Open AccessMachine Learning Techniques for Automated Tremor Detection in the Presence of External Stressors
Author(s) -
K. Vanitha,
Viswanath Talasila
Publication year - 2022
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2022.16.69
Subject(s) - artificial intelligence , accelerometer , computer science , recall , wearable computer , inertial measurement unit , classifier (uml) , stressor , computer vision , pattern recognition (psychology) , psychology , embedded system , clinical psychology , cognitive psychology , operating system
In this study tremor data of 25 subjects (Senile tremor = 5, Alcohol induced tremor = 9, Healthy individuals = 11) were collected using a wearable device consisting of five Inertial Measuring Units (IMUs) and an embedded optical sensor. The subjects were made to draw the Archimedes spiral under the influence of external stressors. Features were extracted from measured acceleration data and also from an optical sensor. Using the selected features few supervised machined learning algorithms were explored for automatic classification of tremor. Performance matrix used to evaluate the classifier was accuracy, recall, and precision. It is observed that the algorithms are able to accurately classify healthy, senile tremor and alcohol induced tremor.