The Experts below are selected from a list of 21876 Experts worldwide ranked by ideXlab platform
Olga Boriclubecke - One of the best experts on this subject based on the ideXlab platform.
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wireless sleep apnea detection using continuous wave quadrature Doppler Radar
2020Co-Authors: Mehran Baboli, Aditya Singh, Olga Boriclubecke, Bruce Soll, Victor LubeckeAbstract:A non-contact and non-invasive physiological Radar monitoring system (PRMS) is introduced. The system is based on motion detection using quadrature microwave Doppler Radar, eliminating the need to place sensors on the body. An algorithm was designed to perform real-time actigraphy and sleep apnea detection. The system was validated with clinical polysomnography (PSG) in a sleep study facility on ten consented volunteers with known obstructive sleep apnea. Data obtained from both PRMS and clinical PSG systems were rated by a sleep technician and show an excellent agreement in the detected apnea and hypopnea events. The apnea-hypopnea events were distinguished with an overall sensitivity of 86%, the specificity of 91% and accuracy of 92%.
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Doppler Radar techniques for accurate respiration characterization and subject identification
2018Co-Authors: Ashikur Rahman, Victor Lubecke, Olga Boriclubecke, Jan H Prins, Takuya SakamotoAbstract:A low distortion dc coupled CW Radar system with high signal to noise ratio is capable of accurate representation of respiration in human subjects. We propose to test the hypothesis that a non-contact physiological Radar monitoring system which measures and characterizes subtle body kinematics, can be made to resolve patterns accurately enough to recognize an individual’s identity. This paper investigates a technique to attain the requisite signal to noise ratio by dc offset management. Detailed exploration of the unique features in respiration signals using noncontact CW Doppler Radar are presented. A proposed dynamic segmentation technique allowed detection of various unique features and patterns. KMN nearest neighbor and majority vote algorithms were implemented in software for this Radar-based unique identification system. The system was tested and validated for six test subjects with 95% success rate. Fractal analysis of minor components of linearly demodulated Radar signal was also presented for additional improvement in accuracy. This paper is believed to be significant as Radar unique identification of human subjects has many potential applications, including security, health monitoring, IoT applications, and virtual reality.
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radius correction technique for Doppler Radar noncontact periodic displacement measurement
2017Co-Authors: Olga BoriclubeckeAbstract:Noncontact physiological monitoring using Doppler Radar has been studied extensively. Most commonly, continuous-wave (CW) quadrature Doppler Radar is used to measure cardiopulmonary rates. Accurate displacement measurement can provide physiological waveform recovery, which may enable tidal volume and pulse pressure estimation. In this paper, we propose a calibration technique that enables high-accuracy millimeter-order periodic displacement measurements using CW quadrature Doppler Radar. Theoretical analysis of center estimation error and its propagation effect are presented. Simulations are performed to show how noise and limited arc length affect error and affect the accuracy of center estimation, as well as improvements after calibration. A high-precision linear stage was employed to create periodic motion for evaluating the performance of calibration technique. Experimental results demonstrate that the proposed calibration technique enables displacement measurement with accuracy within tens of micrometers.
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Doppler Radar sensor for occupancy monitoring
2013Co-Authors: Ehsan Yavari, Victor Lubecke, Olga BoriclubeckeAbstract:This paper investigates the use of Doppler Radar sensor for occupancy monitoring. The feasibility of true presence is explored with Doppler Radar occupancy sensors to overcome the limitations of the common occupancy sensors. The common occupancy sensors are more of a motion sensor than a presence detector. Existing cost effective off the shelf System-on-Chip CC2530 RF transceiver is used for developing the radio. The transmitter sends continuous wave signal at 2.405 GHz. Different levels of activity is detected by post-processing sensor signals. Heart and respiratory signals are extracted in order to improve stationary subject detection.
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a review on recent advances in Doppler Radar sensors for noncontact healthcare monitoring
2013Co-Authors: Changzhi Li, Victor Lubecke, Olga BoriclubeckeAbstract:This paper reviews recent advances in biomedical and healthcare applications of Doppler Radar that remotely detects heartbeat and respiration of a human subject. In the last decade, new front-end architectures, baseband signal processing methods, and system-level integrations have been proposed by many researchers in this field to improve the detection accuracy and robustness. The advantages of noncontact detection have drawn interests in various applications, such as energy smart home, baby monitor, cardiopulmonary activity assessment, and tumor tracking. While many of the reported systems were bench-top prototypes for concept verification, several portable systems and integrated Radar chips have been demonstrated. This paper reviews different architectures, baseband signal processing, and system implementations. Validations of this technology in a clinical environment will also be discussed.
Victor Lubecke - One of the best experts on this subject based on the ideXlab platform.
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wireless sleep apnea detection using continuous wave quadrature Doppler Radar
2020Co-Authors: Mehran Baboli, Aditya Singh, Olga Boriclubecke, Bruce Soll, Victor LubeckeAbstract:A non-contact and non-invasive physiological Radar monitoring system (PRMS) is introduced. The system is based on motion detection using quadrature microwave Doppler Radar, eliminating the need to place sensors on the body. An algorithm was designed to perform real-time actigraphy and sleep apnea detection. The system was validated with clinical polysomnography (PSG) in a sleep study facility on ten consented volunteers with known obstructive sleep apnea. Data obtained from both PRMS and clinical PSG systems were rated by a sleep technician and show an excellent agreement in the detected apnea and hypopnea events. The apnea-hypopnea events were distinguished with an overall sensitivity of 86%, the specificity of 91% and accuracy of 92%.
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Doppler Radar techniques for accurate respiration characterization and subject identification
2018Co-Authors: Ashikur Rahman, Victor Lubecke, Olga Boriclubecke, Jan H Prins, Takuya SakamotoAbstract:A low distortion dc coupled CW Radar system with high signal to noise ratio is capable of accurate representation of respiration in human subjects. We propose to test the hypothesis that a non-contact physiological Radar monitoring system which measures and characterizes subtle body kinematics, can be made to resolve patterns accurately enough to recognize an individual’s identity. This paper investigates a technique to attain the requisite signal to noise ratio by dc offset management. Detailed exploration of the unique features in respiration signals using noncontact CW Doppler Radar are presented. A proposed dynamic segmentation technique allowed detection of various unique features and patterns. KMN nearest neighbor and majority vote algorithms were implemented in software for this Radar-based unique identification system. The system was tested and validated for six test subjects with 95% success rate. Fractal analysis of minor components of linearly demodulated Radar signal was also presented for additional improvement in accuracy. This paper is believed to be significant as Radar unique identification of human subjects has many potential applications, including security, health monitoring, IoT applications, and virtual reality.
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noncontact Doppler Radar unique identification system using neural network classifier on life signs
2016Co-Authors: Ashikur Rahman, Ehsan Yavari, Victor Lubecke, Olga-boric LubeckeAbstract:A continuous-wave (CW) Doppler Radar-based unique-identification system has been studied. Experiments have been performed using a neural network based classifier to uniquely identify individuals based on the variation in their breathing energy, frequency and patterns captured by the Radar. Our work shows the possibility of non-contact unique identification where camera based system is not preferred. It is demonstrated that the system is capable of identifying individuals with more than 90% accuracy. This study also has impact on Radar-based breathing pattern classification for health diagnostics.
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a low if tag based motion compensation technique for mobile Doppler Radar life signs monitoring
2015Co-Authors: Ashikur Rahman, Ehsan Yavari, Victor Lubecke, Aditya Singh, Olga-boric LubeckeAbstract:This paper presents low IF techniques for noninvasive detection of vital signs from a mobile short-range Doppler Radar platform. Stationary continuous-wave Doppler Radar has been used for displacement measurement and vital signs detection. However, on a mobile platform, measurements become challenging due to motion artifacts induced by the platform. In this work, a complete compensated single transceiver Radar system for vital signs detection in the presence of platform movement is demonstrated. In earlier related work, motion of the Radar module was determined using cameras installed on site. However, practical mobile monitoring applications would preclude the use of such stationary cameras. In this work, an RF tag and a low IF Radar architecture with an adaptive noise cancellation technique is employed to extract desired vital signs motion information even in the presence of large platform motion.
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Doppler Radar sensor for occupancy monitoring
2013Co-Authors: Ehsan Yavari, Victor Lubecke, Olga BoriclubeckeAbstract:This paper investigates the use of Doppler Radar sensor for occupancy monitoring. The feasibility of true presence is explored with Doppler Radar occupancy sensors to overcome the limitations of the common occupancy sensors. The common occupancy sensors are more of a motion sensor than a presence detector. Existing cost effective off the shelf System-on-Chip CC2530 RF transceiver is used for developing the radio. The transmitter sends continuous wave signal at 2.405 GHz. Different levels of activity is detected by post-processing sensor signals. Heart and respiratory signals are extracted in order to improve stationary subject detection.
Ehsan Yavari - One of the best experts on this subject based on the ideXlab platform.
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noncontact Doppler Radar unique identification system using neural network classifier on life signs
2016Co-Authors: Ashikur Rahman, Ehsan Yavari, Victor Lubecke, Olga-boric LubeckeAbstract:A continuous-wave (CW) Doppler Radar-based unique-identification system has been studied. Experiments have been performed using a neural network based classifier to uniquely identify individuals based on the variation in their breathing energy, frequency and patterns captured by the Radar. Our work shows the possibility of non-contact unique identification where camera based system is not preferred. It is demonstrated that the system is capable of identifying individuals with more than 90% accuracy. This study also has impact on Radar-based breathing pattern classification for health diagnostics.
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a low if tag based motion compensation technique for mobile Doppler Radar life signs monitoring
2015Co-Authors: Ashikur Rahman, Ehsan Yavari, Victor Lubecke, Aditya Singh, Olga-boric LubeckeAbstract:This paper presents low IF techniques for noninvasive detection of vital signs from a mobile short-range Doppler Radar platform. Stationary continuous-wave Doppler Radar has been used for displacement measurement and vital signs detection. However, on a mobile platform, measurements become challenging due to motion artifacts induced by the platform. In this work, a complete compensated single transceiver Radar system for vital signs detection in the presence of platform movement is demonstrated. In earlier related work, motion of the Radar module was determined using cameras installed on site. However, practical mobile monitoring applications would preclude the use of such stationary cameras. In this work, an RF tag and a low IF Radar architecture with an adaptive noise cancellation technique is employed to extract desired vital signs motion information even in the presence of large platform motion.
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Doppler Radar sensor for occupancy monitoring
2013Co-Authors: Ehsan Yavari, Victor Lubecke, Olga BoriclubeckeAbstract:This paper investigates the use of Doppler Radar sensor for occupancy monitoring. The feasibility of true presence is explored with Doppler Radar occupancy sensors to overcome the limitations of the common occupancy sensors. The common occupancy sensors are more of a motion sensor than a presence detector. Existing cost effective off the shelf System-on-Chip CC2530 RF transceiver is used for developing the radio. The transmitter sends continuous wave signal at 2.405 GHz. Different levels of activity is detected by post-processing sensor signals. Heart and respiratory signals are extracted in order to improve stationary subject detection.
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data based quadrature imbalance compensation for a cw Doppler Radar system
2013Co-Authors: Aditya Singh, Ehsan Yavari, Victor Lubecke, Xiaomeng Gao, Mari Zakrzewski, Xi Hang Cao, Olga BoriclubeckeAbstract:A method for quadrature imbalance compensation in direct-conversion quadrature Doppler Radar systems, based on data obtained using a mechanical target and an ellipse fit method, is reported. The proposed method can be used with different architectures of Doppler Radar and eliminates the need to modify the Radar in order to perform imbalance measurements. A mechanical target was used to provide sufficient motion to create a significant segment of an ellipse in the in-phase/quadrature trace to obtain correction factors with high accuracy. Parametric simulations were performed to analyze the accuracy of this technique in the presence of varying noise and target displacements. This method is compared with an existing phase-shifter-based imbalance computation technique for the measurement of known displacements and is shown to give consistent and more accurate results. Experimental data, consistent with simulations, demonstrates that accurate correction is obtained with 65% of the ellipse, resulting in a displacement error of less than 6%.
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cancellation of unwanted Doppler Radar sensor motion using empirical mode decomposition
2013Co-Authors: Isar Mostafanezhad, Ehsan Yavari, Victor Lubecke, Olga Boriclubecke, Danilo P MandicAbstract:The operation of microwave Doppler Radar for sensing physiological motion signals is heavily compromised under sensor motion. To that end, we investigate the feasibility of applying empirical mode decomposition method in this context, and demonstrate its effectiveness in removing sensor motion artifacts. This method is shown to be effective in canceling unwanted sensor motion with precision sufficient to enable accurate heart rate extraction. Theoretical analysis and simulation results illustrate the potential of the proposed approach for a wide range of frequency separation and amplitude ratios of physiological signals and motion artifacts. Experimental results confirm that separation success is not very sensitive to amplitude ratio. A heart rate is extracted with RMSE within 1 beat per minute even in the presence of mechanical motion and order of magnitude larger in amplitude than that of the heart signal.
Aditya Singh - One of the best experts on this subject based on the ideXlab platform.
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wireless sleep apnea detection using continuous wave quadrature Doppler Radar
2020Co-Authors: Mehran Baboli, Aditya Singh, Olga Boriclubecke, Bruce Soll, Victor LubeckeAbstract:A non-contact and non-invasive physiological Radar monitoring system (PRMS) is introduced. The system is based on motion detection using quadrature microwave Doppler Radar, eliminating the need to place sensors on the body. An algorithm was designed to perform real-time actigraphy and sleep apnea detection. The system was validated with clinical polysomnography (PSG) in a sleep study facility on ten consented volunteers with known obstructive sleep apnea. Data obtained from both PRMS and clinical PSG systems were rated by a sleep technician and show an excellent agreement in the detected apnea and hypopnea events. The apnea-hypopnea events were distinguished with an overall sensitivity of 86%, the specificity of 91% and accuracy of 92%.
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a low if tag based motion compensation technique for mobile Doppler Radar life signs monitoring
2015Co-Authors: Ashikur Rahman, Ehsan Yavari, Victor Lubecke, Aditya Singh, Olga-boric LubeckeAbstract:This paper presents low IF techniques for noninvasive detection of vital signs from a mobile short-range Doppler Radar platform. Stationary continuous-wave Doppler Radar has been used for displacement measurement and vital signs detection. However, on a mobile platform, measurements become challenging due to motion artifacts induced by the platform. In this work, a complete compensated single transceiver Radar system for vital signs detection in the presence of platform movement is demonstrated. In earlier related work, motion of the Radar module was determined using cameras installed on site. However, practical mobile monitoring applications would preclude the use of such stationary cameras. In this work, an RF tag and a low IF Radar architecture with an adaptive noise cancellation technique is employed to extract desired vital signs motion information even in the presence of large platform motion.
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small scale displacement measurement with passive harmonic rf tag using Doppler Radar
2013Co-Authors: Xiaomeng Gao, Aditya Singh, Olga Boriclubecke, Victor LubeckeAbstract:Measurement accuracy of the displacement from human cardiopulmonary activities has potential in predicting physiological information for the purpose of biomedical remote sensing and non-contact monitoring. In this paper, an RF frequency doubling tag was used for detecting small displacement with high accuracy. A heterodyne and a homodyne quadrature Radar receiving systems were used to detect small scale tag motion and non-tagged motion from a distance, respectively. Arctangent demodulation algorithm and imbalance compensation technique were applied to the raw Radar data for displacement estimation. Simulation and experimental results were compared, indicating that by using the frequency doubling tag, a better accuracy can be achieved for small displacement estimation with Doppler Radar.
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data based quadrature imbalance compensation for a cw Doppler Radar system
2013Co-Authors: Aditya Singh, Ehsan Yavari, Victor Lubecke, Xiaomeng Gao, Mari Zakrzewski, Xi Hang Cao, Olga BoriclubeckeAbstract:A method for quadrature imbalance compensation in direct-conversion quadrature Doppler Radar systems, based on data obtained using a mechanical target and an ellipse fit method, is reported. The proposed method can be used with different architectures of Doppler Radar and eliminates the need to modify the Radar in order to perform imbalance measurements. A mechanical target was used to provide sufficient motion to create a significant segment of an ellipse in the in-phase/quadrature trace to obtain correction factors with high accuracy. Parametric simulations were performed to analyze the accuracy of this technique in the presence of varying noise and target displacements. This method is compared with an existing phase-shifter-based imbalance computation technique for the measurement of known displacements and is shown to give consistent and more accurate results. Experimental data, consistent with simulations, demonstrates that accurate correction is obtained with 65% of the ellipse, resulting in a displacement error of less than 6%.
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detection sensitivity and power consumption vs operation modes using system on chip based Doppler Radar occupancy sensor
2012Co-Authors: Chenyan Song, Ehsan Yavari, Olga Boriclubecke, Aditya Singh, Victor LubeckeAbstract:A low cost, low power Doppler Radar occupancy sensor is developed by building a customized passive sensor node into a low power System-on-Chip (SoC) CC2530 RF transceiver. Experiment on the periodic moving mechanic target illustrates that this SoC based Doppler Radar sensor is able to accurately detect the motion of the target under CW, modulated CW and packet operation modes. The study on sensitivity and power consumption under these modes indicates the most cost efficiency and power efficiency can be achieved by operating the sensor under packet mode with an optimum output power level.
Jenshan Lin - One of the best experts on this subject based on the ideXlab platform.
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respiration rate measurement under 1 d body motion using single continuous wave Doppler Radar vital sign detection system
2016Co-Authors: Taesong Hwang, Jenshan LinAbstract:Random body movement (RBM) is one of the most challenging issues in non-contact vital sign detection using Doppler Radar technique. The large and irregular displacement of the human body could corrupt the vital sign signal and significantly degrade the accuracy of detection. Even the respiration rate (RR) sometimes cannot be measured accurately under RBM. In this paper, the characteristic of the frequency spectrum of the vital sign signal under body motion (the motion modulation effect) is analyzed. Based on that effect, an RR measurement method under one-dimensional (1-D) body motion is developed using only one non-contact continuous-wave (CW) Doppler Radar vital sign detection system. The direction of body motion is extracted along with the new position of the respiration peaks in the frequency spectrum and RR can be calculated. Simulations of the theory using a model of the vital sign detection system are performed, followed by experiments to verify the theory. Experiments are performed on an actuator and a human subject by only one 5.8-GHz non-contact CW vital sign detection system. Under large 1-D body motion that has a displacement 5–10 times larger than the respiratory displacement, the proposed method successfully measures RR with only 7.15% error.
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accurate Doppler Radar noncontact vital sign detection using the relax algorithm
2010Co-Authors: Jun Ling, Jenshan LinAbstract:We consider using a Doppler Radar for accurate noncontact vital sign detection. The Doppler Radar first captures and downconverts the wireless signal that is phase modulated by the physiological movements, and then identifies the human heartbeat and respiration rates by processing the baseband signal. When nonlinear Doppler phase modulation is employed to monitor vital signs without contact, one of the challenges that we encounter is the presence of undesired harmonic terms and intermodulations other than the sinusoids of interest. A spectral estimation algorithm is needed to accurately estimate the sinusoidal frequencies before identifying the heartbeat and respiration rates. The conventional periodogram cannot reliably separate the rich sinusoidal components since it suffers from smearing and leakage problems, particularly for the case of limited data samples. A parametric and cyclic optimization approach, referred to as the RELAX algorithm, is instead suggested to mitigate these difficulties. Both simulated and experimental results are provided to validate the superiority of using the RELAX algorithm for accurate noncontact vital sign detection.
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random body movement cancellation in Doppler Radar vital sign detection
2008Co-Authors: Changzhi Li, Jenshan LinAbstract:The complex signal demodulation and the arctangent demodulation are studied for random body movement cancellation in quadrature Doppler Radar noncontact vital sign detection. This technique can be used in sleep apnea monitor, lie detector, and baby monitor to eliminate the false alarm caused by random body movement. It is shown that if the dc offset of the baseband signal is accurately calibrated, both demodulation techniques can be used for random body movement cancellation. While the complex signal demodulation is less likely to be affected by a dc offset, the arctangent demodulation has the advantage of eliminating harmonic and intermodulation interference at high carrier frequencies. When the dc offset cannot be accurately calibrated, the complex signal demodulation is more favorable. Ray-tracing model is used to show the effects of constellation deformation and optimum/null detection ambiguity caused by the phase offset due to finite antenna directivity. Experiments have been performed using 4-7 GHz Radar to verify the theory.
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a ka band low power Doppler Radar system for remote detection of cardiopulmonary motion
2005Co-Authors: Yanming Xiao, Jenshan Lin, Olga Boriclubecke, Victor LubeckeAbstract:A low power Ka-band Doppler Radar that can detect human heartbeat and respiration signals is demonstrated. This Radar system achieves better than 80% detection accuracy at the distance of 2-m with 16-muW transmitted power. Indirect-conversion receiver architecture is chosen to reduce the DC offset and 1/f noise that can degrade signal-to-noise ratio and detection accuracy. In addition, the Radar has also demonstrated the capability of detecting acoustic signals
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a microwave radio for Doppler Radar sensing of vital signs
2001Co-Authors: Amy Droitcour, Victor Lubecke, Jenshan Lin, O BoriclubeckeAbstract:A microwave radio for Doppler Radar sensing of vital signs is described. This radio was developed using custom DCS1800/PCS1900 base station RFICs. It transmits a single tone signal, demodulates the reflected signal, and outputs a baseband signal. If the object that reflects the signal has periodic motion, the magnitude of the baseband output signal is directly proportional to the periodic displacement of the object. When the signal is reflected off a person's chest, this radio with appropriate baseband filters can detect heart and respiration rates from a distance as large as one meter from the target.
