| Abstrakt: |
Monitoring the patient remotely, has always been a challenging issue in the health care domain. Especially, fall detection during monitoring, is a vital aspect. Progress in technology, has facilitated vision-based systems, and thereby detecting a fall and providing a timely help to the concerned person is possible. This paper mainly focusses on the implementation of a computer vision-based system, which also incorporates Machine Learning algorithms to learn the actions of a person, thereby detecting a fall, and notifying the primary caregiver during the situation, right away, so as to provide the help at the right time. The implemented system, is able to detect the actions of a user by classifying the broad range of activities into fall and non-fall actions. [ABSTRACT FROM AUTHOR] |
