Go to:
Logótipo
Você está em: Start > Publications > View > GoNet - A New Movement Dynamic Evaluation System in Real Time
Map of Premises
Principal
Publication

GoNet - A New Movement Dynamic Evaluation System in Real Time

Title
GoNet - A New Movement Dynamic Evaluation System in Real Time
Type
Article in International Scientific Journal
Year
2015
Authors
J. M. R. S. Tavares
(Author)
FEUP
View Personal Page You do not have permissions to view the institutional email. Search for Participant Publications View Authenticus page View ORCID page
J. S. C. Neto
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
V. H. C. de Albuquerque
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
G. P. F. Silva
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
N. B. C. Olegario
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Journal
Vol. 13 No. 12
Pages: 3928-3933
ISSN: 1548-0992
Publisher: IEEE
Indexing
Scientific classification
CORDIS: Technological sciences
FOS: Engineering and technology
Other information
Authenticus ID: P-00K-803
Abstract (EN): The development of a hybrid solution (hardware and software) integrating a computer and the Kinect sensor is presents in this paper. The solution proposed, here called GoNet, is a promising prototype to be used in dynamic and automatic evaluation of biomechanical rehabilitation processes. Experimental tests concerning the assessment of the range of motion of patients, particularly for elbow flexion, elbow extension, shoulder abduction, shoulder flexion, radial deviation and ulnar deviation, are presented and discussed. Eight healthy subjects were assessed using GoNet and a goniometer. The intraclass correlation coefficient (ICC) was used to analyze the reproducibility, and the Pearson correlation test was used in the analysis of transversal validity. The significance level was defined as equal to 5%. As to the intra- and inter-examiner reproducibility, high ICC values were found for the range of motion of shoulder flexion/extension, shoulder abduction/adduction, radial deviation and ulnar deviation. When evaluated by two experts the correlation between the goniometry and GoNet, significant results were observed for the amplitude of shoulder flexion/extension (r = 0.74; p = 0.03) and elbow flexion/extension (r = 0.67, p = 0.04). Based on the results obtained, GoNet proved to have high reproducibility, except for intraexaminer assessment of elbow flexion/extension. Regarding the transverse validity, relevant measurement results were found in terms of flexion/extension of the elbow and shoulder.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 6
License type: Click to view license CC BY-NC
Documents
File name Description Size
IEEE-2758 paper 2278.65 KB
Related Publications

Of the same journal

Unit Commitment in a Competitive and Emission Constrained Environment (2009)
Article in International Scientific Journal
Catalao, JPS; Mariano, SJPS; Mendes, VMF; Ferreira, LAFM
Support at Decision in Electrical Systems of subtransmission through selection of Topologies by a Paraconsistent Simulator (2016)
Article in International Scientific Journal
Da Silva Filho, JI; Camargo, JDM; Dos Santos, MR; Onuki, AS; Mario, MC; Ferrara, LFP; Garcia, DV; Pereira, JMC; Rocco, A
Real-time industrial communication over IEEE802.11e wireless local area networks (2012)
Article in International Scientific Journal
Raimundo Viegas; L. A. Guedes; Francico Vasques; Paulo Portugal; Ricardo Moraes; Luiz Affonso
Predicting Long-Term Wind Speed in Wind Farms of Northeast Brazil: A Comparative Analysis Through Machine Learning Models (2020)
Article in International Scientific Journal
de Paula, M; Colnago, M; José Nuno Fidalgo; Casaca, W

See all (18)

Recommend this page Top
Copyright 1996-2025 © Faculdade de Medicina Dentária da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-07-22 at 02:42:53 | Privacy Policy | Personal Data Protection Policy | Whistleblowing | Electronic Yellow Book