There is a need for objective measures of dyskinesia and bradykinesia of Parkinson's disease (PD) that are continuous throughout the day and related to levodopa dosing. The output of an algorithm that calculates dyskinesia and bradykinesia scores every two minutes over 10 days (PKG: Global Kinetics Corporation) was compared with conventional rating scales for PD in PD subjects. The algorithm recognises bradykinesia as movements made with lower acceleration and amplitude and with longer intervals between movement. Similarly the algorithm recognises dyskinesia as having movements of normal amplitude and acceleration but with shorter periods without movement. The distribution of the bradykinesia and dyskinesia scores from PD subjects differed from that of normal subjects. The algorithm predicted the clinical dyskinesia rating scale AIMS with a 95% margin of error of 3.2 units compared with the inter-rater 95% limits of agreement from 3 neurologists of −3.4 to +4.3 units. Similarly the algorithm predicted the UPDRS III score with a margin of error similar to the inter-rater limits of agreement. Improvement in scores in response to changes in medication could be assessed statistically in individual patients. This algorithm provides objective, continuous and automated assessment of the clinical features of bradykinesia and dyskinesia in PD.
The angular features and count of direction inversion which can be obtained in real-time while sketching the Archimedean guided spiral on a digital tablet can be used for differentiating between Parkinson's and healthy cohort.
Commonly used methods to assess the severity of essential tremor (ET) are based on clinical observation and lack objectivity. This study proposes the use of wearable accelerometer sensors for the quantitative assessment of ET. Acceleration data was recorded by inertial measurement unit (IMU) sensors during sketching of Archimedes spirals in 17 ET participants and 18 healthy controls. IMUs were placed at three points (dorsum of hand, posterior forearm, posterior upper arm) of each participant’s dominant arm. Movement disorder neurologists who were blinded to clinical information scored ET patients on the Fahn–Tolosa–Marin rating scale (FTM) and conducted phenotyping according to the recent Consensus Statement on the Classification of Tremors. The ratio of power spectral density of acceleration data in 4–12 Hz to 0.5–4 Hz bands and the total duration of the action were inputs to a support vector machine that was trained to classify the ET subtype. Regression analysis was performed to determine the relationship of acceleration and temporal data with the FTM scores. The results show that the sensor located on the forearm had the best classification and regression results, with accuracy of 85.71% for binary classification of ET versus control. There was a moderate to good correlation (r2 = 0.561) between FTM and a combination of power spectral density ratio and task time. However, the system could not accurately differentiate ET phenotypes according to the Consensus classification scheme. Potential applications of machine-based assessment of ET using wearable sensors include clinical trials and remote monitoring of patients.
Although a placebo effect cannot be ruled out, local injection of botulinum toxin may be an effective treatment for intractable asthma associated with abnormal vocal cord movement. Further mechanistic studies and a double-blind randomised controlled trial of botulinum toxin treatment are merited.
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