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In this paper, feasibility of web based breathing exercises for respiratory rehabilitation is examined. A system included visual guidance in a web browser and a microphone equipped headset for biofeedback and interaction. Feasibility was assessed in a controlled environment on 34 subjects with anxiety disorders that were not offered any help from the personnel. Weak points of comprehensibility were identified as applying headset (21%) and adhering to breathing exercises instructions (7%). No adverse events were identified. Design flaws that correlated with poor user’s experience were 1) the unpleasant feelings induced by watching the computer screen (21%) and 2) ease/difficulty of physically applying headset (14%). We conclude that conducting breathing exercises by using an acoustic microphone and a web browser is feasible and should be further researched. Additionally we conclude that audio feedback might be more pleasant to some people. Further we conclude that BREATHING+ has some obvious advantages over alternative devices for respiratory rehabilitation, these are: (more…)

We demonstrate a low latency respiratory/breathing frequency detection system that is fast (<5ms), easy to operate, requires no batteries or external power supply and operates fully via computer-standard USB connection. Exercises in controlling ones breathing frequency, usually referred to as paced breathing exercises, have shown positive effects in treating pulmonary diseases, cardiovascular diseases and stress/anxiety-related disorders. We developed a breathing frequency detection system which uses two pairs of microphones to detect exhalation activity, eliminate noise from the environment and stream the recording data via USB connection to a personal computer. It showed 97.1% reliability (10 subjects) when monitoring breathing activity in non-guided free breathing and 100% reliability (10 subjects) when monitoring breathing activity during interactive paced-breathing exercises. We also evaluated the breathing frequency detection systems noise elimination functionality which showed a reduction of 84.2 dB for stationary (white noise) and a reduction of 79.3 dB for nonstationary (hands clapping) noise.

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