  Biosignals are nowadays important subjects for scientific researches from
both theory and applications especially with the appearance of new pandemics
threatening humanity such as the new Coronavirus. One aim in the present work
is to prove that Wavelets may be successful machinery to understand such
phenomena by applying a step forward extension of wavelets to multiwavelets. We
proposed in a first step to improve the multiwavelet notion by constructing
more general families using independent components for multi-scaling and
multiwavelet mother functions. A special multiwavelet is then introduced,
continuous and discrete multiwavelet transforms are associated, as well as new
filters and algorithms of decomposition and reconstruction. The constructed
multiwavelet framework is applied for some experimentations showing fast
algorithms, ECG signal, and a strain of Coronavirus processing.
