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Jorge Caviedes | School of Computing, Informatics and Decision Systems Engineering
Monitoring spine posture during unsupervised therapeutic, athletic and fitness exercise is essential to achieve optimum results. The main objective of this work is to introduce wearable sensors and supporting mobile applications capable of providing biofeedback in real-time. The method includes algorithms trained to recognize the unique signature of the specific exercise and subject. Using a mobile app, the real-time execution can be monitored and the subject can receive instant personalized feedback in the form of a multimedia signal (e.g. auditory, visual or tactile). The applications of this research include intelligent garments, and large scale studies enabled by wireless data collection and analysis.