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Soroosh Shahtalebi

PhD student in Engineering
Concordia University

Award-winning publication:  pHtnet: characterization and Deep Mining of involuntary pathological Hand tremor using Recurrent neural network Models

Published in: Nature
 

Abstract

As the world’s population ages, the number of people suffering from age-related neurological movement disorders such as Parkinson’s disease has been on the rise. Pathological hand tremor (PHT) is a common symptom that has a considerable impact on patients’ quality of life, and accurate estimations of PHTs are therefore essential to develop rehabilitation and support technologies. Led by Soroosh Shahtalebi, the PHTNet project tackles the problem with a real-time recurrent model for PHTs that integrates computational modeling and machine learning techniques to maximize the resolution of estimation and improve early diagnosis.