Showing papers by "Tom Torfs published in 2019"

Vital-sign monitoring and spatial tracking of multiple people using a contactless radar-based sensor

Abstract: Various medical systems exist for monitoring people in daily life, but they typically require the patient to wear a device, which can create discomfort and can limit long-term use. Contactless vital-sign monitoring would be preferable, but such technology is challenging to develop as it involves weak signals that need to be accurately detected within a practical distance, while being reliably distinguished from unwanted disturbance. Here, we show that a radar-based sensor can be used to monitor the individual vital signs (heartbeat and respiration) of multiple people in a real-world setting. The contactless approach, which does not require any body parts to be worn, uses two antennas (one transmitter and one receiver) and algorithms for target tracking and rejection of random body movements. As a result, it is robust against moderate random body movements (limb movements and desk work) and can keep track of individual people during vigorous movement (such as walking and standing up). A radar-based sensor can monitor the individual vital signs—heartbeat and respiration—of multiple people in a real-world setting, keeping track of individual people during vigorous movement.

A 400 GΩ Input-Impedance Active Electrode for Non-Contact Capacitively Coupled ECG Acquisition With Large Linear-Input-Range and High CM-Interference-Tolerance

Abstract: Electrocardiogram (ECG) is one of the major physiological vital signs and an effective monitoring method for patients with cardiovascular diseases. However, existing ECG recordings require a galvanic body contact, which is unpractical in daily life. This paper presents the design of an ECG chip that facilitates non-contact ECG recording through capacitive coupling. With the input impedance boosting techniques, as well as an active driven-right-leg (DRL) which boosts common-mode rejection ratio to 70 dB, the single-ended capacitive feedback active electrode (AE) achieves ultra-high input impedance of 400 GΩ ( ${\rm V}_{PP}$ ), and a high linear-input-range (220 m ${\rm V}_{PP}$ ). Implemented in 0.18 μ m 5V CMOS process, the prototype occupies an area of 1.23 mm2, and consumes 18 μ A and 13 μ A for the AE and DRL, respectively. Real life non-contact capacitively coupled ECG acquisition has been demonstrated, obtaining ECG waves and heart rate in the presence of motion artifacts as well as ambient interference.

Capacitive multi-electrode array with real-time electrode selection for unobtrusive ECG & BIOZ monitoring

Abstract: Capacitively-coupled ECG (ccECG) and bioimpedance (ccBIOZ) measurements are highly sensitive to motion artefacts. This limits their use in real-life situations. This work presents an array-based system for the simultaneous acquisition of ccECG and ccBIOZ, together with a quality-based electrode scanning approach for ccECG. This allows to increase the time coverage of contactless measurements in real-life situations and reduces the impact of artefacts. This solution was evaluated on a car seat and a mattress prototype. Results show the benefit of this combined array and algorithm approach: for every body position the algorithm was able to find more than one electrode combination providing high-quality ccECG. Night-long recordings were also performed, resulting in a mean time coverage of 72.5%.

Physiological Driver Monitoring Using Capacitively Coupled and Radar Sensors

Abstract: Unobtrusive monitoring of drivers’ physiological parameters is a topic gaining interest, potentially allowing to improve the performance of safety systems to prevent accidents, as well as to improve the driver’s experience or provide health-related services. In this article, two unobtrusive sensing techniques are evaluated: capacitively coupled sensing of the electrocardiogram and respiration, and radar-based sensing of heartbeat and respiration. A challenge for use of these techniques in vehicles are the vibrations and other disturbances that occur in vehicles to which they are inherently more sensitive than contact-based sensors. In this work, optimized sensor architectures and signal processing techniques are proposed that significantly improve the robustness to artefacts. Experimental results, conducted under real driving conditions on public roads, demonstrate the feasibility of the proposed approach. R peak sensitivities and positive predictivities higher than 98% both in highway and city traffic, heart rate mean absolute error of 1.02 bpm resp. 2.06 bpm in highway and city traffic and individual beat R-R interval 95% percentile error within ±27.3 ms are demonstrated. The radar experimental results show that respiration can be measured while driving and heartbeat can be recovered from vibration noise using an accelerometer-based motion reduction algorithm.

Digital Linear Discrete FMCW Radar for Healthcare Applications

Abstract: A digital Linear Discrete Frequency Modulated Continuous Wave (LD-FMCW) radar is analyzed and demonstrated for multi-people tracking and vital signs monitoring. Waveform analysis, simulations, and experimental results are presented to validate the proposed radar architecture.

Data Quality Assessment of Capacitively-Coupled ECG Signals

Abstract: Acquisition of capacitively-coupled ECG (ccECG) from daily life scenarios is limited by its sensitivity to motion and its variability in signal quality. 48 features, in combination with different classifiers, were evaluated for quality classification on a dataset of 10000 ccECG segments of 15 seconds. Feature subsets with potential high discriminatory power were identified and evaluated in multiple supervised models, for two classification problems with different tolerance to artefacts. This resulted in balanced accuracies of 94.02% and 92.4%, achieved using a Linear SVM and a fine KNN respectively. These models are useful tools for real-time and offline processing of ccECG signals recorded in real-life scenarios