Machine Learning for Detection of Muscular Activity from Surface EMG Signals.
Francesco Di NardoAntonio NoceraAlessandro CucchiarelliSandro FiorettiChristian MorbidoniPublished in: Sensors (Basel, Switzerland) (2022)
These outcomes support DEMANN's reliability in assessing onset/offset events in different motor tasks and the condition of signal quality (different SNR), improving reference-algorithm performances. Unlike other works, DEMANN's adopts a machine learning approach where a neural network is trained by only simulated sEMG signals, avoiding the possible complications and costs associated with a typical experimental procedure, making this approach suitable to clinical practice.
Keyphrases
- machine learning
- neural network
- clinical practice
- resistance training
- artificial intelligence
- big data
- deep learning
- working memory
- loop mediated isothermal amplification
- risk factors
- body composition
- quality improvement
- label free
- high density
- real time pcr
- type diabetes
- metabolic syndrome
- insulin resistance
- skeletal muscle