50 research outputs found
Efficient quantitative assessment of facial paralysis using iris segmentation and active contour-based key points detection with hybrid classifier
BACKGROUND: Facial palsy or paralysis (FP) is a symptom that loses voluntary muscles movement in one side of the human face, which could be very devastating in the part of the patients. Traditional methods are solely dependent to clinician’s judgment and therefore time consuming and subjective in nature. Hence, a quantitative assessment system becomes apparently invaluable for physicians to begin the rehabilitation process; and to produce a reliable and robust method is challenging and still underway. METHODS: We introduce a novel approach for a quantitative assessment of facial paralysis that tackles classification problem for FP type and degree of severity. Specifically, a novel method of quantitative assessment is presented: an algorithm that extracts the human iris and detects facial landmarks; and a hybrid approach combining the rule-based and machine learning algorithm to analyze and prognosticate facial paralysis using the captured images. A method combining the optimized Daugman’s algorithm and Localized Active Contour (LAC) model is proposed to efficiently extract the iris and facial landmark or key points. To improve the performance of LAC, appropriate parameters of initial evolving curve for facial features’ segmentation are automatically selected. The symmetry score is measured by the ratio between features extracted from the two sides of the face. Hybrid classifiers (i.e. rule-based with regularized logistic regression) were employed for discriminating healthy and unhealthy subjects, FP type classification, and for facial paralysis grading based on House-Brackmann (H-B) scale. RESULTS: Quantitative analysis was performed to evaluate the performance of the proposed approach. Experiments show that the proposed method demonstrates its efficiency. CONCLUSIONS: Facial movement feature extraction on facial images based on iris segmentation and LAC-based key point detection along with a hybrid classifier provides a more efficient way of addressing classification problem on facial palsy type and degree of severity. Combining iris segmentation and key point-based method has several merits that are essential for our real application. Aside from the facial key points, iris segmentation provides significant contribution as it describes the changes of the iris exposure while performing some facial expressions. It reveals the significant difference between the healthy side and the severe palsy side when raising eyebrows with both eyes directed upward, and can model the typical changes in the iris region
Acupuncture for sequelae of Bell's palsy: a randomized controlled trial protocol
<p>Abstract</p> <p>Objective</p> <p>Incomplete recovery from facial palsy has a long-term impact on the quality of life, and medical options for the sequelae of Bell's palsy are limited. Invasive treatments and physiotherapy have been employed to relieve symptoms, but there is limited clinical evidence for their effectiveness. Acupuncture is widely used on Bell's palsy patients in East Asia, but there is insufficient evidence for its effectiveness on Bell's palsy sequelae. The objective is to evaluate the efficacy and safety of acupuncture in patients with sequelae of Bell's palsy.</p> <p>Method/Design</p> <p>This study consists of a randomized controlled trial with two parallel arms: an acupuncture group and a waitlist group. The acupuncture group will receive acupuncture treatment three times per week for a total of 24 sessions over 8 weeks. Participants in the waitlist group will not receive any acupuncture treatments during this 8 week period, but they will participate in the evaluations of symptoms at the start of the study, at 5 weeks and at 8 weeks after randomization, at which point the same treatment as the acupuncture group will be provided. The primary outcome will be analyzed by the change in the Facial Disability Index (FDI) from baseline to week eight. The secondary outcome measures will include FDI from baseline to week five, House-Brackmann Grade, lip mobility, and stiffness scales.</p> <p>Trial registration</p> <p>Current Controlled-Trials <a href="http://www.controlled-trials.com/ISRCTN43104115">ISRCTN43104115</a>; registration date: 06 July 2010; the date of the first patient's randomization: 04 August 2010</p
Management of peripheral facial nerve palsy
Peripheral facial nerve palsy (FNP) may (secondary FNP) or may not have a detectable cause (Bell’s palsy). Three quarters of peripheral FNP are primary and one quarter secondary. The most prevalent causes of secondary FNP are systemic viral infections, trauma, surgery, diabetes, local infections, tumor, immunological disorders, or drugs. The diagnosis of FNP relies upon the presence of typical symptoms and signs, blood chemical investigations, cerebro-spinal-fluid-investigations, X-ray of the scull and mastoid, cerebral MRI, or nerve conduction studies. Bell’s palsy may be diagnosed after exclusion of all secondary causes, but causes of secondary FNP and Bell’s palsy may coexist. Treatment of secondary FNP is based on the therapy of the underlying disorder. Treatment of Bell’s palsy is controversial due to the lack of large, randomized, controlled, prospective studies. There are indications that steroids or antiviral agents are beneficial but also studies, which show no beneficial effect. Additional measures include eye protection, physiotherapy, acupuncture, botulinum toxin, or possibly surgery. Prognosis of Bell’s palsy is fair with complete recovery in about 80% of the cases, 15% experience some kind of permanent nerve damage and 5% remain with severe sequelae