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Found 6 papers, 4 papers with code
ResEMGNet: A Lightweight Residual Deep Learning Architecture for Neuromuscular Disorder Detection from Raw EMG Signals
Amyotrophic Lateral Sclerosis (ALS) and Myopathy are debilitating neuromuscular disorders that demand accurate and efficient diagnostic approaches.
EMG Signal Classification for Neuromuscular Disorders with Attention-Enhanced CNN
This study marks a contribution to addressing the diagnostic challenges posed by neuromuscular disorders through a data-driven, multi-class classification approach, providing valuable insights into the potential for early and accurate detection.
COVID-19 mRNA Vaccine Degradation Prediction using Regularized LSTM Model
Due to the advantages of mRNA vaccines such as potency, safety, and production feasibility, recent researches in vaccinology has seen strong focus in mRNA vaccines.
SPECMAR: Fast Heart Rate Estimation from PPG Signal using a Modified Spectral Subtraction Scheme with Composite Motion Artifacts Reference Generation
In this paper, a fast algorithm for heart rate estimation based on modified SPEctral subtraction scheme utilizing Composite Motion Artifacts Reference generation (SPECMAR) is proposed using two-channel PPG and three-axis accelerometer signals.
Detection of Inferior Myocardial Infarction using Shallow Convolutional Neural Networks
The performance of the model is evaluated on IMI and healthy signals obtained from Physikalisch-Technische Bundesanstalt (PTB) database.
A Time-Frequency Domain Approach of Heart Rate Estimation From Photoplethysmographic (PPG) Signal
Significance- The proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach and thus feasible for implementing in wearable devices to monitor heart rate for fitness and clinical purpose.
Applications
