Following on from the valuable feedback I received from my last acoustics related question on developing a high pass filter, I wanted to open up this highly topical acoustics related question.
As we probably all know by now, the covid-19 coronovirus has some fairly specific symptoms, one of which is a dry cough and/or breathing difficulties.
As I had acoustics projects on my brain, I wondered what techniques and sensors could be used to detect a cough and with the use of machine learning and/or AI is there a means of differentiating different coughs (as well as breathing patterns). Maybe this could then eventually form some type of data set for automated monitoring.
I did a quick online search and this academic paper (published 2018) popped up on my search list, which is a rather useful reference: https://www.hindawi.com/journals/js/2018/9845321/
So, I thought this could make for an interesting community related project and hence I'm putting it out there.
Where does one start, for example? Does this require a low pass filter or a pass band filter? What other acoustic techniques could be used etc.
Similarly with breathing - what techniques and sensors would be best suited to monitor the speed and depth of breathing.
Any thoughts and suggestions, will be welcomed.