Machine Learning
WordNet: a lexical database for English
Communications of the ACM
BALANCE: towards a usable pervasive wellness application with accurate activity inference
Proceedings of the 10th workshop on Mobile Computing Systems and Applications
Data clustering: 50 years beyond K-means
Pattern Recognition Letters
Real world activity summary for senior home monitoring
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Mobile healthcare infrastructure for home and small clinic
Proceedings of the 2nd ACM international workshop on Pervasive Wireless Healthcare
A reliable and accurate indoor localization method using phone inertial sensors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Human gait recognition using depth camera: a covariance based approach
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
A robust heart rate detection using smart-phone video
Proceedings of the 3rd ACM MobiHoc workshop on Pervasive wireless healthcare
Unobtrusive indoor surveillance of patients at home using multiple Kinect sensors
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Hi-index | 0.00 |
Once the person's identity is established, the most important aspects of ubiquitous healthcare monitoring of elderly and chronic patients are location, activity, physiological and psychological parameters. Since smartphones have become the most pervasive computing platform today, it is only a logical extension to use the same in healthcare domain for bringing ubiquity. Besides smartphone, skeleton based activity detection and localization using depth sensor like Kinect make ubiquitous monitoring effective without compromising privacy to a large extent. Finally sensing mental condition is made possible by analysis of the subject's social network feed. This paper presents an end-to-end healthcare monitoring system code named UbiHeld (Ubiquitous Healthcare for Elderly) using the techniques mentioned above and an IoT (Internet of Things) based back-end platform.