Name
Abstract | ||
|---|---|---|
This work proposes a model of movement detection in patients with hip surgery rehabilitation. Using the Microsoft Xbox One Kinect motion capture device, information is acquired from 25 body points -with their respective coordinate axes- of patients while doing rehabilitation exercises. Bayesian networks and sUpervised Classification System (UCS) techniques have been jointly applied to identify correct and incorrect movements. The proposed system generates a multivalent logical model, which allows the simultaneous representation of the exercises performed by patients with good precision. It can be a helpful tool to guide rehabilitation. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-94120-2_42 | INTERNATIONAL JOINT CONFERENCE SOCO'18-CISIS'18- ICEUTE'18 |
Keywords | Field | DocType |
Movement detection,Kinect,Bayesian networks,sUpervised Classification System,Rehabilitation | Motion capture,Rehabilitation,Computer science,Logical data model,Movement detection,Bayesian network,Artificial intelligence,Surgery,Machine learning | Conference |
Volume | ISSN | Citations |
771 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| César Guevara | 1 | 0 | 0.34 |
| Matilde Santos | 2 | 143 | 24.39 |
| Janio Jadán | 3 | 0 | 0.34 |