RESUMEN
The aim of this work is to show non-contact physiological signal monitoring system based on continuous-wave (CW) Doppler radar, which is becoming highly attractive in the field of health care monitoring of elderly people. Two radar signal processing methods were introduced in this paper: one to extract respiration and heart rates of a single person and the other to separate mixed respiration signals. To verify the validity of the methods, physiological signal is obtained from stationary human subjects using a CW Doppler radar unit. The sensor operating at 24 GHz is located 0.5 meter away from the subject. The simulation results show that the respiration and heart rates are clearly extracted, and the mixed respiration signals are successfully separated. Finally, reference respiration and heart rate signals are measured by an ECG monitor and compared with the results tracked by the CW Doppler radar monitoring system.
Asunto(s)
Monitoreo Fisiológico/instrumentación , Respiración , Procesamiento de Señales Asistido por Computador , Ultrasonografía Doppler , Adulto , Algoritmos , Simulación por Computador , Electrocardiografía , Diseño de Equipo , Frecuencia Cardíaca , Humanos , Masculino , Microondas , Radar , Programas InformáticosRESUMEN
In disaster rescue, breathing motion detection is an important approach to searching survivors trapped under debris. Detection of breathing motion is realized by detecting the respiratory signal acquired by the sensing system. In this paper, modeling the regular respiratory signal is studied. Firstly, a preliminary model is built based on power of absolute value of cosine function. Then, this preliminary model is improved in terms of some practical considerations, such as the DC-component of the respiratory signal often is removed by signal processing, and a phase uncertainty occurs due to the data acquisition. Finally, an analytical harmonic-based random respiratory signal model is derived, which can be used as the signal model in the future research about breathing motion detection.
Asunto(s)
Modelos Teóricos , Respiración , Procesamiento de Señales Asistido por Computador , Humanos , Factores de TiempoRESUMEN
Through-wall respiration detection using Ultra-wideband (UWB) impulse radar can be applied to the post-disaster rescue, e.g., searching living persons trapped in ruined buildings after an earthquake. Since strong interference signals always exist in the real-life scenarios, such as static clutter, noise, etc., while the respiratory signal is very weak, the signal to noise and clutter ratio (SNCR) is quite low. Therefore, through-wall respiration detection using UWB impulse radar under low SNCR is a challenging work in the research field of searching survivors after disaster. In this paper, an improved UWB respiratory signal model is built up based on an even power of cosine function for the first time. This model is used to reveal the harmonic structure of respiratory signal, based on which a novel high-performance respiration detection algorithm is proposed. This novel algorithm is assessed by experimental verification and simulation and shows about a 1.5dB improvement of SNR and SNCR.
Asunto(s)
Algoritmos , Radar , Respiración , Simulación por Computador , Análisis de Fourier , Humanos , Probabilidad , Relación Señal-RuidoRESUMEN
With the explosive development of wireless communication technology, more and more implanted medical devices appear in everyday life. Because of the limited energy resource in implanted devices, the energy-quality wireless system design is the biggest challenge. In this paper, we update our former system level energy model and make it suitable for implantable medical communication system. In the new model, the impacts of human body tissue on the signal transmission are considered. The wireless system energy consumption is minimized by adjusting the digital base-band and RF parameters such as signal bandwidth, peak-to-average ratio (PAR), modulation levels, data rates etc. In the communication quality evaluation, we consider the effects of 1/f noise and the third-order harmonic distortion in addition to normal channel noise.