Heart Rate Detection During Sleep Using a Flexible RF Resonator and Injection-Locked PLL Sensor

A Review of Patient Bed Sensors for Monitoring of Vital Signs

The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

Progress in wearable acoustical sensors for diagnostic applications

With extensive and widespread uses of miniaturized and intelligent wearable devices, continuously monitoring subtle spatial and temporal changes in human physiological states becomes crucial for daily healthcare and professional medical diagnosis. Wearable acoustical sensors and related monitoring systems can be comfortably applied onto human body with a distinctive function of non-invasive detection. This paper reviews recent advances in wearable acoustical sensors for medical applications. Structural designs and characteristics of the structural components of wearable electronics, including piezoelectric and capacitive micromachined ultrasonic transducer (i.e., pMUT and cMUT), surface acoustic wave sensors (SAW) and triboelectric nanogenerators (TENGs) are discussed, along with their fabrication techniques and manufacturing processes. Diagnostic applications of these wearable sensors for detection of biomarkers or bioreceptors and diagnostic imaging have further been discussed. Finally, main challenges and future research directions in these fields are highlighted.

A Flexible Near-Field Biosensor for Multisite Arterial Blood Flow Detection

Modern wearable devices show promising results in terms of detecting vital bodily signs from the wrist. However, there remains a considerable need for a device that can conform to the human body's variable geometry to accurately detect those vital signs and to understand health better. Flexible radio frequency (RF) resonators are well poised to address this need by providing conformable bio-interfaces suitable for different anatomical locations. In this work, we develop a compact wearable RF biosensor that detects multisite hemodynamic events due to pulsatile blood flow through noninvasive tissue-electromagnetic (EM) field interaction. The sensor consists of a skin patch spiral resonator and a wearable transceiver. During resonance, the resonator establishes a strong capacitive coupling with layered dielectric tissues due to impedance matching. Therefore, any variation in the dielectric properties within the near-field of the coupled system will result in field perturbation. This perturbation also results in RF carrier modulation, transduced via a demodulator in the transceiver unit. The main elements of the transceiver consist of a direct digital synthesizer for RF carrier generation and a demodulator unit comprised of a resistive bridge coupled with an envelope detector, a filter, and an amplifier. In this work, we build and study the sensor at the radial artery, thorax, carotid artery, and supraorbital locations of a healthy human subject, which hold clinical significance in evaluating cardiovascular health. The carrier frequency is tuned at the resonance of the spiral resonator, which is 34.5 ± 1.5 MHz. The resulting transient waveforms from the demodulator indicate the presence of hemodynamic events, i.e., systolic upstroke, systolic peak, dicrotic notch, and diastolic downstroke. The preliminary results also confirm the sensor's ability to detect multisite blood flow events noninvasively on a single wearable platform.

Electrodeless Heart and Respiratory Rate Estimation during Sleep Using a Single Fabric Band and Event-Based Edge Processing

Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact HR/RR measurement remains a challenge due to imprecise readings. "Invisible" wearables integrated into day-to-day garments have the potential to produce precise readings with a comfortable user experience. Sleep studies and patient monitoring benefit from "Invisibles" due to longer wearability without significant discomfort. This paper suggests a novel method to reduce the footprint of sleep monitoring devices. We use a single silver-coated nylon fabric band integrated into a substrate of a standard cotton/nylon garment as a resistive elastomer sensor to measure air and blood volume change across the chest. We introduce a novel event-based architecture to process data at the edge device and describe two algorithms to calculate real-time HR/RR on ARM Cortex-M3 and Cortex-M4F microcontrollers. RR estimations show a sensitivity of 99.03% and a precision of 99.03% for identifying individual respiratory peaks. The two algorithms used for HR calculation show a mean absolute error of 0.81 ± 0.97 and 0.86±0.61 beats/min compared with a gold standard ECG-based HR. The event-based algorithm converts the respiratory/pulse waveform into instantaneous events, therefore reducing the data size by 40-140 times and requiring 33% less power to process and transfer data. Furthermore, we show that events hold enough information to reconstruct the original waveform, retaining pulse and respiratory activity. We suggest fabric sensors and event-based algorithms would drastically reduce the device footprint and increase the performance for HR/RR estimations during sleep studies, providing a better user experience.

Flexible and stretchable dual mode nanogenerator for rehabilitation monitoring and information interaction

Motion recognition and information interaction sensors with flexibility and stretchability are key functional modules as interactive media between the mechanical motions and electric signals in an intelligent robotic and rehabilitation training system. Nanogenerators have many useful applications in the field of intelligent interaction, with the advantages of a self-powered sensing ability, easy fabrication, considerable sensitivity and reliability. However, the singularity of the sensing mode limits its applications. Hence, in this research, a flexible and stretchable dual mode nanogenerator (FSDM-NG) for human motion sensing and information interaction, based on the integration of piezoelectric and triboelectric principles was developed. In piezoelectric mode, the FSDM-NG can effectively monitor the bending angle of joints (finger, wrist and elbow) from 30° to 90°. In triboelectric mode, text and logic information transfer are encoded using Morse code and logic gates, respectively. In addition, the device has good adhesion and biosafety, and is robust which makes it work normally even in under water environments. Combining these two sensing mechanisms, multiple modes of sensing from touch and stretch based on the FSDM-NG can be achieved for information interaction in real time. The proposed sensor has the potential to be adapted for more complex sensing, which may provide new applications for intelligent interaction of robots and in the rehabilitation training field.

A Noninvasive, Electromagnetic, Epidermal Sensing Device for Hemodynamics Monitoring

Non-intrusive monitoring of blood flow parameters is vital for obtaining physiological and pathophysiological information pertaining to dynamic cardiovascular events and is feasible to achieve via non-invasive, conformal, wearable technologies. Here, we present a proof-of-concept of a fully integrated, high frequency (bandwidth 40 MHz), electromagnetic sensing device for monitoring limb hemodynamics and morphology associated with blood flow. The sensing architecture integrates a novel radio frequency (RF) skin patch resonator embedded with a coplanar outer loop antenna and a scalable, standalone wireless readout hardware based on standing wave ratio (SWR) bridge. The resonator itself is a copper-based open circuit planar Archimedean spiral with a rectangular cross-sectional area, chemically etched on a flexible polyimide substrate. The readout hardware is developed exploiting off-the-shelf components, fabricated on the top of a rigid FR4 substrate. The proposed readout circuit can measure resonant frequency of an RLC network. When energized by the external oscillating RF field via loop antenna, the resonator produces an electromagnetic field response which can be perturbed by dielectric variation inside its field boundary. Through leveraging this principle, the in-vitro experimental results from the benchtop models suggest that the resonator's RF attributes such as resonant frequency shift and magnitude variation of reflection coefficient due to fluid volume displacement can be successfully detected through the proposed hardware architecture. Hence, the system could be an alternative to the conventional, multimodal, non-invasive wearable sensing with an unprecedented capability of ubiquitous fluid phenomena detection from multiple sites of the human body.

Passive Self Resonant Skin Patch Sensor to Monitor Cardiac Intraventricular Stroke Volume Using Electromagnetic Properties of Blood

This paper focuses on the development of a passive, lightweight skin patch sensor that can measure fluid volume changes in the heart in a non-invasive, point-of-care setting. The wearable sensor is an electromagnetic, self-resonant sensor configured into a specific pattern to formulate its three passive elements (resistance, capacitance, and inductance). In an animal model, a bladder was inserted into the left ventricle (LV) of a bovine heart, and fluid was injected using a syringe to simulate stoke volume (SV). In a human study, to assess the dynamic fluid volume changes of the heart in real time, the sensor frequency response was obtained from a participant in a 30° head-up tilt (HUT), 10° HUT, supine, and 10° head-down tilt positions over time. In the animal model, an 80-mL fluid volume change in the LV resulted in a downward frequency shift of 80.16 kHz. In the human study, there was a patterned frequency shift over time which correlated with ventricular volume changes in the heart during the cardiac cycle. Statistical analysis showed a linear correlation \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${R} ^{2} = 0.98$ \end{document} and 0.87 between the frequency shifts and fluid volume changes in the LV of the bovine heart and human participant, respectively. In addition, the patch sensor detected heart rate in a continuous manner with a 0.179% relative error compared to electrocardiography. These results provide promising data regarding the ability of the patch sensor to be a potential technology for SV monitoring in a non-invasive, continuous, and non-clinical setting.