The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed.
Non-invasive UWB sensing of astronauts’ breathing activity / Baldi, Marco; Cerri, Graziano; Chiaraluce, Franco; Eusebi, L.; Russo, Paola. - In: SENSORS. - ISSN 1424-8220. - ELETTRONICO. - 15:(2015), pp. 565-591. [10.3390/s150100565]
Non-invasive UWB sensing of astronauts’ breathing activity
BALDI, Marco;CERRI, GRAZIANO;CHIARALUCE, FRANCO
;RUSSO, Paola
2015-01-01
Abstract
The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.