Evidence map›Paper›PMID 37204963›Full record

ArticleIEEE transactions on biomedical circuits and systems2023

A Portable and a Scalable Multi-Channel Wireless Recording System for Wearable Electromyometrial Imaging.

Weilun Li, Zhili Xiao, Junyi Zhao, Kenji Aono, Stephanie Pizzella, Zichao Wen, Yong Wang, Chuan Wang, Shantanu Chakrabartty

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on biomedical circuits and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. A Low-Power Impedance-to-Frequency Converter for Frequency-Multiplexed Wearable Sensors.IEEE transactions on biomedical circuits and systems · 2024
    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

9 authors at 1 institution in 1 country.

Weilun Li
Zhili Xiao
Junyi Zhao
Kenji Aono
Stephanie Pizzella
Zichao Wen
Yong Wang
Chuan Wang
Shantanu Chakrabartty
Washington University in St. Louis · US

Funding

A self-capacitance driven wearable electromyometrial imaging system for maternal and fetal monitoring during pregnancy and laborR01HD105905 · NICHD · WASHINGTON UNIVERSITY · PI Chuan Wang · 2022 to 2026
$1.7M
NICHD NIH HHS R01 HD105905
6 · The paper itself

Abstract

Electromyometrial imaging (EMMI) technology has emerged as one of the promising technology that can be used for non-invasive pregnancy risk stratification and for preventing complications due to pre-term birth. Current EMMI systems are bulky and require a tethered connection to desktop instrumentation, as a result, the system cannot be used in non-clinical and ambulatory settings. In this article, we propose an approach for designing a scalable, portable wireless EMMI recording system that can be used for in-home and remote monitoring. The wearable system uses a non-equilibrium differential electrode multiplexing approach to enhance signal acquisition bandwidth and to reduce the artifacts due to electrode drifts, amplifier 1/f noise, and bio-potential amplifier saturation. A combination of active shielding, a passive filter network, and a high-end instrumentation amplifier ensures sufficient input dynamic range ([Formula: see text]) such that the system can simultaneously acquire different bio-potential signals like maternal electrocardiogram (ECG) in addition to the EMMI electromyogram (EMG) signals. We show that the switching artifacts and the channel cross-talk introduced due to non-equilibrium sampling can be reduced using a compensation technique. This enables the system to be potentially scaled to a large number of channels without significantly increasing the system power dissipation. We demonstrate the feasibility of the proposed approach in a clinical setting using an 8-channel battery-powered prototype which dissipates less than 8 μW per channel for a signal bandwidth of 1 KHz.

Indexed as

Signal Processing, Computer-AssistedWearable Electronic DevicesElectrocardiographyElectrodesElectromyographyWireless Technology

Identifiers

PMID37204963
PMCPMC10871545
OpenAlexW4377142599

What OpenQuestion holds

Textmetadata
LicenceTDM
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.