Quantifying drug induced dyskinesia in Parkinson's disease patients using standardized videos
ABSTRACT This paper presents a video based method to quantify drug induced dyskinesias in Parkinson's disease (PD) patients. Dyskinetic movement in standard clinical videos of patients is analyzed by tracking landmark points on the video frames using non-rigid image registration. The novel application of Point Distribution Models (PDM) allows geometric variations and covariations of the landmark points to be captured from each video sequence. The PDM parameters represent quantifiable information that can be used to rate dyskinesia effectively, analogously to a neurologist's strategy of assessing the movement of multiple body parts simultaneously to effectively rate dyskinesia. A heuristic decision function is then developed using the PDM parameters to quantify the severity of the dyskinesia. The severity score using our decision function showed a high correlation to the dyskinesia rating of a neurologist on the corresponding patient videos.
- SourceAvailable from: Shyamal Patel[show abstract] [hide abstract]
ABSTRACT: The aim of this study is to identify movement characteristics associated with motor fluctuations in patients with Parkinson's disease by relying on wearable sensors. Improved methods of assessing longitudinal changes in Parkinson's disease would enable optimization of treatment and maximization of patient function. We used eight accelerometers on the upper and lower limbs to monitor patients while they performed a set of standardized motor tasks. A video of the subjects was used by an expert to assign clinical scores. We focused on a motor complication referred to as dyskinesia, which is observed in association with medication intake. The sensor data were processed to extract a feature set responsive to the motor fluctuations. To assess the ability of accelerometers to capture the motor fluctuation patterns, the feature space was visualized using PCA and Sammon's mapping. Clustering analysis revealed the existence of intermediate clusters that were observed when changes occurred in the severity of dyskinesia. We present quantitative evidence that these intermediate clusters are the result of the high sensitivity of the proposed technique to changes in the severity of dyskinesia observed during motor fluctuation cyclesWearable and Implantable Body Sensor Networks, 2006. BSN 2006. International Workshop on; 05/2006
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ABSTRACT: We used a rotation-sensitive movement monitor (RoMM) to quantify and characterize dyskinesia in Parkinson's disease (PD). Both upper limbs of 22 patients with dyskinetic PD were recorded and videotaped simultaneously. Three neurologists reviewed the video segments and rated severity of dyskinesia on a four-point scale; they also assessed any asymmetry of dyskinesia between the right and left side as well as the dyskinesia type (choreic, dystonic, or mixed). Mean and median clinical ratings for severity, asymmetry, and type of dyskinesia were compared with (1) the total power of the frequency power spectrum (FPS, degrees/second), (2) the percent difference of FPS values between the right and left side, and (3) the frequency (Hz) of the predominant peak, respectively. Intra- and interrater reliability was determined and a test-retest analysis was performed. FPS values showed a statistically significant correlation with the clinical ratings for dyskinesia severity. FPS difference between both sides was more sensitive than raters in detecting dyskinesia asymmetry. A predominant frequency peak of dyskinesia was obtained in all cases and ranged from 0.25-3.25 Hz. There was a significant trend for high-frequency dyskinesia to correlate with choreic type and for low-frequency dyskinesia to correlate with dystonic type. Test-retest analysis indicated a high reliability. We conclude that the RoMM is a valid, reliable, and sensitive method to quantify and characterize dyskinesia. Examples are provided suggesting that this instrument may prove useful for long-term assessment of dyskinetic patients and as a standardized tool for assessing dyskinesia in pharmaceutical or surgical trials for PD.Movement Disorders 10/1999; 14(5):754-63. · 4.56 Impact Factor
- Computer Vision and Image Understanding. 01/1995; 61:38-59.