Prediction of motor Unified Parkinson's Disease Rating Scale scores in patients with Parkinson’s disease using surface electromyography

ObjectiveParkinson's disease (PD) is a chronic neurodegenerative disorder with increasing prevalence in the elderly. Especially patients with advanced PD often require complex medication regimens due to fluctuations, that is abrupt transitions from ON to OFF or vice versa. Current gold standard to quantify PD-patients’ motor symptoms is the assessment of the Unified Parkinson's Disease Rating Scale (UPDRS), which, however, is cumbersome and may depend upon investigators. This work aimed at developing a mobile, objective and unobtrusive measurement of motor symptoms in PD.MethodsData from 45 PD-patients was recorded using surface electromyography (sEMG) electrodes attached to a wristband. The motor paradigm consisted of a tapping task performed with and without dopaminergic medication. Our aim was to predict UPDRS scores from the sEMG characteristics with distinct regression models and machine learning techniques.ResultsA random forest regression model outnumbered other regression models resulting in a correlation of 0.739 between true and predicted UPDRS values.ConclusionsPD-patients’ motor affection can be extrapolated from sEMG data during a simple tapping task. In the future, such records could help determine the need for medication changes in telemedicine applications.SignificanceOur findings support the utility of wearables to detect Parkinson's symptoms and could help in developing tailored therapies in the future.     

Early balance impairment in Parkinson’s Disease: Evidence from Robot-assisted axial rotations

ObjectiveEarly postural instability (PI) is a red flag for the diagnosis of Parkinson’s disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning.MethodsFifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors.ResultsPatients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged.ConclusionsPatients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD.SignificancePD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.     

Impairment of brain functions in Parkinson’s disease reflected by alterations in neural connectivity in EEG studies: A viewpoint

Clinical symptoms of Parkinson’s disease (PD) are accompanied by pathological phenomena detected locally in the basal ganglia (BG) as changes in local field potentials (LFPs) and also in cortical regions by electroencephalography (EEG). The literature published mainly between 2000 and 2017 was reviewed with an emphasis on approaches emerging after 2000, in particular on oscillatory dynamics, connectivity studies, and deep brain stimulation. Eighty-five articles were reviewed. The main observations were a general slowing of background activity, excessive synchronization of beta activity, and disturbed movement-related gamma oscillations in the BG and in the cortico-subcortical and cortico-cortical motor loops, suppressible by dopaminergic medication as well as by high-frequency deep brain stimulation (DBS). Non-motor symptoms are related mainly to changes in the alpha frequency range. EEG parameters can be useful in defining the risk of dementia in PD. Further progress was reported recently using advanced analytical technologies and high-performance computing (graph theory). Detailed knowledge of LFPs in PD enabled progress particularly in DBS therapy, which requires optimizing the clinical effect and minimizing adverse side effects. The neurocognitive networks and their dysfunction in PD and DBS therapy are promising targets for future research.     

Subthalamic dynamic neural states correlate with motor symptoms in Parkinson’s Disease

ObjectiveThis study aims to discriminate the dynamic synchronization states from the subthalamic local field potentials and investigate their correlations with the motor symptoms in Parkinson’s Disease (PD).MethodsThe resting-state local field potentials of 10 patients with PD were recorded from the subthalamic nucleus. The dynamic neural states of multiple oscillations were discriminated and analyzed. The Spearman correlation was used to investigate the correlations between occurrence rate or duration of dynamic neural states and the severity of motor symptoms.ResultsThe proportion of long low-beta and theta synchronized state was significantly correlated with the general motor symptom and tremor, respectively. The duration of combined low/high-beta state was significantly correlated with rigidity, and the duration of combined alpha/high-beta state was significantly correlated with bradykinesia.ConclusionsThis study provides evidence that motor symptoms are associated with the neural states coded with multiple oscillations in PD.SignificanceThis study may advance the understanding of the neurophysiological mechanisms of the motor symptoms and provide potential biomarkers for closed-loop deep brain stimulation in PD.