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Open AccessJournal ArticleDOI

Passive Radar for Opportunistic Monitoring in E-Health Applications

TLDR
The experimental results show that the proposed passive radar system provides adequate performance for both purposes, and prove that non-contact passive Doppler radar is a complementary technology to meet the challenges of future healthcare applications.
Abstract
This paper proposes a passive Doppler radar as a non-contact sensing method to capture human body movements, recognize respiration, and physical activities in e-Health applications. The system uses existing in-home wireless signal as the source to interpret human activity. This paper shows that passive radar is a novel solution for multiple healthcare applications which complements traditional smart home sensor systems. An innovative two-stage signal processing framework is outlined to enable the multi-purpose monitoring function. The first stage is to obtain premier Doppler information by using the high speed passive radar signal processing. The second stage is the functional signal processing including micro Doppler extraction for breathing detection and support vector machine classifier for physical activity recognition. The experimental results show that the proposed system provides adequate performance for both purposes, and prove that non-contact passive Doppler radar is a complementary technology to meet the challenges of future healthcare applications.

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Citations
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RF Sensing Technologies for Assisted Daily Living in Healthcare: A Comprehensive Review

TL;DR: A comprehensive review on three of the most innovative RF sensing technologies for activities of daily living in healthcare sector (namely active radar, passive radar, and wireless channel information and RFID sensing) and presents some of the open challenges that need to be addressed.
Journal ArticleDOI

Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point

TL;DR: Experimental data is presented which verifies the proposed methods for using any type of signal transmission from a standalone WiFi device, and demonstrates the capability for human activity sensing.
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Technological innovations to assess and include the human dimension in the building-performance loop: A review

TL;DR: This literature review summarises applications and main challenges related to the combination of the human dimension and technological innovations in the building sector to increase user welfare and reduce the energy consumption in buildings, as human and machine components of intelligence may complement each other regarding building performance.
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Wearables Meet IoT: Synergistic Personal Area Networks (SPANs)

TL;DR: Synergistic processing of sensors from the smartwatch and objects of everyday use may provide user identification and assessment of new parameters that individual sensors could not generate, such as pulse wave velocity (PWV) and blood pressure.
References
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A comparison of methods for multiclass support vector machines

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Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

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Proceedings ArticleDOI

Whole-home gesture recognition using wireless signals

TL;DR: WiSee is presented, a novel gesture recognition system that leverages wireless signals (e.g., Wi-Fi) to enable whole-home sensing and recognition of human gestures and achieves this goal without requiring instrumentation of the human body with sensing devices.
Journal ArticleDOI

What Is a Savitzky-Golay Filter? [Lecture Notes]

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Trending Questions (1)
What is passive monitoring in mHealth?

Passive monitoring in mHealth involves using passive Doppler radar to capture human body movements, detect respiration, and recognize physical activities using existing wireless signals, as proposed in the paper.