ABSTRACT
This paper presents a method for ultrasonic ranging based on the cross-correlation of two multi-frequency signals. The stimulus signal is composed by multiple sine-wave bursts/segments, each containing a different frequency and an integer number of periods. The frequency of each sine-wave burst is different from that of the adjacent bursts, but it is very close to the transducer resonant frequency. The time-of-flight (TOF) is estimated by finding the maximum of the cross-correlation. Interpolation is used to increase the measurement resolution. The experimental error corresponding to two standard deviations, for a range up to 1 m, is less than 0.3 mm.
ABSTRACT
Mobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations are frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to unavoidable power consumption limitations, the amount of data acquired, processed, and transmitted needs to be diminished, which is counterproductive, regarding the quality of the information produced. Compressed sensing implementation in wireless sensor networks (WSNs) promises to bring gains not only in power savings to the devices, but also with minor impact in signal quality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm states that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates the compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy management, and the improvements accomplished by in-network processing.
