Name
Title | ||
|---|---|---|
Noise Reduction in Swallowing Muscle Activity Measurement Based on Mixture Gaussian Distribution Model. |
Abstract | ||
|---|---|---|
For the noninvasive measurement of swallowing muscle activity, surface electromyograms and swallowing sounds are used. The electromyogram electrodes can be placed appropriately only by experts with specialized knowledge about the location of the swallowing muscle group. Therefore, these sensors have not been used for measurements in food development, for which there were no experts. In order to develop a simple swallowing muscle measurement method for food development, we proposed a sensor sheet consisting of multiple electromyogram electrodes and observed that different swallowing muscle activities could be measured depending on the type of food. In this work, we study a calculation method for the elimination of noise, which is inevitable in electromyograms, from the sensor sheet measurement results and prove that the method improves the performance of the swallowing muscle activity measurements. |
Year | Venue | Keywords |
|---|---|---|
2017 | JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | swallowing,sensor sheet,noise,electromyography |
Field | DocType | Volume |
Muscle activity,Noise reduction,Swallowing,Distribution model,Pattern recognition,Computer science,Speech recognition,Gaussian,Artificial intelligence | Journal | 21 |
Issue | ISSN | Citations |
1 | 1343-0130 | 0 |
PageRank | References | Authors |
0.34 | 1 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nobuyuki Ohmori | 1 | 0 | 0.34 |
| Chihiro Murasawa | 2 | 0 | 0.34 |
| Jumpei Aizawa | 3 | 0 | 0.34 |
| Hideya Momose | 4 | 0 | 0.34 |
| Yoshito Koyama | 5 | 0 | 0.34 |
| Hiroshi Kurita | 6 | 0 | 0.34 |
| Hiroaki Yoshida | 7 | 0 | 0.34 |
| Masayoshi Kamijo | 8 | 8 | 5.73 |