FMCW radar for life-sign detection

Anitori, Laura; Jong, A. de; Nennie, Frans

doi:10.1109/radar.2009.4976934

Cited by 88 publications

(50 citation statements)

References 8 publications

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“…Past proposals use one of the following techniques: Doppler radar [17,16,15], WiFi [34,27], or ultra-wideband radar [48,14,7]. The key challenge in using wireless signals to extract vital signs is that any motion in the environment affects the signal.…”

Section: Related Workmentioning

confidence: 99%

“…Past proposals deal with this problem by ensuring that there is only one source of motion in the environment: namely, the vital signs of the monitored individual. Hence, their experimental setup has one person, who typically lies still in close proximity to the device [17,16,15,34,27,48,14,7,4].…”

Section: Related Workmentioning

confidence: 99%

“…6 We limit the experiments to distances of 8 m because the localization accuracy of FMCW-based systems for consumer applications drops beyond this range [6]. 7 We note that one of our subject has a significantly high heart rate of 115 beats/minute. We confirmed with the subject that this value, which was measured with the Alice PDx, is compatible with his medical records.…”

Section: Breathing Rate Accuracymentioning

confidence: 99%

See 2 more Smart Citations

Smart Homes that Monitor Breathing and Heart Rate

Adib

Mao

Kabelac

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

729

371

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The evolution of ubiquitous sensing technologies has led to intelligent environments that can monitor and react to our daily activities, such as adapting our heating and cooling systems, responding to our gestures, and monitoring our elderly. In this paper, we ask whether it is possible for smart environments to monitor our vital signs remotely, without instrumenting our bodies. We introduce Vital-Radio, a wireless sensing technology that monitors breathing and heart rate without body contact. Vital-Radio exploits the fact that wireless signals are affected by motion in the environment, including chest movements due to inhaling and exhaling and skin vibrations due to heartbeats. We describe the operation of Vital-Radio and demonstrate through a user study that it can track users' breathing and heart rates with a median accuracy of 99%, even when users are 8 meters away from the device, or in a different room. Furthermore, it can monitor the vital signs of multiple people simultaneously. We envision that Vital-Radio can enable smart homes that monitor people's vital signs without body instrumentation, and actively contribute to their inhabitants' well-being.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Breathing Rate Accuracymentioning

confidence: 99%

See 1 more Smart Citation

Smart Homes that Monitor Breathing and Heart Rate

Adib

Mao

Kabelac

et al. 2015

Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

729

371

View full text Add to dashboard Cite

show abstract

“…6,9,37 We refer the reader to Ref. Adib et al 6 for a detailed description of such methods, and summarize below the basic information relevant to this paper.…”

Section: Rf-based Sensingmentioning

confidence: 99%

Emotion recognition using wireless signals

2018

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This paper demonstrates a new technology that can infer a person's emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person's body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-theart emotion recognition systems that require a person to be hooked to an ECG monitor.

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“…능동형은 신호를 송신한 후 신체에 부딪혀 되돌아오는 수신 신호와의 비교를 통해 생체신호 를 검출한다. 이러한 대표적 구조는 도플러 효과를 이용 한 원거리(또는 근거리) 생체신호를 검출하기 위한 FM-CW, CW 레이더 등이 있다 [6]～ [9] . 반면, 수동형은 송신신 호 없이 신체와 센서 사이의 근접 전자기장의 변화를 이 용하여 호흡 및 심박 신호를 검출하였다 [10]～ [13] .…”

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Vital Sign Sensor Based on Second Harmonic Frequency Drift of Oscillator

Ku¹,

Hong²,

Lee³

et al. 2016

The Journal of Korean Institute of Electromagnetic Engineering

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In this paper, a vital sign sensor based on impedance variation of resonator is proposed to detect the respiration and heartbeat signals within near-field range as a function of the separation distance between resonator and subject. The sensor consists of an oscillator with a built-in planar type patch resonator, a diplexer for only pass the second harmonic frequency, amplifier, SAW filter, and RF detector. The cardiac activity of a subject such as respiration and heartbeat causes the variation of the oscillation frequency corresponding impedance variation of the resonator within near-field range. The combination of the second harmonic oscillation frequency deviation and the superior skirt frequency of the SAW filter enables the proposed sensor to extend twice detection range. The experimental results reveal that the proposed sensor placed 40 mm away from a subject can reliably detect respiration and heartbeat signals.

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FMCW radar for life-sign detection

Cited by 88 publications

References 8 publications

Smart Homes that Monitor Breathing and Heart Rate

Smart Homes that Monitor Breathing and Heart Rate

Emotion recognition using wireless signals

Vital Sign Sensor Based on Second Harmonic Frequency Drift of Oscillator

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