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.Index Terms-Biomedical signal processing, Doppler radar measurement, non-contact heart and respiration measurement, physiological monitoring, remote sensing.

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The ongoing revolution of touch‐based user interfaces sets new requirements for touch panel technologies, including the need to operate in a wide range of environments. Such touch panels need to endure moisture and sunlight. Moreover, they often need to be curved or flexible. Thus, there is a need for new technologies suitable, for example, for home appliances used in the kitchen or the bathroom, automotive applications, and e‐paper. In this work, the development of transparent and flexible touch panels for moist environments is reported. A piezoelectric polymer, poly(vinylidene difluoride) (PVDF), is used as a functional substrate material. Transparent electrodes are fabricated on both sides of a PVDF film using a graphene‐based ink and spray coating. The excellent performance of the touch panels is demonstrated in moist and underwater conditions. Also, the transparent device shows very small pyroelectric response to radiative heating in comparison to a non‐transparent device. Solution processable electrode materials in combination with functional substrates allow the low‐cost and high‐throughput manufacturing of touch panels using printing technologies.

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.

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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%.

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.