A Method for Automatic and Objective Scoring of Bradykinesia Using Orientation Sensors and Classification Algorithms.

Correct assessment of bradykinesia is a key element in the diagnosis and monitoring of Parkinson's disease. Its evaluation is based on a careful assessment of symptoms and it is quantified using rating scales, where the Movement Disorders Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is the gold standard. Regardless of their importance, the bradykinesia-related items show low agreement between different evaluators. In this study, we design an applicable tool that provides an objective quantification of bradykinesia and that evaluates all characteristics described in the MDS-UPDRS. Twenty-five patients with Parkinson's disease performed three of the five bradykinesia-related items of the MDS-UPDRS. Their movements were assessed by four evaluators and were recorded with a nine degrees-of-freedom sensor. Sensor fusion was employed to obtain a 3-D representation of movements. Based on the resulting signals, a set of features related to the characteristics described in the MDS-UPDRS was defined. Feature selection methods were employed to determine the most important features to quantify bradykinesia. The features selected were used to train support vector machine classifiers to obtain an automatic score of the movements of each patient. The best results were obtained when seven features were included in the classifiers. The classification errors for finger tapping, diadochokinesis and toe tapping were 15-16.5%, 9.3-9.8%, and 18.2-20.2% smaller than the average interrater scoring error, respectively. The introduction of objective scoring in the assessment of bradykinesia might eliminate inconsistencies within evaluators and interrater assessment disagreements and might improve the monitoring of movement disorders.

Parkinson bradykinesia correlates with EEG background frequency and perceptual forward projection.

BACKGROUND: To deal with processing-time in the nervous system, visuomotor control requires anticipation. An index for such anticipation is provided by the 'flash-lag illusion' in which moving objects are perceived ahead of static objects while actually being in the same place. We investigated the neurophysiological relation between visuomotor anticipation and motor velocity in Parkinson's disease (PD) and controls. METHODS: Motor velocity was assessed by the number of keystrokes in 30s ('kinesia score') and visuomotor anticipation in a behavioural flash-lag paradigm while electroencephalography data was obtained. PD patients (n = 24) were divided in a 'PDslow' and a 'PDfast' group based on kinesia score. RESULTS: The PDslow group had a lower kinesia score than controls (resp. 40.3 ± 1.7 and 64.9 ± 4.6, p < 0.001). The flash-lag illusion was weaker in the PDslow group than in controls (resp. fractions 0.32 ± 0.04 and 0.50 ± 0.09 of the responses indicating perceived lagging, p = 0.03). Furthermore, the magnitude of the flash-lag illusion correlated with the kinesia score (cc = 0.45, p = 0.02). Finally, electroencephalography background frequency was lower in the PDslow group than in controls (resp 8.24 ± 0.24 and 9.1 ± 0.32 Hz, p = 0.01) and background frequency correlated with the kinesia score (cc = 0.58, p = 0.001). CONCLUSIONS: The decreased flash-lag illusion and lower electroencephalography background frequency in more bradykinetic PD patients provides support for disturbed visuomotor anticipations, putatively caused by reduced, sub-cortically mediated, network efficiency. This suggests a link between anticipation in early-stage visual motion processing and motor preparation.