Open AccessCloud Based Virtual Analysis of Patients and Automatic Assistance Using ML
Author(s) -
S. Tephillah,
J Bavithra.,
S Isaiyamuthu.
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-969
Subject(s) - cloud computing , computer science , artificial intelligence , physical medicine and rehabilitation , balance (ability) , virtual machine , machine learning , artificial neural network , rehabilitation , human–computer interaction , simulation , medicine , physical therapy , operating system
Human Activity Recognition is one of the active research areas in computer vision for various contexts like security surveillance, health care and human computer interaction. Parkinson's disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance and coordination. Parkinson's symptoms usually begin gradually and get worse over time. As the disease progresses, people may have difficulty in walking and talking. The objective of the project is to train a machine-learning based model using Artificial Neural Network (ANN) and K-means algorithm. This model helps the patient with Parkinson’s disease to understand their actions and identify the error in their movements. The kinect camera captures the actions of the patient and transforms those into Gray scale image and depth view. The advantage of this system is to prevent the patient from going clinic thereby saving the time of physically challenged people. The proposed virtual Physiotherapist (PT) system hasthe potential of enabling on demand virtual care and significantly reducing cost for both patients and care providers.