Evidence map›Paper›PMID 36081094›Full record

ArticleSensors (Basel, Switzerland)2022

Numerical Approach to Facial Palsy Using a Novel Registration Method with 3D Facial Landmark.

Junsik Kim, Hyungwha Jeong, Jeongmok Cho, Changsik Pak, Tae Suk Oh, Joon Pio Hong, Soonchul Kwon, Jisang Yoo

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. [The assessment of facial nerve function].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Junsik KimDepartment of Electronic Engineering, Kwangwoon University, Seoul 01897, Korea.
Hyungwha JeongDepartment of Plastic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.
Jeongmok ChoDepartment of Plastic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.
Changsik PakDepartment of Plastic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.ORCID 0000-0002-3477-7120
Tae Suk OhDepartment of Plastic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.
Joon Pio HongDepartment of Plastic Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.ORCID 0000-0002-6208-9704
Soonchul KwonGraduate School of Smart Convergence, Kwangwoon University, Seoul 01897, Korea.ORCID 0000-0001-6595-6415
Jisang YooDepartment of Electronic Engineering, Kwangwoon University, Seoul 01897, Korea.
Ulsan College · KRKwangwoon University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment of facial palsy is essential because neglecting this disorder can lead to serious sequelae and further damage. For an objective evaluation and consistent rehabilitation training program of facial palsy patients, a clinician's evaluation must be simultaneously performed alongside quantitative evaluation. Recent research has evaluated facial palsy using 68 facial landmarks as features. However, facial palsy has numerous features, whereas existing studies use relatively few landmarks; moreover, they do not confirm the degree of improvement in the patient. In addition, as the face of a normal person is not perfectly symmetrical, it must be compared with previous images taken at a different time. Therefore, we introduce three methods to numerically approach measuring the degree of facial palsy after extracting 478 3D facial landmarks from 2D RGB images taken at different times. The proposed numerical approach performs registration to compare the same facial palsy patients at different times. We scale landmarks by performing scale matching before global registration. After scale matching, coarse registration is performed with global registration. Point-to-plane ICP is performed using the transformation matrix obtained from global registration as the initial matrix. After registration, the distance symmetry, angular symmetry, and amount of landmark movement are calculated for the left and right sides of the face. The degree of facial palsy at a certain point in time can be approached numerically and can be compared with the degree of palsy at other times. For the same facial expressions, the degree of facial palsy at different times can be measured through distance and angle symmetry. For different facial expressions, the simultaneous degree of facial palsy in the left and right sides can be compared through the amount of landmark movement. Through experiments, the proposed method was tested using the facial palsy patient database at different times. The experiments involved clinicians and confirmed that using the proposed numerical approach can help assess the progression of facial palsy.

Indexed as

Facial ParalysisDatabases, FactualHumansImaging, Three-DimensionalMovement3D facial landmarkfacial palsyiterative closest pointregistrationsymmetry

Identifiers

PMID36081094
PMCPMC9459972
OpenAlexW4295079600

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.