Name
Abstract | ||
|---|---|---|
Gait analysis is the measurement, processing and systematic interpretation of biomechanical parameters that characterize human locomotion. It supports the identification of movement limitations and development of rehabilitation procedures. Accurate Gait analysis is important in sports analysis, medical field, and rehabilitation. Although Gait analysis is performed in several laboratories in many countries, there are many issues such as: (i) the high cost of precise Motion Capture systems; (ii) the scarcity of qualified personnel to operate them; (iii) expertise required to interpret their results; (iv) space requirements to install and store these systems; as well as difficulties related to the measurement protocols of each system; (vi) limited availability (vii) and the use of markers can be a barrier for some clinical use cases (e.g. patients recovering from orthopedics surgeries). In this work, we present a low cost and more accessible system based on the integration of a Multiple Microsoft Kinect sensors and multiple Shimmer inertial sensors to capture human Gait. The novel multimodal system combines data from inertial and 3D depth cameras and outputs spatiotemporal Gait variables. A comparison of this system with the VICON system (the gold standard in Motion Capture) was performed. Our relatively low-cost marker-less multimodal motion generates a complete 360-degree skeleton view. We compare our system with the VICON via gait spatiotemporal variables: Gait cycle time, stride time, Gait length (distance between two strides), stride length, and velocity. The system was also evaluated with knee and hip joint angles measurement accuracy. The results show high correlation for spatiotemporal variables and joint angles inside the 95% bootstrap prediction when compared with VICON. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11042-019-08275-9 | Multimedia Tools and Applications |
Keywords | Field | DocType |
3D model, Gait analysis, Motion capture, Multimodal sensors | Inertial frame of reference,Motion capture,Computer vision,Use case,Pattern recognition,STRIDE,Gait,Computer science,Gait analysis,Inertial measurement unit,Artificial intelligence,Gait (human) | Journal |
Volume | Issue | ISSN |
79 | 3-4 | 1573-7721 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thiago Braga Rodrigues | 1 | 6 | 1.52 |
| Débora Pereira Salgado | 2 | 5 | 1.84 |
| Ciaran Ó Catháin | 3 | 1 | 0.70 |
| Noel E. O'Connor | 4 | 2137 | 223.20 |
| Niall Murray | 5 | 102 | 19.17 |