Both the theoretical background and the experimental results of an algorithm developed to perform human respiratory rate measurements without any physical contact are presented. Based on depth image sensing techniques, the respiratory rate is derived by measuring morphological changes of the chest wall. The algorithm identifies the human chest, computes its distance from the camera and compares this value with the instantaneous distance, discerning if it is due to the respiratory act or due to a limited movement of the person being monitored. To experimentally validate the proposed algorithm, the respiratory rate measurements coming from a spirometer were taken as a benchmark and compared with those estimated by the algorithm. Five tests were performed, with five different persons sat in front of the camera. The first test aimed to choose the suitable sampling frequency. The second test was conducted to compare the performances of the proposed system with respect to the gold standard in ideal conditions of light, orientation and clothing. The third, fourth and fifth tests evaluated the algorithm performances under different operating conditions. The experimental results showed that the system can correctly measure the respiratory rate, and it is a viable alternative to monitor the respiratory activity of a person without using invasive sensors.

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This paper presents a discrete-time variablestructure control (DTVSC) for the dynamic positioning system of a marine vessel. The DTVSC guarantees robustness with respect to environmental disturbances. Moreover, the allocation problem, in the case of vessels with azimuth thrusters, represents a challenging problem since a non-convex nonlinear problem must be solved. In this paper, the allocation problem is solved using the Damped Least Squares method. The proposed solution is compared with a PID-based control. Reported simulations show that the proposed solution produces better performance.

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