Korean J Otolaryngol-Head Neck Surg.  2001 Nov;44(11):1140-1144.

Blepharokymography: A New Tool for Dynamic Eyelid Motion Analysis Using Image Processing

Affiliations
  • 1Department of Otorhinolaryngology-Head & Neck Surgery, Hallym University College of Medicine, Seoul, Korea.
  • 2Department of Otolaryngology, Seoul National University College of Medicine, Seoul, Korea.
  • 3Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea.

Abstract

BACKGROUND AND OBJECTIVES: Evaluation of facial movements, especially eyelid movements, per se, depends largely on subjective judgments of trained clinicians. Recently, however, a few objective methods were reported although they required bothersome markers attached on the eyelids and a special-purpose high-speed video camera. This study aimed to develop a new dynamic and quantitative analysis system for eyelid motion using an image processing method without markers or a high-speed camera, and to evaluate parameters that could properly differentiate normal and abnormal states. MATERIALS AND METHOD: The system was consisted of a personal computer with a general-purpose frame grabber and a specially developed software which was named, Blepharokymography. Displacement of upper eyelids, duration of closing and opening segments, and closing and opening velocity were measured in 12 normal subjects and 5 facial nerve palsy patients of variable causes. Mean values of each parameter and the ratio of a palsy or slower side to a normal or faster side in normal and facial palsy groups were compared.
RESULTS
In the normal group, the mean displacement of upper eyelids, mean closing time, mean and peak closing velocity were 8.3mm, 161 msec. 61.6 mm/sec and 146.2 mm/sec respectively. Among parameters, displacement, the closing time, mean closing velocity and peak closing velocity were significantly different between normal and facial palsy groups.
CONCLUSION
By using blepharokymography system, it was possible to measure the eyelid motion objectively. Displacement, closing time, average and peak closing velocity were useful in differentiating the normal state as well as the facial nerve palsy state.

Keyword

Eyelids; Facial nerve; Kymography; Image processing; computer-assisted

MeSH Terms

Eyelids*
Facial Nerve
Facial Paralysis
Humans
Judgment
Kymography
Microcomputers
Paralysis
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