Automated Biomedical Signal Quality Assessment of Electromyograms: Current Challenges and Future Prospects
Author:
Affiliation:
1. Inst. of Biomed. Eng., Univ. of New Brunswick, Fredericton, NB, Canada
2. Dept. of Syst. & Comput. Eng., Carleton Univ. in Ottawa, Ottawa, ON, Canada
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation,Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/5289/9693405/09693438.pdf?arnumber=9693438
Reference24 articles.
1. Navigating features: a topologically informed chart of electromyographic features space
2. Deep learning for surface electromyography artifact contamination type detection
3. Detection of ADC clipping, quantization noise, and amplifier saturation in surface electromyography
4. Automatic assessment of electromyogram quality
5. A Nonstationary Model for the Electromyogram
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