Raw biomedical signals are notoriously dirty. Common artifacts include:
Sensors (electrodes, transducers) pick up analog signals from the body. Because modern computers operate digitally, these continuous analog signals must be converted into discrete digital values via an Analog-to-Digital Converter (ADC). This involves two critical parameters: Biomedical Signal Analysis
The final step involves making a decision. Is the signal normal or pathological? Traditionally, this was done via thresholding. Today, Machine Learning (ML) algorithms are increasingly used to Raw biomedical signals are notoriously dirty
Once the signal is clean, algorithms identify specific characteristics. In ECG analysis, the algorithm must detect the QRS complex (the spike representing ventricular contraction). In EEG, features might include specific frequency bands (Alpha, Beta, Delta waves). These "features" become the variables used for diagnosis. this was done via thresholding. Today