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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Identification of Directed Interactions in Kinematic Data during Running

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Author(s):
Nakashima, Giovana Y. [1, 2] ; Nakagawa, Theresa H. [3] ; dos Santos, Ana F. [4] ; Serrao, V, Fabio ; Bessani, Michel [1] ; Macie, Carlos D. [1]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Elect Engn Dept EESC, LPS, Sao Carlos, SP - Brazil
[2] Fed Inst Educ Sci & Technol Sao Paulo, Campus Salto, Salto - Brazil
[3] Laureate Int Univ, Uninorte, Manaus, Amazonas - Brazil
[4] V, Univ Fed Sao Carlos, Physiotherapy Dept, LAIOT, Sao Carlos, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY; v. 5, OCT 31 2017.
Web of Science Citations: 0
Abstract

The knowledge of motion dynamics during running activity is crucial to enhance the development of rehabilitation techniques and injury prevention programs. Recent studies investigated the interaction between joints, using several analysis techniques, as cross-correlation, sensitivity analysis, among others. However, the direction of the joints pairing is still not understood. This paper proposes a study of the influence direction pattern in healthy runners by using kinematic data together with partial directed coherence, a frequency approach of Granger causality. The analysis was divided into three anatomical planes, sagittal, frontal, and transverse, and using data from ankle, knee, hip, and trunk segments. Results indicate a predominance of proximal to distal influence during running, reflecting a centralized anatomic source of movements. These findings highlight the necessity of managing proximal joints movements, in addition to motor control and core (trunk and hip) strengthening training to lumbar spine, knee, and ankle injuries prevention and rehabilitation. (AU)

FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
Grantee:Marco Henrique Terra
Support type: Research Projects - Thematic Grants