Noninvasive Respiration Monitoring of Different Sleeping Postures Using an RF Sensor

Resuli, Nuerzati; Skubic, Marjorie; Myungki, Jung

doi:10.1109/bibm52615.2021.9669669

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…Physiological motion sensing has been demonstrated below 6 GHz using either dedicated radar systems or by leveraging WiFi equipment and signals. Dedicated radar systems have been used to monitor a wide range of human physiological activity, including respiration and heart rate, respiratory tidal volume, and respiratory sleep disorders [9], [10], [11], [12], [13], [14], [15], [16], [17]. These systems typically employ custom-designed continuous wave (CW) or frequencymodulated continuous wave (FMCW) radar architectures or utilize ultra-wideband (UWB) radar systems.…”

Section: A Physiological Sensing Below 6 Ghzmentioning

confidence: 99%

Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems

et al. 2023

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Wireless communications systems provide channel state information (CSI), which can be used to characterize the physical propagation environment. The small physiological motion of human subjects in that environment, such as that associated with respiration, can modulate the CSI, thus allowing wireless physiological sensing through which a communications system detects and monitors cardiopulmonary motion. NextG millimeter-wave communications systems present even greater opportunities for wireless physiological sensing due to the advantages of small wavelength and high directionality. But challenges also arise due to the multipath effect and phase aliasing caused by larger-than-wavelength motion displacement. This work introduces a comprehensive mathematical CSI model to accurately characterize physiological motion captured by the amplitude and phase of the CSI of a millimeter-wave communications system. The model allows for the interpretation of intricate CSI pattern variations to avoid aliasing error and has been validated with experiments involving both parametric measures conducted with a robotic mover and respiration rate measurements for human subjects. In all cases, rate measurements could be consistently resolved within 10%, or 0.02 Hz, demonstrating the potential for incorporating physiological sensing in NextG millimeter-wave communications systems.

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Section: A Physiological Sensing Below 6 Ghzmentioning

confidence: 99%

Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems

et al. 2023

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“…By monitoring the small movements of the chest, radar systems can detect vital signs such as heart rate ( 143) and respiration rate. (144) Breathing and location can be used to monitor sleep quality. (145) The radar system can be installed on the wall or above the person being monitored.…”

Section: Radarmentioning

confidence: 99%

Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: A scoping review

Xu,

Smaling,

Schoones

et al. 2023

Preprint

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Background Discomfort and distressing symptoms are common at the end of life, while people in this stage are often no longer able to express themselves. Technologies may aid clinicians in detecting and treating these symptoms to improve end-of-life care. This review provides an overview of noninvasive monitoring technologies that may be applied to persons with limited communication at the end of life to identify discomfort or distressing symptoms. Methods A systematic search was performed in nine databases, and experts were consulted. Manuscripts were included if they were written in English, Dutch, German, French, Japanese or Chinese, if the monitoring technology measured discomfort or distressing symptoms, was noninvasive, could be continuously administered for 4 hours and was potentially applicable for bed-ridden people. The screening was performed by two researchers independently. Information about the technology, its clinimetrics (validity, reliability, sensitivity, specificity, responsiveness), acceptability, and feasibility were extracted. Results Of the 3,414 identified manuscripts, 229 met the eligibility criteria. A variety of monitoring technologies were identified, including actigraphy, brain activity monitoring, electrocardiography, electrodermal activity monitoring, surface electromyography, incontinence sensors, multimodal systems, and noncontact monitoring systems. The main symptoms monitored by these technologies were sleep, level of consciousness, risk of pressure ulcers, urinary incontinence, agitation, and pain. For the end-of-life phase, brain activity monitors could be helpful and acceptable to monitor the level of consciousness during palliative sedation. However, no manuscripts have reported on the clinimetrics, feasibility, and acceptability of the other technologies for the end-of-life phase. Conclusions Noninvasive monitoring technologies are available to measure common symptoms at the end of life. Future research should evaluate the quality of evidence provided by existing studies and investigate the feasibility, acceptability, and usefulness of these technologies in the end-of-life setting. Guidelines for studies on healthcare technologies should be better implemented and further developed.

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Combating Interference for Robust and Accurate Heart Rate Variability Monitoring via Millimeter-Wave Radar

Zhou

Shi

et al. 2022

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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Noninvasive Respiration Monitoring of Different Sleeping Postures Using an RF Sensor

Cited by 8 publications

References 15 publications

Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems

Physiological Motion Sensing via Channel State Information in NextG Millimeter-Wave Communications Systems

Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: A scoping review

Combating Interference for Robust and Accurate Heart Rate Variability Monitoring via Millimeter-Wave Radar

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