Hidden state dynamics in laser Doppler vibrometery measurements of the carotid pulse under resting conditions

A laser Doppler vibrometer (LDV) is used to sense movements of the skin overlying the carotid artery. Fluctuations in carotid artery diameter due to variations in the underlying blood pressure are sensed at the surface of the skin. Portions of the LDV signal corresponding to single heartbeats, called the LDV pulses, are extracted. This paper introduces the use of hidden Markov models (HMMs) to model the dynamics of the LDV pulse from beat to beat based on pulse morphology, which under resting conditions are primarily due to breathing effects. LDV pulses are classified according to state, by computing the optimal state path through the data using trained HMMs. HMM state dynamics are compared to simultaneous recordings of strain gauges placed on the abdomen. The work presented here provides a robust statistical approach to modeling the dependence of the LDV pulse on latent states.