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Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data
Sleep constitutes a key indicator of human health, performance, and quality of life.
Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data
Psychiatric patients' passive activity monitoring is crucial to detect behavioural shifts in real-time, comprising a tool that helps clinicians supervise patients' evolution over time and enhance the associated treatments' outcomes.
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