Evidence map›Paper›PMID 34069847›Full record

ArticleSensors (Basel, Switzerland)2021

Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices.

Chendan Dou, Hao Huan

Abstract readClinical Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Chendan DouSchool of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
Hao HuanSchool of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.

Funding

National Natural Science Foundation of China 62027801
6 · The paper itself

Abstract

Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios. However, previous studies show that the breathing depth and location may affect the detectability of respiratory signals. In this study, we leverage the variation of the Doppler spectral energy extracted from the channel state information (CSI) collected by Wi-Fi devices to track the chest displacement induced by respiration. First, the random phase is eliminated by phase-fitting method to obtain the complex CSI containing the Doppler shift. Then, the multipath decomposition of CSI is carried out to obtain the channel impulse response, which eliminates the interference phase of the time delay and retains the Doppler shift. The dynamic path units are also separate from the multipath, which overcomes the indoor multipath effect. Finally, we conduct a time-frequency analysis to dynamic units to accumulate Doppler spectral energy. Based on these ideas, we design a complete respiration rate-monitoring system to obtain the respiration rate by using the consistency between the Doppler energy change period and the respiratory cycle. We evaluate our system through extensive experiments in several typical home environments filled with multipath. Experimental results show that the errors of the three scenarios are approximate, the maximum error is less than 0.7 bpm, and the average errors are approximately 0.15 bpm. This result indicates that our scheme can achieve high precision respiration monitoring and has good anti-multipath ability compared with existing methods.

Indexed as

Respiratory RateVital SignsDoppler EffectHumansMonitoring, PhysiologicRespirationchannel state information (CSI)Doppler shiftrespiration sensingWi-Fi

Identifiers

PMID34069847
PMCPMC8157398

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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.