Name
Abstract | ||
|---|---|---|
Lower limb injuries, especially those related to the knee joint, are some of the most common and severe injuries among sport practitioners. Consequently, a growing interest in the identification of subjects with high risk of injury has emerged during last years. One of the most commonly used injury risk factor is the measurement of joint angles during the execution of dynamic movements. To that end, techniques such as human motion capture and video analysis have been widely used. However, traditional procedures to measure joint angles present certain limitations, which makes this practice not practical in common clinical settings. This work presents SPIRA, a novel 2D video analysis system directed to support practitioners during the evaluation of joint angles in functional tests. The system employs an infrared camera to track retro-reflective markers attached to the patient’s body joints and provide a real-time measurement of the joint angles in a cost-and-time-effective way. The information gathered by the sensor is processed and managed through a computer application that guides the expert during the execution of the tests and expedites the analysis of the results. In order to show the potential of the SPIRA system, a case study has been conducted, performing the analysis with the both the proposed system and a gold-standard in 2D offline video analysis. The results (ICC(\(\rho\)) = 0.996) reveal a good agreement between both tools and prove the reliability of SPIRA. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s12652-018-0722-6 | Journal of Ambient Intelligence and Humanized Computing |
Keywords | Field | DocType |
Injury risk, Lower limb, Joint angles, Marker tracking, Computer vision, Kinect, 2D video analysis | Computer vision,Lower limb injury,Lower limb,Computer science,Human motion,Knee Joint,Artificial intelligence,Body joints | Journal |
Volume | Issue | ISSN |
10 | 6 | 1868-5145 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Bailon | 1 | 2 | 1.11 |
| M. Damas | 2 | 387 | 33.04 |
| Héctor Pomares | 3 | 651 | 64.11 |
| Oresti Baños | 4 | 380 | 35.57 |