ArticleSensors (Basel, Switzerland)2022
Discussion of the Influence of Multiscale PCA Denoising Methods with Three Different Features.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Robust point cloud lightweighting with multi-scale adaptive filtering and entropy-driven subdivision.PloS one · 2026Article
- Ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer.Frontiers in oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bioinformation is information generated from biological movement. By using a variety of modern technologies, we can use this information to form a meaningful model for researchers to study. An electromyographic (EMG) signal is one type of bioinformation that is used in many areas to help people study human muscle movement. This information can help in both clinical areas and industrial areas. EMG is a very complicated signal, so processing it is vital. The processing of EMG signals is divided into collection, denoising, decomposition, feature extraction and classification steps. In this article, the wavelet denoising step and several decomposition processes are discussed to show the usage of this technique in the final classification step. At the end of the study, we find that after the wavelet denoising step, the classification accuracy, which uses the K-nearest neighbor of the independent component analysis features, improves, but the accuracy of the wavelet coefficient features and autoregression coefficient features decreases.
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Registered trials
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.