Mari Zakrzewski

Wireless, Multipurpose In-Home Health Monitoring Platform: Two Case Trials

We propose a general purpose home area sensor network and monitoring platform that is intended for e-Health applications, ranging from elderly monitoring to early homecoming after a hospitalization period. Our monitoring platform is multipurpose, meaning that the system is easily configurable for various user needs and is easy to set up. The system could be temporarily rented from a service company by, for example, hospitals, elderly service providers, specialized physiological rehabilitation centers, or individuals. Our system consists of a chosen set of sensors, a wireless sensor network, a home client, and a distant server. We evaluated our concept in two initial trials: one with an elderly woman living in sheltered housing, and the other with a hip surgery patient during his rehabilitation phase. The results prove the functionality of the platform. However, efficient utilization of such platforms requires further work on the actual e-Health service concepts.

Comparison of Center Estimation Algorithms for Heart and Respiration Monitoring With Microwave Doppler Radar

Microwave doppler radar offers significant improvements for unobtrusive heart and respiration measurement. Radar monitoring enables non-contact measurement, through clothing, of heart and respiration rate, which is desired in several applications ranging from medical sleep laboratory measurements to home health care measurements and stress monitoring. The use of high frequency radar (>; 10 GHz) instead of lower frequencies (~2.4 GHz) increases the signal-to-noise-ratio of the signal and enables the utilization of commercial radar modules. However, if high frequency radar is used, linear combining of quadrature radar channels is inadequate. Instead, a nonlinear channel combining algorithm is needed. The combining can be performed with an arctangent function if center, amplitude error, and phase error are estimated accurately and corrected. In this paper, we show that the Levenberg-Marquardt (LM) center estimation algorithm outperforms the state-of-the-art center estimation algorithm precision-wise and is computationally less complex. The simulated results show that the root mean squared error with the LM method is always less than 1%, while it is around 5%-13% with the compared method, depending on the breathing signal model used. In addition, the computational complexity of the LM method stays almost constant as the size of the data set increases, whereas with the reference method, it increases exponentially. In this paper, the LM method is validated both with simulations and with real data.

Data-Based Quadrature Imbalance Compensation for a CW Doppler Radar System

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%.

Quadrature Imbalance Compensation With Ellipse-Fitting Methods for Microwave Radar Physiological Sensing

Accurate displacement measurement using quadrature Doppler radar requires amplitudes and phase imbalance compensation. Previously, this imbalance calibration has required cumbersome hardware modifications and thus can only be performed in a laboratory setting. Recently, a data-based method that does not require hardware modifications has been proposed. This simplifies the calibration process and allows the calibration to be performed on-site periodically. The method is called ellipse fitting. In this paper, the different factors affecting imbalance estimation accuracy, namely, arc length, initial phase angle, and noise level were thoroughly investigated. The Levenberg-Marquardt (LM) algorithm is proposed for the first time to increase the estimation accuracy as compared to the previously suggested algebraic fitting. Comprehensive simulations and experimental data show that the algebraic fitting method results in biased estimates. The proposed LM method has also been demonstrated to be more robust to noise, varying arc lengths, and different initial angles. The LM method reaches sufficient imbalance estimation accuracy with an arc length of 40% and a noise level of 1.5%.

UUTE Home Network for Wireless Health Monitoring

This paper presents a home sensor network for wireless health monitoring, including a wireless sensor network, client for controlling the sensor network, and a data storage server. A common software and hardware microcontroller-sensor interface was defined to enable joint use of sensor technologies developed in three different projects. IEEE 802.15.4 RF-transceiver based radio-boards and ZigBee network software were designed and built, along with a simple sensor network software on top of the ZigBee stack, to implement the wireless sensor network. Both commercial and custom made sensors have been interfaced to the sensor network. A set-up consisting of four sensors was developed and tested in a real home environment. The architectural overview of the system and main technical design choices are presented.

Contactless and Unobtrusive Measurement of Heart Rate in Home Environment

Current technology trends, such as ubiquitous computing and calm technology, call for novel unobtrusive sensors. The commonly used heart rate monitoring techniques require direct contact to the patient which makes the patient well aware of the sensors. In this paper, a novel method for detecting the distance of an approaching patient and for measuring his or her heart rate with a microwave Doppler radar is presented. This enables a truly non-contact and unobtrusive measurement. In addition, the measurement can be performed even through thick clothing. Furthermore, the patient does not need to be aware of being monitored since the method enables measurement to be started automatically as the patient approaches the sensor

Utilization of wireless sensor network for health monitoring in home environment

The health care costs in developed countries are increasing fast due to the aging of the population. In-home monitoring of health is becoming more and more attractive both because of expected cost-savings and technical development of suitable measurement devices and wireless sensor networks. In this paper, we present on-going work about embedding health monitoring devices into ordinary homes. The developed system is targeted both for monitoring elderly and for monitoring rehabilitation after hospitalization period. The paper presents the utilized sensor network implementation, chosen set of sensors for the first test trial, as well as other design choices for the trial. In addition, further objectives about concentrating on one special case, the ubiquitous heart rate measurement, are discussed. Our objective is to install several non-contact heart rate monitors into a home environment. The designed system performed well during the trial. However, some issues, such as sensor addressing in WSN and user identification, will be better taken into account in the next trials.

Low-Temperature Solution Processable Electrodes for Piezoelectric Sensors Applications

Piezoelectric thin-film sensors are suitable for a wide range of applications from physiological measurements to industrial monitoring systems. The use of flexible materials in combination with high-throughput printing technologies enables cost-effective manufacturing of custom-designed, highly integratable piezoelectric sensors. This type of sensor can, for instance, improve industrial process control or enable the embedding of ubiquitous sensors in our living environment to improve quality of life. Here, we discuss the benefits, challenges and potential applications of piezoelectric thin-film sensors. The piezoelectric sensor elements are fabricated by printing electrodes on both sides of unmetallized poly(vinylidene fluoride) film. We show that materials which are solution processable in low temperatures, biocompatible and environmental friendly are suitable for use as electrode materials in piezoelectric sensors.

Noncontact Respiration Monitoring During Sleep With Microwave Doppler Radar

This paper demonstrates the measurement of respiration waveform during sleep with a noncontact radar sensor. Instead of measuring only the respiration rate, the methods that allow monitoring the absolute respiration displacement were studied. Absolute respiration displacement can in theory be measured with a quadrature microwave Doppler radar sensor and using the nonlinear demodulation as the channel combining method. However, in this paper, relative respiration displacement measures were used as a reference. This is the first time that longer data sets have been analyzed successfully with the nonlinear demodulation method. This paper consists of whole-night recordings of three patients in an uncontrolled environment. The reference respiration data were obtained from a full polysomnography recorded simultaneously. The feasibility of the nonlinear demodulation in a real-life setting has been unclear. However, this paper shows that it is successful most of the time. The coverage of successfully demodulated radar data was ~58%-78%. The use of the nonlinear demodulation is not possible in the following cases: 1) if the chest wall displacement is too small compared with the wavelength of the radar; 2) if the radar data do not form an arc-like shape in the I Q-plot; or 3) if there are large movement artifacts present in the data. Both in academic literature and in commercial radar devices, the data are processed based on the presumption that it forms either an arc or a line in the I Q-plot. Our measurements show that the presumption is not always valid.

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

With a microwave radar, chest wall movements originating from cardiac and respiratory activity can be recorded non-contactly. A major challenge is how to separate the desired low-amplitude cardiac signal from large-amplitude artifacts, such as respiration. Commonly, the separation is performed with a narrow band-pass filter. This causes the signal edges to be rounded, which complicates the accurate timing estimation in the heart rate variability (HRV) analysis. In addition, the harmonics of the respiration signal might fall into the same frequency spectrum as the cardiac signal. In this study, we recorded data with two radars and studied signal separation using a complex-valued Independent Component Analysis (ICA). After ICA, the respiratory signal is greatly attenuated, although still present, in two of the independent components (ICs). However, respiration harmonics are reduced as well, and thus, the residual respiratory signal can be removed by filtering.