2014 Webinar Series

Technology in Clinical Trials for Parkinson’s Disease

technology for parkinson's diseaseGreat Lakes NeuroTechnologies is proud to present the webinar series, “Technology in Clinical Trials for Parkinson’s Disease”. This series is targeted to researchers, clinicians, and product developers who are designing and implementing clinical trials for Parkinson’s disease. Whether you’re designing trials for pharma or deep brain stimulation, our team of scientific investigators will be delivering a wide variety of topics to stimulate creativity and collaboration. Each monthly, 20-minute session will share methods, sample data, and analysis techniques that will drive insight and innovation for designing Parkinson’s trials and integrating automated technology.

January 30th Thursday 12:00 to 12:30 EST Towards Ambulatory Motor Monitoring: Measuring Dyskinesia During Activities of Daily Living View Webcast Chris Pulliam, PhD View Slides View Abstract
March 20th Thursday 12:00 to 12:30 EST Development and clinical evaluation of a clinician worn device for the assessment of abnormal muscle tone Elizabeth Brokaw, PhD  View Slides  View Abstract
May 8th Thursday
12:00 to 12:30 EST
Quantitative Parkinson’s Gait Assessment: A high resolution measure of change in impairment Elizabeth Brokaw, PhD
June 5th Thursday
12:00 to 12:30 EST
Automated Guidance of Post-Operative DBS Programming Chris Pulliam, PhD



Development and clinical evaluation of a clinician worn device for the assessment of abnormal muscle tone

March 20th Thursday 12:00 to 12:30 EST

Neurological conditions such as cerebral palsy, stroke, Parkinson’s disease, and spinal cord injury often result in abnormal muscle tone, which is a major impediment to functional use of the affected limbs. Treatments such as Botox injections and deep brain stimulation differ in effectiveness depending on the condition. As a result, the ability to quantitatively distinguish between different types of abnormal tone is important for determining the appropriate treatment.

MyoSense, a clinician worn device, is being developed to identify and quantify abnormal muscle tone. MyoSense is instrumented with force and velocity sensors to monitor changes in resistance to movement as the clinician moves the individual’s limb at different speeds. This will help clinicians quantitatively distinguish between speed based changes in muscle properties such as those that result from spasticity, and effects of other types of abnormal muscle tone such as rigidity and dystonia. This webinar will focus on MyoSense device design, results from evaluation of simulated types of abnormal tone, and preliminary clinical results.

Towards Ambulatory Motor Monitoring: Measuring Dyskinesia During Activities of Daily Living

Thursday, January 30 – 12:00 – 12:30 EST

Dyskinesia throughout the levodopa dose cycle has been previously measured in patients with Parkinson’s disease (PD) using a wrist-worn motion sensor during the stationary tasks of arms resting and extended. Quantifying dyskinesia during unconstrained activities poses a unique challenge since these involuntary movements are kinematically similar to voluntary movement. The objective of the current study was to determine the feasibility of using motion sensors to measure dyskinesia during activities of daily living. Fifteen PD subjects performed scripted activities of daily living while wearing motion sensors on bilateral hands, thighs, and ankles over the course of a levodopa dose cycle. Videos were scored by clinicians using the modified Abnormal Involuntary Movement Scale to rate dyskinesia severity in separate body regions, with the total score used as an overall measure. Kinematic features were extracted from the motion data and linear regression models were generated to output severity scores. Dyskinesia scores predicted by the model were highly correlated with clinician scores, demonstrating that a system with motion sensors may provide an accurate measure of overall dyskinesia that can be used to monitor patients as they complete typical activities, and thus provide insight on symptom fluctuation in the context of daily life.

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