GaitQualityAnalyzer

SEDMIDUBSKÝ, Jan; Tomáš LJUTENKO a Pavel ZEZULA. GaitQualityAnalyzer. 2022.

Základní údaje

Originální název

GaitQualityAnalyzer

Autoři

SEDMIDUBSKÝ, Jan; Tomáš LJUTENKO a Pavel ZEZULA

Vydání

2022

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Další údaje

Jazyk

angličtina

Typ výsledku

Software

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/22:00127383

Organizační jednotka

Fakulta informatiky

Klíčová slova anglicky

3D motion data;gait cycle;similarity search;gait quality assessment

Technické parametry

The technical documentation of the GaitQualityAnalyzer system, including the description of installation steps, system design, and graphical user interface, is available at the system web page.

Příznaky

Mezinárodní význam

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Anotace

V originále

GaitQualityAnalyzer is a system for analyzing the quality of human gait. The system manages human subjects along with their gait style recorded in different time periods in the form of motion capture data. The main system objective is to provide the functionality for searching for similar movement patterns on the level of gait cycles and assessing the quality of the retrieved patterns. This enables determining whether a subject performs better or worse after some circumstance, e.g., underwent surgery. Even if the system is intended to be used for evaluating the suitability of treatments for patients suffering from cerebral-palsy disease, it can be potentially applied to other scenarios in which the quality of movement patterns needs to be analyzed. The system is implemented as a client-server architecture with a web-based graphical user interface. The interface primarily allows users to: (1) manage subjects, visits of subjects, and gait recordings associated with visits, (2) assess the quality of gait recordings, (3) search for similar gait recordings of other subjects based on a pre-trained recurrent neural network model, and (4) determine whether the most relevant retrieved subjects exhibit an improvement or deterioration of gait style.

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Návaznosti

MUNI/G/1585/2019, interní kód MU

Název: Improving Treatments in Cerebral-Palsy Children using Artificial Intelligence Investor: Masarykova univerzita, Improving Treatments in Cerebral-Palsy Children using Artificial Intelligence, INTERDISCIPLINARY - Mezioborové výzkumné projekty