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Clinical and non-clinical initial assessment of facial nerve paralysis: A qualitative review

Samsudin W. S. W., Sundaraj K.

Biocybernetics and Biomedical Engineering

2014

Vol. 34, no. 2

71--78

This paper illustrates a brief review of some clinical and non-clinical methods to evaluate the facial nerve function in facial paralysis cases. A rigorous search of online databases such as IEEE, Springer, Elsevier, ACM digital library, Wiley online library, and Pub Med was conducted from January, 2012 to August, 2013 to discover and examine previous works on the field of facial treatment and rehabilitation. A brief introduction of facial nerve paralysis is provided. We examined the type of facial disorders, the number of subjects, and methods used to evaluate the facial nerve function. Different keywords were used to acquire the studies based on the desired criteria. A total of 80 articles were identified and were analysed for inclusion in this search. A brief discussion of both types of methods is presented. In conclusion, the review provides recommendations for further improvements.

Profiling bell’s palsy based on House - Brackmann score

Song I., Vong J., Yen N. Y.., Diederich J., Yellowlees P.

Journal of Artificial Intelligence and Soft Computing Research

2013

Vol. 3, No. 1

41--50

In this study, we propose to diagnose facial nerve palsy using Support Vector Machines (SVMs) and Emergent Self-Organizing Map (ESOM). This research seeks to analyze facial palsy domain using facial features and grade the degree of nerve damage based on the House-Brackmann score. Traditional diagnostic approaches involve a medical doctor recording a thorough history of a patient and determining the onset of paralysis, rate of progression and so on. The most important step is to assess the degree of voluntary movement of the facial nerves and document the grade of facial paralysis using House- Brackmann score. The significance of the work is the attempt to understand the diagnosis and grading processes using semi-supervised learning with the aim of automating the process. The value of the research is in identifying and documenting the limited literature seen in this area. The use of automated diagnosis and grading greatly reduces the duration of medical examination and increases the consistency, because many palsy images are stored to provide benchmark references for comparative purposes. The proposed automated diagnosis and grading are computationally efficient. This automated process makes it ideal for remote diagnosis and examination of facial palsy. The profiling of a large number of facial images are captured using mobile phones and digital cameras.