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Sensors 2015, 15(10), 26756-26768; doi:10.3390/s151026756

A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy

1
Interdisciplinary Program of Bioengineering, Seoul National University, Seoul 03080, Korea
2
Department of Otorhinolaryngology, Head and Neck Surgery, Seoul National University, Boramae Medical Center, Seoul 07061, Korea
3
Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul 03080, Korea
*
Authors to whom correspondence should be addressed.
Academic Editor: Ki H. Chon
Received: 31 July 2015 / Revised: 12 October 2015 / Accepted: 19 October 2015 / Published: 21 October 2015
(This article belongs to the Special Issue Smartphone-Based Sensors for Non-Invasive Physiological Monitoring)
View Full-Text   |   Download PDF [1914 KB, uploaded 21 October 2015]   |  

Abstract

Facial nerve palsy induces a weakness or loss of facial expression through damage of the facial nerve. A quantitative and reliable assessment system for facial nerve palsy is required for both patients and clinicians. In this study, we propose a rapid and portable smartphone-based automatic diagnosis system that discriminates facial nerve palsy from normal subjects. Facial landmarks are localized and tracked by an incremental parallel cascade of the linear regression method. An asymmetry index is computed using the displacement ratio between the left and right side of the forehead and mouth regions during three motions: resting, raising eye-brow and smiling. To classify facial nerve palsy, we used Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), and Leave-one-out Cross Validation (LOOCV) with 36 subjects. The classification accuracy rate was 88.9%. View Full-Text
Keywords: facial nerve palsy; smartphone; automatic diagnosis; asymmetry; assessment system facial nerve palsy; smartphone; automatic diagnosis; asymmetry; assessment system
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kim, H.S.; Kim, S.Y.; Kim, Y.H.; Park, K.S. A Smartphone-Based Automatic Diagnosis System for Facial Nerve Palsy. Sensors 2015, 15, 26756-26768.

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