Radar remote monitoring of vital signs

Li, Changzhi; Cummings, J. P.; Lam, Jennifer O; Graves, Eric; Wu, Whei Mei

doi:10.1109/mmm.2008.930675

Cited by 218 publications

(85 citation statements)

References 25 publications

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“…Empowered by body sensor network (BSN) technology these methods became more easily to deploy while being less obtrusive to patients. 8,9 More recently, Baltag and Popa 10 designed a microwave Doppler transducer and Li et al 11 proposed a radarbased approach for noninvasive respiratory monitoring, but their attempts are still premature for clinical employments. Accelerometers have been increasingly used in recently years to derive respiration rate.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Respiration Rate from Three-Dimensional Acceleration Data Based on Body Sensor Network

Liu

Guo

Zhu

et al. 2011

Telemedicine and e-Health

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Respiratory monitoring is widely used in clinical and healthcare practice to detect abnormal cardiopulmonary function during ordinary and routine activities. There are several approaches to estimate respiratory rate, including accelerometer(s) worn on the torso that are capable of sensing the inclination changes due to breathing. In this article, we present an adaptive band-pass filtering method combined with principal component analysis to derive the respiratory rate from threedimensional acceleration data, using a body sensor network platform previously developed by us. In situ experiments with 12 subjects indicated that our method was capable of offering dynamic respiration rate estimation during various body activities such as sitting, walking, running, and sleeping. The experimental studies also suggested that our frequency spectrum-based method was more robust, resilient to motion artifact, and therefore outperformed those algorithms primarily based on spatial acceleration information.

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Section: Introductionmentioning

confidence: 99%

Estimation of Respiration Rate from Three-Dimensional Acceleration Data Based on Body Sensor Network

Liu

Guo

Zhu

et al. 2011

Telemedicine and e-Health

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“…Quite recently, researchers investigated the performance of radars for monitoring vital signs as heartbeat or breathing [3]. At first, the application field has been prevalently the biomedical engineering: to exploit noncontact measurement method that assures a more comfortable analysis for human patient, avoiding the electrodes applied on the skin.…”

Section: People Buried Under Debrismentioning

confidence: 99%

Technical survey about available technologies for detecting buried people under rubble or avalanches

Ferrara

2015

WIT Transactions on the Built Environment

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Among all activities carried out in disaster scenarios, such as collapsed buildings, earthquakes, and avalanches, the detection and rescue of buried or trapped people have the priority. The paper aims at presenting the progress in the technological development of electronic devices and systems used to detect people buried under rubbles or avalanches. Many technologies realize detection, but only electromagnetic ones assure best results in terms of speed and accuracy of a relief, working also in a noisy environment. We can divide the methodologies using electromagnetic propagation in the three main. One is based on detection of active or passive electronic devices carried by the victim; the second one detects the body of a person as perturbation of the backscattered electromagnetic wave, due to dielectric discontinuity in the medium; the third case is based on the detection of vital signs. Both last two methodologies can be suitable for detecting people trapped under rubbles that can be free to move, also partially. More frequently, a buried person is motionless, because he is unconscious or the ruins block him. Consequently, the detection of vital signs, such as heartbeat or breathing, is the unique possible only. Performances and limits of each method is presented in the article, together with possible innovations.

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“…The next examples were monitoring of the elderly, infants and also animals using a microwave radar, especially focused respiratory monitoring (Li et al, 2009). …”

Section: Elderly Carementioning

confidence: 99%