa and DBS treatments

Abstract

BackgroundOver 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.MethodsIn 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.ResultsThe 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.ConclusionsThis 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.

Dopaminergic agents: back to the basics – A small review

“…The dopamine which is obtained from levodopa is stored in the dopamine receptors and then is utilized when required [7]. With the combination of levodopa and Carbidopa, more concentration is available in the brain.…”

Parkinson Hastalığı ve Atipik Parkinson Sendromlarının Ayırıcı Tanısı

“…Postural instability usually does not occur until late into the disease of PD, which can help with a differential diagnosis between APS and PD 22 . Bradykinesia is known as slow movements and can be further detrimental to PD and APS patients 3 .…”

“…The primary technique in diagnosing PD is through a thorough neurological and physical examination and further referral to a movement specialist 3 . When two of the four Parkinsonism classical symptoms are present, there can be accurate diagnoses of PD 1 .…”

“…Destruction of neurons in the substantia nigra cultivates an insidious incurable neurodegenerative movement disorder called Parkinson's Disease (PD) [1][2][3][4] . PD causes a number of clinical manifestations both motor and nonmotor typically after 60-80% of dopamine loss occurs in the terminals of the striatum 5 .…”

“…Additional treatment for PD includes deep brain stimulation (DBS), pallidotomy and thalamotomy. The most proficient and commonly prescribed medication today for PD is Levodopa 3 . Levodopa is used to control motor symptoms but increased and prolonged use causes abnormal involuntary movements known as dyskinesias 1,2,18,19,20 .…”