Christer Ahlström

Orcid: 0000-0003-4134-0303

According to our database1, Christer Ahlström authored at least 29 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
Fit for Duty Assessment of Driver Fatigue based on Statistical Modelling of Cardiovascular Parameters.
Simul. Notes Eur., December, 2023

A Review of Occlusion as a Tool to Assess Attentional Demand in Driving.
Hum. Factors, 2023

2022
A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions.
IEEE Trans. Intell. Transp. Syst., 2022

Real-Time Adaptation of Driving Time and Rest Periods in Automated Long-Haul Trucking: Development of a System Based on Biomathematical Modelling, Fatigue and Relaxation Monitoring.
IEEE Trans. Intell. Transp. Syst., 2022

Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm.
IEEE Trans. Intell. Transp. Syst., 2022

Technologies for Risk Mitigation and Support of Impaired Drivers.
IEEE Trans. Intell. Transp. Syst., 2022

2021
Heart Rate Variability for Classification of Alert Versus Sleep Deprived Drivers in Real Road Driving Conditions.
IEEE Trans. Intell. Transp. Syst., 2021

2020
Attentional Demand as a Function of Contextual Factors in Different Traffic Scenarios.
Hum. Factors, 2020

On the Difference Between Necessary and Unnecessary Glances Away From the Forward Roadway: An Occlusion Study on the Motorway.
Hum. Factors, 2020

Effects of training on truck drivers' interaction with cyclists in a right turn.
Cogn. Technol. Work., 2020

Using smartphone logging to gain insight about phone use in traffic.
Cogn. Technol. Work., 2020

2019
Driver Sleepiness Classification Based on Physiological Data and Driving Performance From Real Road Driving.
IEEE Trans. Intell. Transp. Syst., 2019

Automatic driver sleepiness detection using EEG, EOG and contextual information.
Expert Syst. Appl., 2019

Heart Rate Variability for Driver Sleepiness Classification in Real Road Driving Conditions.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018
Automated EEG Artifact Handling With Application in Driver Monitoring.
IEEE J. Biomed. Health Informatics, 2018

Performance of an Additional Task During Level 2 Automated Driving: An On-Road Study Comparing Drivers With and Without Experience With Partial Automation.
Hum. Factors, 2018

Bicyclists' adaptation strategies when interacting with text messages in urban environments.
Cogn. Technol. Work., 2018

Driver drowsiness detection: a comparison between intrusive and non-intrusive signal acquisition methods.
Proceedings of the 7th European Workshop on Visual Information Processing, 2018

2017
A Generalized Method to Extract Visual Time-Sharing Sequences From Naturalistic Driving Data.
IEEE Trans. Intell. Transp. Syst., 2017

Minimum Required Attention: A Human-Centered Approach to Driver Inattention.
Hum. Factors, 2017

2013
A Gaze-Based Driver Distraction Warning System and Its Effect on Visual Behavior.
IEEE Trans. Intell. Transp. Syst., 2013

2012
Processing of Eye/Head-Tracking Data in Large-Scale Naturalistic Driving Data Sets.
IEEE Trans. Intell. Transp. Syst., 2012

2010
Review of real-time visual driver distraction detection algorithms.
Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research, 2010

Comparison of eye tracking systems with one and three cameras.
Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research, 2010

2008
Assessing Aortic Stenosis Using Sample Entropy of the Phonocardiographic Signal in Dogs.
IEEE Trans. Biomed. Eng., 2008

2006
Pulse wave transit time for monitoring respiration rate.
Medical Biol. Eng. Comput., 2006

Thresholding Distance Plots Using True Recurrence Points.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Detection of the 3<sup>rd</sup>Heart Sound Using Recurrence Time Statistics.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005
Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction.
IEEE Signal Process. Lett., 2005


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