Habitually poor posture can lead to repetitive strain injuries that lower an individual's quality of life and productivity. Slouching over computer screens and smart phones, asymmetric weight distribution due to uneven leg loading, and improper loading posture are some of the common examples that lead to postural problems and health ramifications. To help cultivate good postural habits, researchers have proposed slouching, balance, and improper loading posture detection systems that alert users through traditional visual, auditory or vibro-tactile feedbacks when posture requires attention. However, such notifications are disruptive and can be easily ignored. We address these issues with a new physiological feedback system that uses sensors to detect these poor postures, and electrical muscle stimulation to automatically correct the poor posture. We compare our automatic approach against other alternative feedback systems and through different unique contexts. We find that our approach outperformed alternative traditional feedback systems by being faster and more accurate while delivering an equally comfortable user experience.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2029 |
| Date | 01 January 2022 |
| Creators | Kattoju, Ravi Kiran |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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