Query: How could the heart rate be estimated by means of an active inference paradigm?
Source: pubmed1.pdf
Relevant passages:
The second panel of Fig. 2 shows the Shannon surprise of an inference model that estimates the current heart rate using the two standard components of a generative model. The for- mer component is the prior, which encodes the person’s a priori probabilistic belief (i.e. probability distribution) about her “nor- mal” heart rate range; here, the prior is a Gaussian centered on 67 and has a precision of 0.11. The latter component is the likeli- hood, which encodes the probabilistic mapping between sensory (heartbeat) observations and the hidden state (heart rate); here, the likelihood is a Gaussian centered on the current heart rate with an additional bias of 15 pulses, and the panel shows the results for 10 values for precision obtained by subdividing the range [0.1,10] into equal intervals.