Evidence map›Paper›PMID 34695911›Full record

ArticleSensors (Basel, Switzerland)2021

Towards Accurate, Cost-Effective, Ultra-Low-Power and Non-Invasive Respiration Monitoring: A Reusable Wireless Wearable Sensor for an Off-the-Shelf KN95 Mask.

Yu Xu, Qi Li, Zhenzhou Tang, Jun Liu, Bingjin Xiang

Open access · goldAbstract read
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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Laser spectroscopic method for remote sensing of respiratory rate.Physical and engineering sciences in medicine · 2023
    Article
  4. Review
  5. Article
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

5 authors at 1 institution in 1 country.

Yu XuCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.ORCID 0000-0002-2605-2816
Qi LiCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.
Zhenzhou TangCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.ORCID 0000-0001-7997-6038
Jun LiuCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.
Bingjin XiangCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China.
Wenzhou University · CN

Funding

Zhejiang Provincial Natural Science Foundation of China No.LY19F010010 and No. LY18F030016.
6 · The paper itself

Abstract

Respiratory rate is a critical vital sign that indicates health condition, sleep quality, and exercise intensity. This paper presents a non-invasive, ultra-low-power, and cost-effective wireless wearable sensor, which is installed on an off-the-shelf KN95 mask to facilitate respiration monitoring. The sensing principle is based on the periodic airflow temperature variations caused by exhaled hot air and inhaled cool air in respiratory cycles. By measuring the periodic temperature variations at the exhalation valve of mask, the respiratory parameters can be accurately and reliably detected, regardless of body movements and breathing pathways through nose or mouth. Specifically, we propose a voltage divider with controllable resistors and corresponding selection criteria to improve the sensitivity of temperature measurement, a peak detection algorithm with spline interpolation to increase sampling period without reducing the detection accuracy, and effective low-power optimization measures to prolong the battery life. The experimental results have demonstrated the effectiveness of the proposed sensor, showing a small mean absolute error (MAE) of 0.449 bpm and a very low power consumption of 131.4 μW. As a high accuracy, low cost, low power, and reusable miniature wearing device for convenient respiration monitoring in daily life, the proposed sensor holds promise in real-world feasibility.

Indexed as

N95 RespiratorsWearable Electronic DevicesCost-Benefit AnalysisMonitoring, PhysiologicRespirationairflow temperaturenon-invasive respiration monitoringwireless wearable sensor

Identifiers

PMID34695911
PMCPMC8540598
OpenAlexW3205245870

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.