Engineering Commons^™

Health Monitoring Using Deep Learning Of Acoustic And Speech Signals, Eric E. Hamke

Electrical and Computer Engineering ETDs

The focus of the research is to identify stress markers in a firefighter's speech. These markers include changes in breathing patterns and changes in the fundamental frequency of an individual’s voice. The breathing patterns are characterized using the number of breaths taken in a minute and the time spent inhaling. These measures are estimated using a Restricted Boltzmann Machine to process a firefighters’ SCBA regulator sounds, as open and closed. The classifications are then combined into continuous intervals. Observing the length of the intervals and the number of interval-starts represents time spent inhaling and the breathing rates (breaths per minute). …