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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zilic, Zeljko Roshan Fekr, Atena Radecka, Katarzyna Janidarmian, Majid |
| Copyright Year | 2015 |
| Abstract | Approximately, 21,000 breaths per day and 10.5 million breaths per year are taken by average people. Breathing functions depend on the actions of the respiratory muscles on the chest wall. This study analyzes the motions of the humans’ chest compartments with a portable, low-cost and convenient monitoring system to be used in e-health applications. Two wearable MEMS sensors are used to capture the rib cage (RC) and abdomen (AB) movements, simultaneously. In addition to measuring the phase shift between the chest wall compartments, the impacts of different body positions on AB and RC motions have been investigated on four different respiration patterns with ten subjects. The performance of the presented system is evaluated and the average mean square error of 0.13 is achieved for three time parameters including inspiratory, expiratory, and total time of the respiratory cycle. Moreover, the overall errors of phase shifts for paradoxical and synchronous breath patterns are 0.13° ± 0.12° and 0.21° ± 0.08°, respectively, considering two vernier respiration monitor belts as our references. The system properly indicates a significant increase in the degree of RC and AB asynchrony in the paradoxical breathing compared to normal pattern. To complete our platform, we propose a new “Breathing Therapy” technique as an advanced way to assist people to learn the science of breath and help the patients successfully restore their health in a systematic way. Graphical signs are used to provide feedback on the quality of each breath taken in real-time. The performance of the system is evaluated based on five well-known yogic breathing patterns. |
| Starting Page | 1 |
| Ending Page | 20 |
| Page Count | 20 |
| File Format | |
| ISSN | 21926662 |
| Journal | Network Modeling Analysis in Health Informatics and Bioinformatics |
| Volume Number | 4 |
| Issue Number | 1 |
| e-ISSN | 21926670 |
| Language | English |
| Publisher | Springer Vienna |
| Publisher Date | 2015-08-01 |
| Publisher Place | Vienna |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Accelerometer sensor Computational Biology/Bioinformatics Breathing therapy Complex Networks Body posture Health Informatics Bioinformatics Respiration pattern |
| Content Type | Text |
| Resource Type | Article |
| Subject | Urology |
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