Phase-Based Methods for Heart Rate Detection Using UWB Impulse Doppler Radar

Ghaffar

et al. 2020

Sensors

Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR-UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate's health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.

Section: Introductionmentioning

confidence: 99%

An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver

Ghaffar

et al. 2020

Sensors

IEEE Signal Process. Mag.

“…Recently, vital sign detection and activity recognition have captivated the research community especially in assisted living (AL) [1][2][3][4], for aging in place ( Figure 1) and hospitals to monitor in/outpatients e.g. pulmonary obstruction disorder (POD).…”

Section: Introductionmentioning

confidence: 99%

“…Radar has gained popularity as a sensing technology to support innovative/personalized healthcare services [1][2][3][4]. Why Radar?…”

Section: Introductionmentioning

confidence: 99%

Radar Signal Processing for Sensing in Assisted Living: The Challenges Associated With Real-Time Implementation of Emerging Algorithms

Kernec

Fioranelli

Ding

et al. 2019

130

This article presents radar signal processing for sensing in the context of assisted living. This is covered through 3 example applications: human activity recognition for activities of daily living, respiratory disorder and Sleep Stages classification. The common challenge of classification is discussed within a framework of measurements/pre-processing, feature extraction, and classification algorithms for supervised learning. Then, the specific challenges of the 3 applications from a signal processing standpoint are detailed in their specific data processing and ad-hoc classification strategies, focusing on recent trends in the field of activity recognition (multidomain, multi-modal and fusion) and healthcare applications based on vital signs (super-resolution techniques) and commenting on outstanding challenges. To conclude, this paper explores the challenge of the real-time implementation of signal processing/classification algorithms.

“…The identification of various significant information from the satellites has been carried out by Vega et al [29] where the Doppler radar is also equipped with double frequency as well as polarization. The work carried out by Ren et al [30] has performed identification of heartbeats using demodulation of the complex signal for precise detection performance. Majority of the existing approaches using Doppler radar has been tested in hardware-based approach with a lesser computational model while the majority of the studies focuses on identification of the certain targets.…”

Section: Introductionmentioning

confidence: 99%

Granular Mobility-Factor Analysis Framework for enriching Occupancy Sensing with Doppler Radar

Mane¹,

Rao²

2018

IJECE

With the growing need for adoption of smarter resource control system in existing infrastructure, the proliferation of occupancy sensing is slowly increasing its pace. After reviewing an existing system, we find that utilization of Doppler radar is less progressive in enhancing the accuracy of occupancy sensing operation. Therefore, we introduce a novel analytical model that is meant for incorporating granularity in tracing the psychological periodic characteristic of an object by emphasizing on the mobility and uncertainty movement of an object in the monitoring area. Hence, the model is more emphasized on identifying the rate of change in any periodic physiological characteristic of an object with the aid of mathematical modelling. At the same time, the model extracts certain traits of frequency shift and directionality for better tracking of the unidentified object behavior where its applicabilibility can be generalized in majority of the fields related to object detection.