1. the train test in here was leaky, but in our current iteration of the work we do 10 fold train / test without leakage
2. There was no different in performance at higher HR values, the rpi data contained people running in place and our performance on that was as good as laying down
3. a simple presence detection model would solve that and also the algorithm already covers this
1. The collected data set has one person in between receiver and transmitter. Will the same model work if there is multiple people between receiver and transmitter?
2. If anyone has a heart rate outside the range of 48-130? can this model detect that heart rate?
1. We are currently working on multi person, this iteration doesn't support it.
2. The range was just what we had in this dataset, if we exposed the algorithm to a broader range, it would work for that too.
1. in this iteration we used a 64% training 16% validation 20% testing split. In our current work we are testing with 10 fold / leave a subject out to get better analysis.
2. the esp dataset had heart rate up to 130 which is relatively high, and the raspberry pi data had people running in place etc... where the heart rate is higher
