A Machine Learning Approach to VTA Prediction in DBS
Objective: This study aims to evaluate a novel, machine learning approach to volume of activation (VTA) prediction for real-time use in the clinical setting and…Validity of quantitative parameters for analyzing gait motion in PD patients after STN-DBS
Objective: The validity of parameters for quantitative assessment of gait movement characteristics specific to Parkinson's disease (PD) patients was tested with data from STN-DBS On/Off.…Technology-based adaptation of a natural history study of Parkinson disease during the COVID-19 pandemic
Objective: To describe the transition of a novel study in Parkinson disease (PD) evaluating four technologies—the mPower 2.0 smartphone application, MC10 wearable BioStamp nPoint® sensors,…Wearable Devices in Movement Disorder Trials to Provide Objective Measures
Objective: To understand the validity of wearable devices in capturing objective motor and nonmotor symptoms of Parkinson’s Disease (PD) in addition to what has been…Closing the gap: How to record valuable data for movement disorders using FHIR
Objective: To make data generated in routine clinical practice in the treatment of patients with movement disorders and deep brain stimulation available for clinical decision-making…Pilot study to assess gait-related motor symptoms in Parkinson’s disease by using a unique passive monitoring wearable technology
Objective: The objective of this pilot study is to present data demonstrating the ability of a wearable medical device combining plantar pressure sensors, accelerometers, and…Use Of Digitizing Tablet For the Tremor Evaluation
Objective: This review was done to know the uses of digitalizing tablets for the tremor evaluation. Background: Tremor is the most common movement disorder seen…Parkinson’s Disease Functional Impacts Digital Instrument (PD-FIDI): Studies Preceding Clinical Validation
Objective: Summarize the findings from 3 developmental studies of the Parkinson’s Disease Functional Impacts Digital Instrument (PD-FIDI) – a novel endpoint for assessing PD symptoms.…Accuracy in Detection of Performance of Activities of Daily Living in Subjects with Parkinson’s Disease by Using Inertial Sensors and Decision Tree Classifiers
Objective: To obtain an accurate method for the detection of activities of daily living (ADL) in subjects with Parkinson’s disease (PD) by using inertial sensors…Using Machine Learning to Predict the Best Outcomes with Electrical Muscle Stimulation for Tremors in Parkinson’s Disease
Objective: This study explores the effect of electrical muscle stimulation (EMS) on resting tremor and aims to identify the best machine learning model to predict…
Abstracts from the International Congress of Parkinson’s and Movement Disorders.