Fast and cost-effective method for non-contact respiration rate tracking using UWB impulse radar

• Published in: Sensors and actuators. A. Physical. Vol. 329; p. 112814
• Main Authors: Kakouche, Ibrahim, Maali, Abdelmadjid, El Korso, Mohammed Nabil, Mesloub, Ammar, Azzaz, Mohamed Salah
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 01.10.2021; Elsevier BV
• Subjects: Algorithms; Breath monitoring; Breathing; Clutter; Complex adaptive notch filter; Complexity; Control charts; Double exponential moving average; Emergency warning programs; Generalized Goertzel Algorithm; Health; Notch filters; Radar tracking; Respiration; Ultrawideband radar; UWB radar; Vital signs; Generalized Goertzel Algorithm; Double exponential moving average; Vital signs; Complex adaptive notch filter; Breath monitoring; UWB radar
• ISSN: 0924-4247; 1873-3069
• DOI: 10.1016/j.sna.2021.112814

[Display omitted] •Non-contact-based solution using UWB radar for VS monitoring, offers an adequate measurement without restricting the person's freedom.•Extraction of VS signal directly from the collected radar data using the GGA avoiding the prior knowledge of the person location and overcoming the effect of the clutter.•RR tracking based on the CANF with a variable step size to offer a robust estimation against SRBM and a fast tracking of the breath variability.•Design a control chart of the breathing process using the DEMA in order to detect the apnea. Breathing rate monitoring for a long period provides a valuable indicator about human health and an early warning of possible disasters on the well-being. To gain a comfortable and adequate measurement without restricting the person's privacy, this study investigates a novel non-contact-based solution using ultra wide-band (UWB) impulse radar. We propose a fast and low-cost method for breathing events detection and respiration rate (RR) tracking. This novel approach consists of three main parts: vital signs (VS) patterns extraction based on the Generalized Goertzel Algorithm (GGA) avoiding the prior knowledge of the person's location and overcoming the effect of the clutter. RR tracking built on the complex adaptive notch filter (CANF) with a variable step size to obtain a robust estimation under the presence of sparse random body movement (SRBM) and fast tracking of the breath variability. Finally, we introduce a control chart of the breathing process using the double exponential moving average (DEMA) in order to detect the apnea events. The proposed method is evaluated using two sets of experiments, from mechanical vibrating structure to human subject. The results demonstrate that the proposed system is a promising and effective solution and provides wide usability for continuous monitoring applications. Moreover, it outperforms the state-of-the-art, in terms of computation cost and space complexity.