Non-Contact Detection of Breathing Using a Microwave Sensor

Dei, Devis; Grazzini, Gilberto; Luzi, G.; Pieraccini, Massimiliano; Atzeni, C.; Boncinelli, S; Camiciottoli, Gianna; Castellani, Walter; Marsili, M; Dico, Juri Lo

doi:10.3390/s90402574

Cited by 57 publications

(44 citation statements)

References 18 publications

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“…These sensors were introduced in 1970s demonstrating, for the first time, the concept of contactless vital signs detection [17,18]. In recent years, the technological advances have triggered numerous studies on CW Doppler radars devoted on one hand to the miniaturization and sensitivity improvement [19,20] and on the other hand to their assessment in new applicative contexts [21][22][23][24][25][26]. In medicine, these radar systems have been proposed for preventing sudden infant death syndrome [22], tumor tracking in radiation therapy [22], sleep monitoring [23], imaging cardiac motion [24], monitoring of elderly subjects in smart homes [16], and detection of sleep breathing disorder episodes in living animals [25].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

2016

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This paper deals with the development of a short-range radar suitable for the detection of humans behind visually opaque structures such as building walls. The system consists in a continuous wave Doppler radar operating in the S-band of the electromagnetic spectrum in order to ensure an adequate signal penetration through the walls. Based on the interaction of the electromagnetic waves with human targets, a phase modulation of the radar signal arises due to their movements and tiny periodic chest displacements associated with the respiratory activity. A simple and effective radar data processing algorithm is proposed to detect, in real-time, the presence of one or several human subjects in the through-wall scene. Such an algorithm automatically provides also an indication on whether the subjects are static or moving in the environment. As shown by experimental tests carried out in an indoor scenario, the proposed sensing device and related signal processing yields prompt and reliable information about the scene thus confirming its practical value.

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Section: Introductionmentioning

confidence: 99%

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

2016

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“…The contactless measurement of vital signs with bioradar technique is valuable in several application fields such as security and surveillance, healthcare, and space medicine [1][2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…From this information and a suitable signal processing, it is possible to extract the breathing and heartbeat pattern of the subject under test [2,[6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Metrological Characterization for Vital Sign Detection by a Bioradar

et al. 2017

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Abstract:In space missions, during the long isolation at extreme conditions for human health, it is of paramount importance to monitor vital parameters. One such parameter is the breathing rate. Indeed, several factors can induce some breathing anomalies during the sleep, which may cause apnea episodes. In order to act timely with the right therapy, an early diagnosis is required. Conventional devices are usually uncomfortable since they require electrodes or probes in contact with the subject. An alternative way to perform this kind of measurement in a remote sensing modality is provided by a continuous wave bioradar operating in the microwave frequency band. This is an effective contactless tool for monitoring the respiratory activity through the measurement of chest deformation due to inhalation and exhalation. The radar emits a low power electromagnetic wave at a single frequency, which is reflected by the human chest. By measuring of the phase shift between the incident and reflected wave, it is possible to detect and monitor the respiratory rate. The main contribution of this work is concerned with a metrological characterization of the continuous wave bioradar; which is a topic not thoroughly assessed in the relevant literature. In particular, the bioradar measurements are also compared with data recorded by a spirometer, which is a standard medical device that measures the air volume inhaled and exhaled by the subject. The purpose of this study is the characterization of the measurement standard uncertainty to enable the assessment of the bioradar system performance.

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“…Breathing has also been detected using a continuous wave single frequency microwave sensor (Dei et al, 2009).…”

Section: Noncontact Respiration Rate Monitoringmentioning

confidence: 99%

An Evaluation of Thermal Imaging Based Respiration Rate Monitoring in Children

Al-Khalidi

Saatchi

Elphick

et al. 2011

American Journal of Engineering and Applied Sciences

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Problem statement: An important indicator of an individual's health is respiration rate. It is the average number of times air is inhaled and exhaled per minute. Existing respiration monitoring methods require an instrument to be attached to the patient's body during the recording. This is a discomfort to the patient and the instrument can be dislodged from its position. Approach: In this study a novel noncontact, thermal imaging based respiration rate measurement method is developed and evaluated. Facial thermal videos of 16 children (age: Median = 6.5 years, minimum = 6 months, maximum = 17 years) were processed in the study. The recordings were carried out while the children rested comfortably on a bed. The children's respiration rates were also simultaneously measured using a number of conventional contact based methods. Results: This allowed comparisons with the thermal imaging method to be carried out. The image capture rate was 50 frames per second and the duration of a thermal video recording was 2 min per child. The thermal images were filtered and segmented to identify the nasal region. An algorithm was developed to automatically track the identified nasal area. This region was partitioned into eight equal concentric segments. The pixel values within each segment were averaged to produce a single thermal feature for that segment of the image. A respiration signal was obtained by plotting each segment's feature against time. Conclusion: Respiration rate values were automatically calculated by determining the number of oscillations in the respiration signals per minute. A close correlation (coefficient = 0.994) was observed between the respiration rates measured using the thermal imaging method and those obtained using the most effective conventional contact based respiration method.

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Non-Contact Detection of Breathing Using a Microwave Sensor

Cited by 57 publications

References 18 publications

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor

Metrological Characterization for Vital Sign Detection by a Bioradar

An Evaluation of Thermal Imaging Based Respiration Rate Monitoring in Children

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