Separating respiration artifact in microwave doppler radar heart monitoring by Independent Component Analysis

Zakrzewski, Mari; Vanhala, Jukka

doi:10.1109/icsens.2010.5690538

Cited by 14 publications

(4 citation statements)

References 13 publications

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“…In the case of radar signals, ICA can be performed either in the time domain, or in the frequency domain [ 42 , 43 , 44 , 45 ]. In our data processing chain, we have opted for the frequency-domain ICA, applied to the calibrated data

per T x /R x couple at each vertical scan position H n .…”

Section: Methodsmentioning

confidence: 99%

On-Site Validation of a Microwave Breast Imaging System, before First Patient Study

Fasoula¹,

Duchesne²,

Cano³

et al. 2018

Diagnostics

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This paper presents the Wavelia microwave breast imaging system that has been recently installed at the Galway University Hospital, Ireland, for a first-in-human pilot clinical test. Microwave breast imaging has been extensively investigated over the last two decades as an alternative imaging modality that could potentially bring complementary information to state-of-the-art modalities such as X-ray mammography. Following an overview of the main working principles of this technology, the Wavelia imaging system architecture is presented, as are the radar signal processing algorithms that are used in forming the microwave images in which small tumors could be detectable for disease diagnosis. The methodology and specific quality metrics that have been developed to properly evaluate and validate the performance of the imaging system using complex breast phantoms that are scanned at controlled measurement conditions are also presented in the paper. Indicative results from the application of this methodology to the on-site validation of the imaging system after its installation at the hospital for pilot clinical testing are thoroughly presented and discussed. Given that the imaging system is still at the prototype level of development, a rigorous quality assessment and system validation at nominal operating conditions is very important in order to ensure high-quality clinical data collection.

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per T x /R x couple at each vertical scan position H n .…”

Section: Methodsmentioning

confidence: 99%

On-Site Validation of a Microwave Breast Imaging System, before First Patient Study

Fasoula¹,

Duchesne²,

Cano³

et al. 2018

Diagnostics

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show abstract

“…There is also another non-contact vital signs monitoring technique using radar sensors [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. The advantage of radar-based heart rate monitoring is that patients do not need to take off clothes and put on electrodes, which is convenient, and patients do not need to worry about privacy issues.…”

Section: Introductionmentioning

confidence: 99%

“…Principal component analysis (PCA) was applied in [ 21 ] to remove the static noise and recover vital signals [ 22 ]. Two CW radars systems in [ 23 ] apply ICA to attenuate the breathing effect for heartbeat signal recovering. In [ 32 ] ICA-JADE and direction of arrival techniques were used to obtain the respiration rate of multiple people.…”

Section: Introductionmentioning

confidence: 99%

Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors

Ebrahim

Hasan

et al. 2021

Sensors

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Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing: (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.

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“…Owing to the lack of range resolution, its output signal represents a superposition of the motion of all objects within the beam of the radar antenna. Nevertheless, one is able to separate various types of motions if their time histories are sufficiently different [2][3][4]. However, in many cases, (e.g.…”

Section: Introductionmentioning

confidence: 99%

M‐sequence‐based ultra‐wideband sensor network for vitality monitoring of elders at home

Sachs

Herrmann

2015

IET Radar, Sonar & Navigation

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The western societies are increasingly faced with the challenges of enabling a self-determined and safe life for a growing number of elderly people. Remote monitoring of vitality is an important tool for health risk mitigation but many of the current methods either deliver only infrequent information or require conscious cooperation of the senior. The authors propose an ultrawideband (UWB) radio sensor network based on M-sequence technology specifically designed for the vitality monitoring of persons living alone. It uses the frequency band in the range from 6 to 8.5 GHz (electronic communications committee (ECC)-band), and provides precise localisation, captures breathing motion during rests, can be used for fall detection and allows the extraction of gait features. The sensor network can be installed in common living spaces. It operates continuously in the background without any user interaction. Vitality monitoring by radar sensors is based on motion detection and tracking. This poses some challenges to radar devices because of the harsh multi-path conditions in apartments. This study discusses these challenges, illustrates how to meet them and gives examples for vitality features which can be extracted from UWB-radar data.

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Separating respiration artifact in microwave doppler radar heart monitoring by Independent Component Analysis

Cited by 14 publications

References 13 publications

On-Site Validation of a Microwave Breast Imaging System, before First Patient Study

On-Site Validation of a Microwave Breast Imaging System, before First Patient Study

Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors

M‐sequence‐based ultra‐wideband sensor network for vitality monitoring of elders at home

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