Learning from Life-Logging Data by Hybrid HMM: A Case Study on Active States Prediction
Ji Ni, Tryphon Lambrou, Xujiong Ye · 2016
In this paper, we have proposed employing a hybrid classifier-hidden Markov model (HMM) as a supervised learning approach to recognize daily active states from sequential life-logging data collected from wearable sensors.