Evidence map›Paper›PMID 31799015›Full record

ArticleBiomedical engineering letters2019

A compact-sized surface EMG sensor for myoelectric hand prosthesis.

Alok Prakash, Shiru Sharma, Neeraj Sharma

Abstract read
In one paragraph

Article in Biomedical engineering letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Advances in Printed Electronic Textiles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Design of Wearable Electrolarynx with Automatic Control.Journal of medical signals and sensors
    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

3 authors.

Alok PrakashSchool of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005 India.
Shiru SharmaSchool of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005 India.
Neeraj SharmaSchool of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, 221005 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Myoelectric prosthesis requires a sensor that can reliably capture surface electromyography (sEMG) signal from amputees for its controlled operation. The main problems with the presently available EMG devices are their extremely high cost, large response time, noise susceptibility, less amplitude sensitivity, and larger size. This paper proposes a compact and affordable EMG sensor for the prosthetic application. The sensor consists of an electrode interface, signal conditioning unit, and power supply unit all encased in a single package. The performance of dry electrodes employed in the skin interface was compared with the conventional Ag/AgCl electrodes, and the results were found satisfactory. The envelope detection technique in the sensor based on the tuned RC parameters enables the generation of smooth, faster, and repeatable EMG envelope irrespective of signal strength and subject variability. The output performance of the developed sensor was compared with commercial EMG sensor regarding signal-to-noise ratio, sensitivity, and response time. To perform this, EMG data with both devices were recorded for 10 subjects (3 amputees and 7 healthy subjects). The results showed 1.4 times greater SNR values and 45% higher sensitivity of the developed sensor than the commercial EMG sensor. Also, the proposed sensor was 57% faster than the commercial sensor in producing the output response. The sEMG sensor was further tested on amputees to control the operation of a self-designed 3D printed prosthetic hand. With proportional control scheme, the myoelectric hand setup was able to provide quicker and delicate grasping of objects as per the strength of the EMG signal.

Indexed as

Control schemeGrasp typesMyoelectric prosthesisSignal-to-noise ratio (SNR)Surface electromyography

Identifiers

PMID31799015
PMCPMC6859146

What OpenQuestion holds

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Registered trials

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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.