Advanced Statistical Analysis of 3D Kinect Data: Mimetic Muscle Rehabilitation Following Head and Neck Surgeries Causing Facial Paresis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064173%3A_____%2F20%3AN0000021" target="_blank" >RIV/00064173:_____/20:N0000021 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11120/21:43920903 RIV/60461373:22340/21:43923556 RIV/00064173:_____/21:N0000178

Result on the web

<a href="https://doi.org/10.3390/s21010103" target="_blank" >https://doi.org/10.3390/s21010103</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s21010103" target="_blank" >10.3390/s21010103</a>

Result language

angličtina

Original language name

Advanced Statistical Analysis of 3D Kinect Data: Mimetic Muscle Rehabilitation Following Head and Neck Surgeries Causing Facial Paresis

Original language description

An advanced statistical analysis of patients' faces after specific surgical procedures that temporarily negatively affect the patient's mimetic muscles is presented. For effective planning of rehabilitation, which typically lasts several months, it is crucial to correctly evaluate the improvement of the mimetic muscle function. The current way of describing the development of rehabilitation depends on the subjective opinion and expertise of the clinician and is not very precise concerning when the most common classification (House-Brackmann scale) is used. Our system is based on a stereovision Kinect camera and an advanced mathematical approach that objectively quantifies the mimetic muscle function independently of the clinician's opinion. To effectively deal with the complexity of the 3D camera input data and uncertainty of the evaluation process, we designed a three-stage data-analytic procedure combining the calculation of indicators determined by clinicians with advanced statistical methods including functional data analysis and ordinal (multiple) logistic regression. We worked with a dataset of 93 distinct patients and 122 sets of measurements. In comparison to the classification with the House-Brackmann scale the developed system is able to automatically monitor reinnervation of mimetic muscles giving us opportunity to discriminate even small improvements during the course of rehabilitation.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30206 - Otorhinolaryngology

Project

—

Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors

ISSN

1424-8220

e-ISSN

—

Volume of the periodical

21

Issue of the periodical within the volume

1

Country of publishing house

CH - SWITZERLAND

Number of pages

21

Pages from-to

103

UT code for WoS article

000606098600001

EID of the result in the Scopus database

2-s2.0-85098778618