Evidence map›Paper›PMID 24514883›Full record

ArticleSensors (Basel, Switzerland)2014

Techniques for clutter suppression in the presence of body movements during the detection of respiratory activity through UWB radars.

Antonio Lazaro, David Girbau, Ramon Villarino

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
7.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 143 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Antonio LazaroDepartment of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, Spain. antonioramon.lazaro@urv.cat.
David GirbauDepartment of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, Spain. david.girbau@urv.cat.
Ramon VillarinoDepartment of Electronic, Electric and Automatic Control Engineering, Universitat Rovira i Virgili (URV), Av. Països Catalans 26, Campus Sescelades, Tarragona 43007, Spain. ramon.villarino@urv.cat.
Universitat Rovira i Virgili · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper focuses on the feasibility of tracking the chest wall movement of a human subject during respiration from the waveforms recorded using an impulse-radio (IR) ultra-wideband radar. The paper describes the signal processing to estimate sleep apnea detection and breathing rate. Some techniques to solve several problems in these types of measurements, such as the clutter suppression, body movement and body orientation detection are described. Clutter suppression is achieved using a moving averaging filter to dynamically estimate it. The artifacts caused by body movements are removed using a threshold method before analyzing the breathing signal. The motion is detected using the time delay that maximizes the received signal after a clutter removing algorithm is applied. The periods in which the standard deviations of the time delay exceed a threshold are considered macro-movements and they are neglected. The sleep apnea intervals are detected when the breathing signal is below a threshold. The breathing rate is determined from the robust spectrum estimation based on Lomb periodogram algorithm. On the other hand the breathing signal amplitude depends on the body orientation respect to the antennas, and this could be a problem. In this case, in order to maximize the signal-to-noise ratio, multiple sensors are proposed to ensure that the backscattered signal can be detected by at least one sensor, regardless of the direction the human subject is facing. The feasibility of the system is compared with signals recorded by a microphone.

Identifiers

PMID24514883
PMCPMC3958278
OpenAlexW2045200098

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.