A variety of signal processing methods have been developed for detecting the heartbeat from signals obtained by non-invasive devices. In this paper, an algorithm developed for the accurate detection of heartbeats from a ballistocardiography signal is presented. The signal is obtained using a regular chair adapted with Electro-Mechanical Film (EMFi) sensors and an acquisition system, so a ballistocardiogram is generated. The presence of important disturbances in this type of signal is unavoidable due to several natural causes; therefore, its processing involves significant difficulties to be tackled in order to obtain reliable lectures of the heartbeat. The algorithm presented here performs consistently well, showing a very low error rate, even if the signal contains significant noise.
The location of sensors represents a relevant attribute in wireless sensor networks. In this article, we propose a distributed range-based localization algorithm for wireless sensor network. The algorithm is mainly based on an adaptively local circular searching area where each unknown sensor must find inside a position that minimizes the error distance with neighboring sensors using a local function. The new position of a sensor is broadcast to neighboring sensors allowing collaboratively to other sensors re-estimate their new positions. The iterative process is repeated until a stopping criterion is reached. The performance of the proposed algorithm is evaluated and compared with other state-of-the-art algorithms, and results indicate that the approach overcomes the other methods in both accuracy and time of convergence.
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