2021
|
Parnandi, A.; Gutierrez-Osuna, R. Partial reinforcement in game biofeedback for relaxation training Journal Article In: IEEE Transactions on Affective Computing, vol. 12, no. 1, pp. 141-153, 2021. @article{parnandi2018taffc,
title = {Partial reinforcement in game biofeedback for relaxation training},
author = {A. Parnandi and R. Gutierrez-Osuna },
url = {https://ieeexplore.ieee.org/document/8400398
https://psi.engr.tamu.edu/wp-content/uploads/2021/02/08400398.pdf},
year = {2021},
date = {2021-02-28},
journal = {IEEE Transactions on Affective Computing},
volume = {12},
number = {1},
pages = {141-153},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
2020
|
Ahmed, B; Zafar, M; Rihawi, R; Gutierrez-Osuna, R Gaming away stress: Using biofeedback games to learn paced breathing Journal Article In: IEEE Transactions on Affective Computing, vol. 11, no. 3, pp. 519-531, 2020. @article{ahmed2018tac,
title = {Gaming away stress: Using biofeedback games to learn paced breathing},
author = {B Ahmed and M Zafar and R Rihawi and R Gutierrez-Osuna},
url = {https://ieeexplore.ieee.org/document/8319498},
year = {2020},
date = {2020-12-02},
journal = {IEEE Transactions on Affective Computing},
volume = {11},
number = {3},
pages = {519-531},
keywords = {Electrodermal activity, Games, Health, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
Zaman, S.; Wesley, A.; Silva, D. Rodrigo Da Cunha; Buddharaju, P.; Akbar, F.; Gao, G.; Mark, G.; Gutierrez-Osuna, R.; Pavlidis, I. Stress and productivity patterns of interrupted, synergistic, and antagonistic office activities Journal Article In: Scientific Data, vol. 6, no. 1, 2020. @article{zaman2019scientificdata,
title = {Stress and productivity patterns of interrupted, synergistic, and antagonistic office activities},
author = {S. Zaman and A. Wesley and D. Rodrigo Da Cunha Silva and P. Buddharaju and F. Akbar and G. Gao and G. Mark and R. Gutierrez-Osuna and I. Pavlidis},
url = {https://www.nature.com/articles/s41597-019-0249-5
https://psi.engr.tamu.edu/wp-content/uploads/2020/04/shaila2019scientificdata.pdf},
year = {2020},
date = {2020-11-08},
journal = {Scientific Data},
volume = {6},
number = {1},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
Blank, C.; Zaman, S.; Wesley, A.; Tsiamyrtzis, P.; Silva, D. R. Da Cunha; Gutierrez-Osuna, R.; Mark, G.; Pavlidis, I. Emotional Footprints of Email Interruptions Proceedings Article In: Proc. CHI, 2020. @inproceedings{blank-2020-chi,
title = {Emotional Footprints of Email Interruptions},
author = {C. Blank and S. Zaman and A. Wesley and P. Tsiamyrtzis and D. R. Da Cunha Silva and R. Gutierrez-Osuna and G. Mark and I. Pavlidis},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2020/06/3313831.3376282.pdf},
year = {2020},
date = {2020-04-25},
booktitle = {Proc. CHI},
keywords = {Electrodermal activity, Health, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2019
|
Akbar, F.; Mark, G.; Pavlidis, I.; Gutierrez-Osuna, R. An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work Journal Article In: Sensors, vol. 19, 2019. @article{akbar2019sensors,
title = {An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work},
author = {F. Akbar and G. Mark and I. Pavlidis and R. Gutierrez-Osuna},
url = {https://www.mdpi.com/1424-8220/19/17/3766
https://psi.engr.tamu.edu/wp-content/uploads/2020/04/akbar2019sensors.pdf},
year = {2019},
date = {2019-08-30},
journal = {Sensors},
volume = {19},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
Parnandi, A; Gutierrez-Osuna, R Visual Biofeedback and Game Adaptation in Relaxation Skill Transfer Journal Article In: IEEE Transactions on Affective Computing, vol. 10, no. 2, pp. 276 - 289, 2019. @article{parnandi21017tac,
title = {Visual Biofeedback and Game Adaptation in Relaxation Skill Transfer},
author = {A Parnandi and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2019/06/avinash-2019-tac.pdf},
year = {2019},
date = {2019-05-17},
journal = {IEEE Transactions on Affective Computing},
volume = {10},
number = {2},
pages = {276 - 289},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
Akbar, F.; Bayraktaroglu, A. E.; Gao, G.; Grover, T.; Mark, G.; Storer, K.; Silva, D. R. Da Cunha; Gutierrez-Osuna, R.; Wang, Z.; Buddharaju, P.; Jones, N. Cooper; Pavlidis, I.; Wesley, A.; S. Zaman, Email Makes You Sweat: Examining Email Interruptions and Stress with Thermal Imaging Proceedings Article In: Proc. CHI, 2019. @inproceedings{akbar-2019-hci,
title = {Email Makes You Sweat: Examining Email Interruptions and Stress with Thermal Imaging},
author = {F. Akbar and A. E. Bayraktaroglu and G. Gao and T. Grover and G. Mark and K. Storer and D. R. Da Cunha Silva and R. Gutierrez-Osuna and Z. Wang and P. Buddharaju and N. Cooper Jones and I. Pavlidis and A. Wesley and S. Zaman, },
url = {https://psi.engr.tamu.edu/wp-content/uploads/2019/06/paper668.pdf
https://dl.acm.org/citation.cfm?id=3300898},
year = {2019},
date = {2019-05-04},
booktitle = {Proc. CHI},
journal = {Proc. CHI 2019},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2018
|
Wang, Z; Parnandi, A; Gutierrez-Osuna, R BioPad: Leveraging off-the-Shelf Video Games for Stress Self-Regulation Journal Article In: IEEE Journal of Biomedical and Health Informatics, in press, 2018. @article{wang2018jbhi,
title = {BioPad: Leveraging off-the-Shelf Video Games for Stress Self-Regulation},
author = {Z Wang and A Parnandi and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/wang2018jbhi.pdf},
year = {2018},
date = {2018-01-01},
journal = {IEEE Journal of Biomedical and Health Informatics, in press},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
2017
|
Parnandi, A; Gutierrez-Osuna, R Physiological modalities for relaxation skill transfer in biofeedback games Journal Article In: Journal of Biomedical and Health Informatics, vol. in press, 2017. @article{parnandi2017jbhi,
title = {Physiological modalities for relaxation skill transfer in biofeedback games},
author = {A Parnandi and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/avinash2017jbhi.pdf},
year = {2017},
date = {2017-03-01},
journal = {Journal of Biomedical and Health Informatics},
volume = {in press},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
2015
|
Bhandari, R; Parnandi, A; Shipp, E; Ahmed, B; Gutierrez-Osuna, R Music-based respiratory biofeedback in visually-demanding tasks Proceedings Article In: 15th International Conference on New Interfaces for Musical Expression (NIME), 2015. @inproceedings{Bhandari2015nime,
title = {Music-based respiratory biofeedback in visually-demanding tasks},
author = {R Bhandari and A Parnandi and E Shipp and B Ahmed and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/Bhandari2015nime.pdf},
year = {2015},
date = {2015-05-31},
urldate = {2015-05-31},
booktitle = {15th International Conference on New Interfaces for Musical Expression (NIME)},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2014
|
Al-Rihawi, R; Ahmed, B; Gutierrez-Osuna, R Dodging Stress With A Personalized Biofeedback Game Proceedings Article In: Proc. CHI-PLAY, 2014. @inproceedings{rami2014chiplay,
title = {Dodging Stress With A Personalized Biofeedback Game},
author = {R Al-Rihawi and B Ahmed and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/rami2014chiplay.pdf},
year = {2014},
date = {2014-10-19},
booktitle = {Proc. CHI-PLAY},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Parnandi, A; Gutierrez-Osuna, R A Comparative Study of Game Mechanics and Control Laws for an Adaptive Physiological Game Journal Article In: Journal on Multimodal User Interfaces, 2014. @article{avinash2014jmui,
title = {A Comparative Study of Game Mechanics and Control Laws for an Adaptive Physiological Game},
author = {A Parnandi and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/avinash2014jmui.pdf},
year = {2014},
date = {2014-04-29},
journal = {Journal on Multimodal User Interfaces},
keywords = {Electrodermal activity, Games, Health, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
|
2013
|
Parnandi, A; Ahmed, B; Shipp, E; Gutierrez-Osuna, R Chill-Out: Relaxation training through respiratory biofeedback in a mobile casual game Conference Fifth International Conference on Mobile Computing, Applications and Services (MobiCASE 2013), 2013. @conference{avimobicase2013,
title = {Chill-Out: Relaxation training through respiratory biofeedback in a mobile casual game},
author = {A Parnandi and B Ahmed and E Shipp and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/avimobicase2013.pdf},
year = {2013},
date = {2013-11-07},
booktitle = {Fifth International Conference on Mobile Computing, Applications and Services (MobiCASE 2013)},
keywords = {Electrodermal activity, Games, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {conference}
}
|
Parnandi, A; Son, Y; Gutierrez-Osuna, R A Control-Theoretic Approach to Adaptive Physiological Games Conference Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), 2013. @conference{avigameacii,
title = {A Control-Theoretic Approach to Adaptive Physiological Games},
author = {A Parnandi and Y Son and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/avigameacii.pdf},
year = {2013},
date = {2013-09-02},
booktitle = {Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII)},
keywords = {Electrodermal activity, Games, Health, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {conference}
}
|
2012
|
Son, Y; Parnandi, A; Gutierrez-Osuna, R A Control-Theoretic Approach to Adaptive Physiological Games Technical Report 2012. @techreport{son2012techreport,
title = {A Control-Theoretic Approach to Adaptive Physiological Games},
author = {Y Son and A Parnandi and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/son2012techreport.pdf},
year = {2012},
date = {2012-09-21},
abstract = {This paper presents an adaptive biofeedback videogame
that aims to maintain the player’s arousal level at an
optimum level by monitoring physiological signals and
manipulating game difficulty accordingly. We use concepts
from classical control theory to model the interaction
between human physiology and game difficulty during
game play. Based on this control model, we have developed
a real-time car-racing game with adaptive game mechanics.
Specifically, we utilized car speed, road visibility, and
steering jitter as three mechanisms to manipulate game
difficulty. We propose quantitative measures to characterize
the extent to which these three game adaptations can
manipulate the player’s arousal. For this purpose, we used
electrodermal activity (EDA) as a physiological correlate of
arousal. We have validated our approach by conducting
experimental trials with 20 subjects in both open-loop (no
feedback) and closed-loop (negative feedback) conditions.
Our results show statistically significant differences among
the three game mechanics in terms of their effectiveness.
Specifically, manipulating car speed provides higher
arousal levels than modulating road visibility or vehicle
steering. Finally, we discuss the theoretical and practical
implications of our approach},
keywords = {Electrodermal activity, Games, Health, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {techreport}
}
This paper presents an adaptive biofeedback videogame
that aims to maintain the player’s arousal level at an
optimum level by monitoring physiological signals and
manipulating game difficulty accordingly. We use concepts
from classical control theory to model the interaction
between human physiology and game difficulty during
game play. Based on this control model, we have developed
a real-time car-racing game with adaptive game mechanics.
Specifically, we utilized car speed, road visibility, and
steering jitter as three mechanisms to manipulate game
difficulty. We propose quantitative measures to characterize
the extent to which these three game adaptations can
manipulate the player’s arousal. For this purpose, we used
electrodermal activity (EDA) as a physiological correlate of
arousal. We have validated our approach by conducting
experimental trials with 20 subjects in both open-loop (no
feedback) and closed-loop (negative feedback) conditions.
Our results show statistically significant differences among
the three game mechanics in terms of their effectiveness.
Specifically, manipulating car speed provides higher
arousal levels than modulating road visibility or vehicle
steering. Finally, we discuss the theoretical and practical
implications of our approach |
Alamudun, F; Choi, J; Gutierrez-Osuna, R; Khan, H; Ahmed, B Removal of Subject-Dependent and Activity-Dependent Variation in Physiological Measures of Stress Conference Proceedings of Pervasive Computing Technologies for Healthcare, 2012, ISBN: 978-1-936968-43-5. @conference{alamudun2012phealth,
title = {Removal of Subject-Dependent and Activity-Dependent Variation in Physiological Measures of Stress},
author = {F Alamudun and J Choi and R Gutierrez-Osuna and H Khan and B Ahmed},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/alamudun2012phealth.pdf},
isbn = {978-1-936968-43-5},
year = {2012},
date = {2012-05-21},
booktitle = {Proceedings of Pervasive Computing Technologies for Healthcare},
pages = {115},
abstract = {The ability to monitor stress levels in daily life can provide valuable information to patients and their caretakers, help identify potential stressors, determine appropriate interventions, and monitor their effectiveness. Wearable sensor technology makes it now possible to measure non-invasively a number of physiological correlates of stress, from skin conductance to heart rate variability. These measures, however, show large individual differences and are also correlated with the physical activity of the subject. In this paper, we propose two multivariate signal processing techniques to reduce the effect of both forms of interference. The first method is an unsupervised technique that removes any systematic variation that is orthogonal to the dependent variable, in this case physiological stress. In contrast, the second method is a supervised technique that first projects the data into a subspace that emphasizes these systematic variations, and then removes them from the data. The two methods were validated on an experimental dataset containing physiological recordings from multiple subjects performing physical and/or mental activities. When compared to z-score normalization, the standard method for removing individual differences, our methods can reduce stress prediction errors by as much as 50%.},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {conference}
}
The ability to monitor stress levels in daily life can provide valuable information to patients and their caretakers, help identify potential stressors, determine appropriate interventions, and monitor their effectiveness. Wearable sensor technology makes it now possible to measure non-invasively a number of physiological correlates of stress, from skin conductance to heart rate variability. These measures, however, show large individual differences and are also correlated with the physical activity of the subject. In this paper, we propose two multivariate signal processing techniques to reduce the effect of both forms of interference. The first method is an unsupervised technique that removes any systematic variation that is orthogonal to the dependent variable, in this case physiological stress. In contrast, the second method is a supervised technique that first projects the data into a subspace that emphasizes these systematic variations, and then removes them from the data. The two methods were validated on an experimental dataset containing physiological recordings from multiple subjects performing physical and/or mental activities. When compared to z-score normalization, the standard method for removing individual differences, our methods can reduce stress prediction errors by as much as 50%. |
Choi, J; Ahmed, B; Gutierrez-Osuna, R Development and Evaluation of an Ambulatory Stress Monitor Based on Wearable Sensors Journal Article In: IEEE Transactions on Information Technology in Biomedicine, no. 99, pp. 279 - 286, 2012. @article{choi2012titb,
title = {Development and Evaluation of an Ambulatory Stress Monitor Based on Wearable Sensors},
author = {J Choi and B Ahmed and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/choi2012titb.pdf},
year = {2012},
date = {2012-03-01},
journal = {IEEE Transactions on Information Technology in Biomedicine},
number = {99},
pages = {279 - 286},
publisher = {IEEE},
abstract = {Chronic stress is endemic to modern society. However, as it is unfeasible for physicians to continuously monitor stress levels, its diagnosis is nontrivial. Wireless body sensor networks offer opportunities to ubiquitously detect and monitor mental stress levels, enabling improved diagnosis, and early treatment. This article describes the development of a wearable sensor platform to monitor a number of physiological correlates of mental stress. We discuss tradeoffs in both system design and sensor selection to balance information content and wearability. Using experimental signals collected from the wearable sensor, we describe a selected number of physiological features that show good correlation with mental stress. In particular, we propose a new spectral feature that estimates the balance of the autonomic nervous system by combining information from the power spectral density of respiration and heart rate variability. We validate the effectiveness of our approach on a binary discrimination problem when subjects are placed under two psychophysiological conditions: mental stress and relaxation. When used in a logistic regression model, our feature set is able to discriminate between these two mental states with a success rate of 81% across subjects.},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {article}
}
Chronic stress is endemic to modern society. However, as it is unfeasible for physicians to continuously monitor stress levels, its diagnosis is nontrivial. Wireless body sensor networks offer opportunities to ubiquitously detect and monitor mental stress levels, enabling improved diagnosis, and early treatment. This article describes the development of a wearable sensor platform to monitor a number of physiological correlates of mental stress. We discuss tradeoffs in both system design and sensor selection to balance information content and wearability. Using experimental signals collected from the wearable sensor, we describe a selected number of physiological features that show good correlation with mental stress. In particular, we propose a new spectral feature that estimates the balance of the autonomic nervous system by combining information from the power spectral density of respiration and heart rate variability. We validate the effectiveness of our approach on a binary discrimination problem when subjects are placed under two psychophysiological conditions: mental stress and relaxation. When used in a logistic regression model, our feature set is able to discriminate between these two mental states with a success rate of 81% across subjects. |
2010
|
Choi, J; Ahmed, B; Gutierrez-Osuna, R Ambulatory Stress Monitoring with Minimally-Invasive Wearable Sensors Technical Report 2010. @techreport{choi10techreport,
title = {Ambulatory Stress Monitoring with Minimally-Invasive Wearable Sensors},
author = {J Choi and B Ahmed and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/choi2010techreport.pdf},
year = {2010},
date = {2010-11-10},
abstract = {Chronic stress can have serious health consequences, and is a leading risk factor for heart diseases, diabetes, asthma and depression. This article presents a minimally-invasive and wireless wearable sensor platform that can be used to monitor a number of physiological variables known to correlate with stress. We discuss the system design and sensor selection, both of which were guided as a tradeoff between information content and wearability. The platform is thoroughly evaluated through a battery of tests that elicit mental workload and physical activity, as well as through subjective assessments of comfort. Our results indicate that the sensor system is responsive to three broad types of factors: mental workload, posture and physical activity. We also describe a system-identification method that improves detection of mental stress by removing respiratory influences on heart rate.},
keywords = {Electrodermal activity, Health, Heart rate variability, Stress, Wearable sensors},
pubstate = {published},
tppubtype = {techreport}
}
Chronic stress can have serious health consequences, and is a leading risk factor for heart diseases, diabetes, asthma and depression. This article presents a minimally-invasive and wireless wearable sensor platform that can be used to monitor a number of physiological variables known to correlate with stress. We discuss the system design and sensor selection, both of which were guided as a tradeoff between information content and wearability. The platform is thoroughly evaluated through a battery of tests that elicit mental workload and physical activity, as well as through subjective assessments of comfort. Our results indicate that the sensor system is responsive to three broad types of factors: mental workload, posture and physical activity. We also describe a system-identification method that improves detection of mental stress by removing respiratory influences on heart rate. |