Evidence map›Paper›PMID 32664268›Full record

ArticleMicromachines2020

Design and Implementation of a Multifunction Wearable Device to Monitor Sleep Physiological Signals.

Lun-De Liao, Yuhling Wang, Yung-Chung Tsao, I-Jan Wang, De-Fu Jhang, Chiung-Cheng Chuang, Sheng-Fu Chen

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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  6. Article
  7. Cardiodiagnostics Based on Photoplethysmographic Signals.Diagnostics (Basel, Switzerland) · 2022
    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

7 authors at 3 institutions in 1 country.

Lun-De LiaoInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.ORCID 0000-0002-2601-3673
Yuhling WangInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.
Yung-Chung TsaoInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.ORCID 0000-0003-0061-9682
I-Jan WangDepartment of Industrial Engineering and Enterprise Information, Tunghai University, Taichung City 407224, Taiwan.
De-Fu JhangInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.
Chiung-Cheng ChuangInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.ORCID 0000-0002-8124-1396
Sheng-Fu ChenInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Zhunan 35053, Taiwan.
National Health Research Institutes · TWChung Yuan Christian University · TWTunghai University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a wearable device built on an Adafruit Circuit Playground Express (CPE) board and integrated with a photoplethysmographic (PPG) optical sensor for heart rate monitoring and multiple embedded sensors for medical applications-in particular, sleep physiological signal monitoring. Our device is portable and lightweight. Due to the microcontroller unit (MCU)-based architecture of the proposed device, it is scalable and flexible. Thus, with the addition of different plug-and-play sensors, it can be used in many applications in different fields. The innovation introduced in this study is that with additional sensors, we can determine whether there are intermediary variables that can be modified to improve our sleep monitoring algorithm. Additionally, although the proposed device has a relatively low cost, it achieves substantially improved performance compared to the commercially available Philips ActiWatch2 wearable device, which has been approved by the Food and Drug Administration (FDA). To assess the reliability of our device, we compared physiological sleep signals recorded simultaneously from volunteers using both our device and ActiWatch2. Motion and light detection data from our device were shown to be correlated to data simultaneously collected using the ActiWatch2, with correlation coefficients of 0.78 and 0.89, respectively. For 7 days of continuous data collection, there was only one instance of a false positive, in which our device detected a sleep interval, while the ActiWatch2 did not. The most important aspect of our research is the use of an open architecture. At the hardware level, general purpose input/output (GPIO), serial peripheral interface (SPI), integrated circuit (I

Indexed as

Internet of Things (IoT)physiological signalssleep physiological signalswearable device

Identifiers

PMID32664268
PMCPMC7407184
OpenAlexW3040828038

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.