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Monitoring breathing is required in many applications of medical and health fields but it can also be used also in a new set of applications that involve fields as diverse as entertainment games or some new applications oriented to develop skills such as focused attention. As smartphones are widespread around the world it is assumed that an important number of such applications must run on such platforms. In this work, an automatic, low-complex real-time system for monitoring breathing is presented. The system uses the acoustic signal recorded by a standard microphone placed in the area of the nostrils. The method is based on the Sequencial Walsh Hadamard (SWH) transform coefficients computed on non-overlapped frames to finally provide a reduced set of real parameters. These parameters feed a linear classifier that labels the frames in three different groups: inspiration, transition and expiration, in real time. The system runs in a smartphone or any portable device, only requiring as auxiliary equipment, a standard microphone from a conventional Bluetooth Headset.
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