Noncontact Millimeter-Wave Real-Time Detection and Tracking of Heart Rate on an Ambulatory Subject

Mikhelson, Ilya V.; Lee, P.; Bakhtiari, Sasan; Elmer, Thomas W.; Katsaggelos, A.K.; Sahakian, Alan V.

doi:10.1109/titb.2012.2204760

Cited by 46 publications

(30 citation statements)

References 23 publications

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“…[12,13,14], and 94.0 GHz [15,16,17,18]. Among these studies, only a few [1,2,8] successfully measured the instantaneous heart rate, which would allow the assessment of heart-rate variability.…”

Section: Introductionmentioning

confidence: 99%

Accurate heartbeat monitoring using ultra-wideband radar

Sakamoto

Imasaka

Taki

et al. 2015

IEICE Electron. Express

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Abstract:We demonstrate an accurate remote measurement of heartbeats using an ultra-wideband radar system. Although most conventional systems use either continuous waves or impulse-radio systems for remote vital monitoring, continuous waves suffer from non-stationary clutters, while impulse-radio systems cannot detect heartbeats. Our ultra-wideband radar system has a moderate fractional bandwidth intermediate of these systems, resulting in both the suppression of clutters and high sensitivity in measuring accurate heart rates even in a dynamic environment. A simultaneous measurement of the vital signal of a participant employing the ultra-wideband radar and electrocardiography reveals the high accuracy of the radar system in measuring the heart rate varying over time. Keywords: ultra-wideband, radar, vital monitoring, heart rate Classification: Microwave and millimeter wave devices, circuits, and systems References

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Section: Introductionmentioning

confidence: 99%

Accurate heartbeat monitoring using ultra-wideband radar

Sakamoto

Imasaka

Taki

et al. 2015

IEICE Electron. Express

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“…It works by measuring slight color variations of the face that correspond to cardiac pulses. Meanwhile, others have focused on contactless sensing and wearable sensors [8] [9]. This chapter will first give an overview of traditional health monitoring sensors, followed by descriptions of a range of wearable sensors used in common mHealth applications.…”

Section: Introductionmentioning

confidence: 99%

Ubiquitous Health Monitoring: Integration of Wearable Sensors, Novel Sensing Techniques, and Body Sensor Networks

2015

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Abstract. Emergence of the Internet and widespread use of mobile computing have brought traditional eHealth beyond the boundary of the clinical setting, evolving to mHealth which is patient-centered and ubiquitous. Faced with the world's rapidly ageing population and its burden on the healthcare system, one of the intense areas of development in mHealth is continuous patient monitoring. It requires careful integration of wearable sensors and wireless body sensor networks. Unlike traditional ambulatory monitors, sensors for mHealth may appear in various forms, such as watches, jewelry, eyewear, and even smart garments. Recent work have focused on design for wearability, alternative sensing techniques, and mHealth-specific network topologies.

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“…[1][2][3][4] Their benefits compared to conventional methods, which require sensors in direct contact with the person investigated, are numerous and consist in the possibility of performing some investigations on patients with special problems (e.g., victims of burns) and in extending the monitoring of vital signals over longer periods of time (e.g., during sleep).…”

Section: Introductionmentioning

confidence: 99%

A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

Bechet

Mitran

Munteanu

2013

Review of Scientific Instruments

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Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

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Noncontact Millimeter-Wave Real-Time Detection and Tracking of Heart Rate on an Ambulatory Subject

Cited by 46 publications

References 23 publications

Accurate heartbeat monitoring using ultra-wideband radar

Accurate heartbeat monitoring using ultra-wideband radar

Ubiquitous Health Monitoring: Integration of Wearable Sensors, Novel Sensing Techniques, and Body Sensor Networks

A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

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