Non-contact detection of myocardium’s mechanical activity by ultrawideband RF-radar and interpretation applying electrocardiography

Abstract

Electromagnetic waves can propagate through the body and are reflected at interfaces between materials with different dielectric properties. Therefore the reason for using ultrawideband (UWB) radar for probing the human body in the frequency range from 100 MHz up to 10 GHz is obvious and suggests an ability to monitor the motion of organs within the human body as well as obtaining images of internal structures. The specific advantages of UWB sensors are high temporal and spatial resolutions, penetration into object, low integral power, and compatibility with established narrowband systems. The sensitivity to ultralow power signals makes them suitable for human medical applications including mobile and continuous noncontact supervision of vital functions. Since no ionizing radiation is used, and due to the ultralow specific absorption rate applied, UWB techniques permit noninvasive sensing with no potential risks. This research aims at the synergetic use of UWB sounding combined with magnetic resonance imaging (MRI) to gain complementary information for improved functional diagnosis and imaging, especially to accelerate and enhance cardiac MRI by applying UWB radar as a noncontact navigator of myocardial contraction. To this end a sound understanding of how myocardial's mechanic is rendered by reflected and postprocessed UWB radar signals must be achieved. Therefore, we have executed the simultaneous acquisition and evaluation of radar signals with signals from a high-resolution electrocardiogram. The noncontact UWB illumination was done from several radiographic standard positions to monitor selected superficial myocardial areas during the cyclic physiological myocardial deformation in three different respiratory states. From our findings we could conclude that UWB radar can serve as a navigator technique for high and ultrahigh field magnetic resonance imaging and can be beneficial preserving the high resolution capability of this imaging modality. Furthermore it can potentially be used to support standard electrocardiography (ECG) analysis by complementary information where sole ECG analysis fails, e.g., electromechanical dissociation.

ultraMEDIS – Ultra-Wideband Sensing in Medicine

“…The anticipated potentials of this technique are (i) a contactless measuring principle for better patient safety and comfort, thus streamlining the clinical workflow, (ii) concurrent monitoring of a variety of body movements, (iii) direct relation to tissue mechanics [68], (iv) direct tracking of the temporal evolution of inner body landmarks, and (v) absence of any interferences of the UWB radar signals with the MR measurement if MR compatible designed UWB antennas are applied, (s. Section 2.3.3). The decomposition of physiological signatures in UWB radar data is the main challenge of this approach and a prerequisite for a reliable tracking of landmarks within the human body suitable for MRI gating.…”

“…For such a layered arrangement, the reflection coefficient () can be calculated recursively. In this manner, the response of (, t) to the variation of a certain internal interface can be analyzed [68], [73]. We simulated the physiological event by variations of (, t), which is done by a sinusoidal oscillation of the white matter.…”

“…We started our multi-channel UWB radar development with the single module device enabling us to add a second receiver (Rx) antenna, oriented towards the left-anterior oblique direction [68] (Fig. 33.a), to the existing Rx and Tx antennas facing the antero-posterior direction.…”

“…Stand-alone UWB radar enables the detection of cardiac activities by different illumination conditions as shown in [68] for the radiographic standard position. The illumination of the heart from only one side at a time, like the frontal direction for motion detection as depicted in Fig.…”

Super-resolution spectral estimation in short-time non-contact vital sign measurement

“…Various systems have been designed and validated these years, [4][5][6][7][8][9][10] While the specific signal processing algorithm inside the system attracts little attention. The signal processing of non-contact vital sign measurement can be formulated as a spectral estimation problem, 11 and the existing algorithms are mainly based on discrete Fourier transform (DFT).…”