title: Patient State Recognition System for Healthcare Using Speech and Facial Expressions.
abstract: Smart, interactive healthcare is necessary in the modern age. Several issues, such as accurate diagnosis, low-cost modeling, low-complexity design, seamless transmission, and sufficient storage, should be addressed while developing a complete healthcare framework. In this paper, we propose a patient state recognition system for the healthcare framework. We design the system in such a way that it provides good recognition accuracy, provides low-cost modeling, and is scalable. The system takes two main types of input, video and audio, which are captured in a multi-sensory environment. Speech and video input are processed separately during feature extraction and modeling; these two input modalities are merged at score level, where the scores are obtained from the models of different patients' states. For the experiments, 100 people were recruited to mimic a patient's states of normal, pain, and tensed. The experimental results show that the proposed system can achieve an average 98.2 % recognition accuracy.
authors.affiliation: Department of Software Engineering, College of Computer and Information Sciences (CCIS), King Saud University, Riyadh, Saudi Arabia. mshossain@ksu.edu.sa.
authors.forename: M Shamim
authors.initials: MS
authors.lastname: Hossain
mesh_terms: D005149:Facial Expression; D006801:Humans; D007256:Information Systems / Q000458:organization & administration; D020380:Needs Assessment; D010361:Patients; D010363:Pattern Recognition, Automated / Q000379:methods*; D013060:Speech; D013997:Time Factors; D014741:Video Recording / Q000379:methods*
keywords: Local ternary pattern; Multi-directional regression; Patient state recognition; Smart healthcare