1. Survey and high level design of activity monitoring for icu patients
Authors : Nikitaa Magi, B. G. Prasad, Priyanka Jigalur
Pages : 17-22
DOI : http://dx.doi.org/10.21172/1.142.03
Keywords : Deep learning, Neural Networks, Patient Monitoring, Image processing, Activity analysis Abstract :ICU patients are immobile and their medical conditions are very sensitive, any minute response shown by them have to be immediately reported to the hospital authority so that the patients are treated as quickly as possible. ICU patients require constant monitoring in order to detect and identify any movement exhibited by them. One of the conventional methods of monitoring ICU patients is to have assigned observer who observes the patients all the time. This conventional method for monitoring ICU patients has several limitations such as observer must be available by the side of the patients always or observer might overlook some minute actions performed by patient. This paper presents a survey on smart and automatic vision based patient monitoring system using deep learning methods and image processing. Deep leaning provides several methods for activity monitoring, detection and identification such as 2D convolution networks, 3D convolution networks, etc. This paper discusses classification, challenges, application and methods for activity detection and also presents high level system design for activity monitoring system.
Citing this Journal Article :Nikitaa Magi, B. G. Prasad, Priyanka Jigalur, "Survey and high level design of activity monitoring for icu patients ", Volume 14 Issue 2 - August 2019, 17-22
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