ArticleBrain sciences2023
Assessment of Vigilance Level during Work: Fitting a Hidden Markov Model to Heart Rate Variability.
Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Vigilance decrements in air traffic control as an aviation safety risk: a systematic review of modeling and prediction approaches.Frontiers in neuroergonomics · 2026Pooled it
- Effects of constant and incremental modes of music volume and odor concentration on vigilance.Frontiers in psychology · 2026Article
- A MultiModal Vigilance (MMV) dataset during RSVP and SSVEP brain-computer interface tasks.Scientific data · 2024Article
- Efficient Generalized Electroencephalography-Based Drowsiness Detection Approach with Minimal Electrodes.Sensors (Basel, Switzerland) · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train parameters of the modified hidden Markov model for a vigilance assessment. The data were collected to train the model using the Baum-Welch algorithm and to obtain the state transition probability matrix A^ and the observation probability matrix B^. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and the Viterbi algorithm was used to find the optimal state, which was compared with the actual state. The constructed vigilance assessment model had a high accuracy rate, and the accuracy rate of data prediction for these three volunteers exceeded 80%. Our approach can be used in wearable products to improve their vigilance level assessment functionality or in other fields that have key positions with high concentration requirements and monotonous repetitive work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.