User Satisfaction Detection System for Smart Healthcare using Multimedia
Rajesh S M1, Suresh kumar K R2
1Rajesh S M, M S Ramaiah Institute of Technology (MSRIT).
2Suresh Kumar K R, M S Ramaiah Institute of Technology (MSRIT).
Manuscript received on 04 August 2019 | Revised Manuscript received on 09 August 2019 | Manuscript published on 30 August 2019 | PP: 3763-3766 | Volume-8 Issue-10, August 2019 | Retrieval Number: J99690881019/2019©BEIESP | DOI: 10.35940/ijitee.J9969.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Emotion plays a critical job ineffectively conveying one’s convictions and intentions. As an outcome, identification of emotion has turned into focus point of few studies recently. Patient observing models are getting to be significant in patient concern and can endow with helpful feedback related to health issues for caregivers and clinicians. In this work, patient fulfilment recognition framework is proposed that uses image frames extracted from the recorded visual-audio modality dataset. The images are treated with techniques such as Local Binary Pattern (LBP) which is a ocular descriptor. The proposed framework incorporates feature extraction from the images and then the Support Vector Machine (SVM) is applied for classification. The three distinct types of emotions are whether the patient is happy, sad or neutral and the same are detected based on the results. The result of such an analysis can be made use of by a group of analysts which include doctors, healthcare experts and system experts to improve smart healthcare system in steps. The reliability of information provided by such a system makes such upgradations more meaningful.
Keywords: Patient Monitoring, Emotion Detection, Feature Extraction, LBP, SVM
Scope of the Article: Healthcare Informatics