Multimodal Hidden Markov Models for Real-Time Human Proficiency Assessment in Industry 5.0: Integrating Physiological, Behavioral, and Subjective Metrics

Multimodal Hidden Markov Models for Real-Time Human Proficiency Assessment in Industry 5.0: Integrating Physiological, Behavioral, and Subjective Metrics

This paper presents a Multimodal Hidden Markov Model (MHMM) framework specifically designed for real-time human proficiency assessment, integrating physiological (Heart Rate Variability (HRV)), behavioral (Task Completion Time (TCT)), and subjective (NASA Task Load Index (NASA-TLX)) data streams to...

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Bibliographic Details
Main Authors: Mowffq M. Alsanousi, Vittaldas V. Prabhu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
Industry 5.0
human proficiency assessment
Multimodal Hidden Markov Model
real-time monitoring
human–AI collaboration
temporal modeling
Online Access:https://www.mdpi.com/2076-3417/15/14/7739
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