Name
Abstract | ||
|---|---|---|
Analysing distinct motion patterns that occur during infancy can be a way through early prediction of cerebral palsy. This analysis can only be performed by well-trained expert clinicians, and hence can not be widespread, specially in poor countries. In order to decrease the need for experts, computer-based methods can be applied. If individual motions of different body parts are available, these methods could achieve more accurate results with better clinical insight. Thus far, motion capture systems or the like were needed in order to provide such data. However, these systems not only need laboratory and experts to set up the experiment, but they could be intrusive for the infant's motions. In this paper we build up our prediction method on a solution based on a single video camera, that is far less intrusive and a lot cheaper. First, the motions of different body parts are separated, then, motion features are extracted and used to classify infants to healthy or affected. Our experimental results show that visually obtained motion data allows cerebral palsy detection as accurate as state-of-the-art electromagnetic sensor data. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/EMBC.2014.6944446 | EMBC |
Keywords | Field | DocType |
video signal processing,paediatrics,medical disorders,cerebral palsy detection,early prediction,motion patterns,motion data,infancy,biomedical optical imaging,motion feature extraction,motion capture systems,image segmentation,video cameras,single video camera,body part individual motions,feature extraction,infant motions,computer-based methods,motion segmentation,clinical insight,medical image processing,electromagnetic sensor data,video-based early cerebral palsy prediction,image motion analysis | Structure from motion,Motion capture,Computer vision,Computer science,Segmentation,Cerebral palsy,Artificial intelligence,Video camera,Videotape Recording | Conference |
Volume | ISSN | Citations |
2014 | 1557-170X | 5 |
PageRank | References | Authors |
0.50 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hodjat Rahmati | 1 | 5 | 0.83 |
| Ole Morten Aamo | 2 | 5 | 0.50 |
| Ø. Stavdahl | 3 | 108 | 8.16 |
| Ralf Dragon | 4 | 5 | 0.50 |
| Lars Adde | 5 | 5 | 0.50 |