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Table 3 Grid search values for HMM hyperparameter optimization. Grad = gradient of the linear regression fit, var = signal variance and poly fit = the first three coefficients of the second-order polynomial fit

From: Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson’s disease patients

Parameters Values
Window size [ms] 100, 220, 500
Feature combinations [raw] / [raw, grad] / [raw, var, poly fit]
Number of GMM components 1, 3, 5, 8
Number of states for stride model 5, 10, 15, 20, 25
Number of states for transition model 3, 5, 8, 12