2024
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Rho, Gianluca; Callara, Alejandro Luis; Scilingo, Enzo Pasquale; Greco, Alberto; Bonfiglio, Luca Habituation of Central and Electrodermal Responses to an Auditory Two-Stimulus Oddball Paradigm Journal Article In: Sensors, vol. 24, no. 15, pp. 5053, 2024. @article{rho2024habituation,
title = {Habituation of Central and Electrodermal Responses to an Auditory Two-Stimulus Oddball Paradigm},
author = {Gianluca Rho and Alejandro Luis Callara and Enzo Pasquale Scilingo and Alberto Greco and Luca Bonfiglio},
doi = {https://doi.org/10.3390/s24155053},
year = {2024},
date = {2024-08-04},
urldate = {2024-01-01},
journal = {Sensors},
volume = {24},
number = {15},
pages = {5053},
publisher = {MDPI},
abstract = {The orienting reaction (OR) towards a new stimulus is subject to habituation, i.e., progressively attenuates with stimulus repetition. The skin conductance responses (SCRs) are known to represent a reliable measure of OR at the peripheral level. Yet, it is still a matter of debate which of the P3 subcomponents is the most likely to represent the central counterpart of the OR. The aim of the present work was to study habituation, recovery, and dishabituation phenomena intrinsic to a two-stimulus auditory oddball paradigm, one of the most-used paradigms both in research and clinic, by simultaneously recording SCRs and P3 in twenty healthy volunteers. Our findings show that the target stimulus was capable of triggering a more marked OR, as indexed by both SCRs and P3, compared to the standard stimulus, that could be due to its affective saliency and relevance for task completion; the application of temporal principal components analysis (PCA) to the P3 complex allowed us to identify several subcomponents including both early and late P3a (eP3a; lP3a), P3b, novelty P3 (nP3), and both a positive and a negative Slow Wave (+SW; −SW). Particularly, lP3a and P3b subcomponents showed a similar behavior to that observed for SCRs , suggesting them as central counterparts of OR. Finally, the P3 evoked by the first standard stimulus after the target showed a significant dishabituation phenomenon which could represent a sign of the local stimulus change. However, it did not reach a sufficient level to trigger an SCR/OR since it did not represent a salient event in the context of the task.},
keywords = {DSI-24, Multimodal},
pubstate = {published},
tppubtype = {article}
}
The orienting reaction (OR) towards a new stimulus is subject to habituation, i.e., progressively attenuates with stimulus repetition. The skin conductance responses (SCRs) are known to represent a reliable measure of OR at the peripheral level. Yet, it is still a matter of debate which of the P3 subcomponents is the most likely to represent the central counterpart of the OR. The aim of the present work was to study habituation, recovery, and dishabituation phenomena intrinsic to a two-stimulus auditory oddball paradigm, one of the most-used paradigms both in research and clinic, by simultaneously recording SCRs and P3 in twenty healthy volunteers. Our findings show that the target stimulus was capable of triggering a more marked OR, as indexed by both SCRs and P3, compared to the standard stimulus, that could be due to its affective saliency and relevance for task completion; the application of temporal principal components analysis (PCA) to the P3 complex allowed us to identify several subcomponents including both early and late P3a (eP3a; lP3a), P3b, novelty P3 (nP3), and both a positive and a negative Slow Wave (+SW; −SW). Particularly, lP3a and P3b subcomponents showed a similar behavior to that observed for SCRs , suggesting them as central counterparts of OR. Finally, the P3 evoked by the first standard stimulus after the target showed a significant dishabituation phenomenon which could represent a sign of the local stimulus change. However, it did not reach a sufficient level to trigger an SCR/OR since it did not represent a salient event in the context of the task. |
2023
|
Chiossi, Francesco; Ou, Changkun; Mayer, Sven Exploring Physiological Correlates of Visual Complexity Adaptation: Insights from EDA, ECG, and EEG Data for Adaptation Evaluation in VR Adaptive Systems Journal Article In: 2023. @article{chiossi2023exploring,
title = {Exploring Physiological Correlates of Visual Complexity Adaptation: Insights from EDA, ECG, and EEG Data for Adaptation Evaluation in VR Adaptive Systems},
author = {Francesco Chiossi and Changkun Ou and Sven Mayer},
url = {https://www.researchgate.net/profile/Francesco-Chiossi/publication/369033584_Exploring_Physiological_Correlates_of_Visual_Complexity_Adaptation_Insights_from_EDA_ECG_and_EEG_Data_for_Adaptation_Evaluation_in_VR_Adaptive_Systems/links/64064d5d0cf1030a567a05fb/Exploring-Physiological-Correlates-of-Visual-Complexity-Adaptation-Insights-from-EDA-ECG-and-EEG-Data-for-Adaptation-Evaluation-in-VR-Adaptive-Systems.pdf},
year = {2023},
date = {2023-04-23},
urldate = {2023-04-23},
abstract = {Physiologically-adaptive Virtual Reality can drive interactions and adjust virtual content to better fit users’ needs and support specific goals. However, the complexity of psychophysiological inference hinders efficient adaptation as the relationship between cognitive and physiological features rarely show one-to-one correspondence. Therefore, it is necessary to employ multimodal approaches to evaluate the effect of adaptations. In this work, we analyzed a multimodal dataset (EEG, ECG, and EDA) acquired during interaction with a VR-adaptive system that employed EDA as input for adaptation of secondary task difficulty. We evaluated the effect of dynamic adjustments on different physiological features and their correlation. Our results show that when the adaptive system increased the secondary task difficulty, theta, beta, and phasic EDA features increased. Moreover, we found a high correlation between theta, alpha, and beta oscillations during difficulty adjustments. Our results show how specific EEG and EDA features can be employed for evaluating VR adaptive systems.
},
keywords = {DSI-7, Multimodal, VR},
pubstate = {published},
tppubtype = {article}
}
Physiologically-adaptive Virtual Reality can drive interactions and adjust virtual content to better fit users’ needs and support specific goals. However, the complexity of psychophysiological inference hinders efficient adaptation as the relationship between cognitive and physiological features rarely show one-to-one correspondence. Therefore, it is necessary to employ multimodal approaches to evaluate the effect of adaptations. In this work, we analyzed a multimodal dataset (EEG, ECG, and EDA) acquired during interaction with a VR-adaptive system that employed EDA as input for adaptation of secondary task difficulty. We evaluated the effect of dynamic adjustments on different physiological features and their correlation. Our results show that when the adaptive system increased the secondary task difficulty, theta, beta, and phasic EDA features increased. Moreover, we found a high correlation between theta, alpha, and beta oscillations during difficulty adjustments. Our results show how specific EEG and EDA features can be employed for evaluating VR adaptive systems.
|
2012
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McDonald, Neil J; Anumula, Harini A; Duff, Eric; Soussou, Walid Noncontact ECG system for unobtrusive long-term monitoring Conference 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE 2012, ISSN: 1557-170X. @conference{mcdonald2012noncontact,
title = {Noncontact ECG system for unobtrusive long-term monitoring},
author = {Neil J McDonald and Harini A Anumula and Eric Duff and Walid Soussou},
doi = {10.1109/EMBC.2012.6346254},
issn = {1557-170X},
year = {2012},
date = {2012-11-12},
booktitle = {2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
pages = {1614--1618},
organization = {IEEE},
abstract = {This paper describes measurements made using an ECG system with QUASAR's capacitive bioelectrodes integrated into a pad system that is placed over a chair. QUASAR's capacitive bioelectrode has the property of measuring bioelectric potentials at a small separation from the body. This enables the measurement of ECG signals through fabric, without the removal of clothing or preparation of skin. The ECG was measured through the subject's clothing while the subject sat in the chair without any supporting action from the subject. The ECG pad system is an example of a high compliance system that places minimal requirements upon the subject and, consequently, can be used to generate a long-term record from ECG segments collected on a daily basis, providing valuable information on long-term trends in cardiac health.},
keywords = {Multimodal},
pubstate = {published},
tppubtype = {conference}
}
This paper describes measurements made using an ECG system with QUASAR's capacitive bioelectrodes integrated into a pad system that is placed over a chair. QUASAR's capacitive bioelectrode has the property of measuring bioelectric potentials at a small separation from the body. This enables the measurement of ECG signals through fabric, without the removal of clothing or preparation of skin. The ECG was measured through the subject's clothing while the subject sat in the chair without any supporting action from the subject. The ECG pad system is an example of a high compliance system that places minimal requirements upon the subject and, consequently, can be used to generate a long-term record from ECG segments collected on a daily basis, providing valuable information on long-term trends in cardiac health. |
2007
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Trejo, Leonard J; McDonald, Neil J; Matthews, Robert; Allison, Brendan Z Experimental design and testing of a multimodal cognitive overload classifier Journal Article In: Foundations of Augmented Cognition, vol. 2007, pp. 13–22, 2007. @article{trejo2007experimental,
title = {Experimental design and testing of a multimodal cognitive overload classifier},
author = {Leonard J Trejo and Neil J McDonald and Robert Matthews and Brendan Z Allison},
url = {https://www.researchgate.net/profile/Leonard-Trejo/publication/266524682_Experimental_Design_and_Testing_of_a_Multimodal_Cognitive_Overload_Classifier/links/5535a1650cf20ea35f10ddf0/Experimental-Design-and-Testing-of-a-Multimodal-Cognitive-Overload-Classifier.pdf},
year = {2007},
date = {2007-01-01},
journal = {Foundations of Augmented Cognition},
volume = {2007},
pages = {13--22},
publisher = {Strategic Analysis, Inc Arlington, VA},
abstract = {We report the results of an experiment designed to construct and test a robust multimodal system for automatic classification of cognitive overload. With the assistance of The Scripps Research Institute, twenty-two experienced gamers performed a first-person shooter combat simulation while multiple biosignals and performance were recorded. Signals included EEG, EOG, EMG, ECG, accuracy, and reaction time measures. A kernel partial least squares or KPLS classifier was trained to distinguish subtle differences in EEG spectra within subjects as they pertained to passive viewing, low-difficulty, and high-difficulty simulations. The KPLS classifier was supported and enhanced by algorithms for preprocessing and normalization of EEG and other biosignals. Results indicated that for some subjects, robust classifiers discriminated passive viewing from active performance with accuracies in the range of 99% to 100% and that such models were stable over two test days, using 35-70 min. of training data from Day 1 and testing on data from Day 2. In addition, for some subjects, classifiers discriminated high-difficulty simulations from low-difficulty and passive simulations with stable accuracies of 80% or better across two test days, using 35-70 min. of training data from Day 1 and testing on data from Day 2. We also tested the effect of alcohol intoxication on simulation performance and classifier accuracy. Performance was slightly altered by drinking alcohol to a blood alcohol level of 0.06%, producing more aggressive behavior than with a placebo across subjects. The KPLS classifiers showed remarkable resilience to alcohol effects, considerably less than the effects of day of testing. Not all subjects had such impressive results. To address the lack of generality across subjects, we are currently performing a modified study design that includes provisions for three calibration tasks. These calibration tasks are intended to serve as brief, simple tasks that a user could easily perform at any time as needed to
recalibrate algorithms that relate physiology to cognitive state. The tasks include a) eyes-open and eyes-closed for general EEG calibration, b) a mental arithmetic task (divide by twos or sevens) for cognitive load classification, and c) passive viewing of the combat simulation task, for calibration of engagement/disengagement of mental resources. We aim to use the data from the calibration tasks to adapt classification algorithms for variations over time and for inclusion of multiple sensor and data modalities, such as electrocardiographic, electrooculographic, and electromyographic sensor data},
keywords = {Multimodal},
pubstate = {published},
tppubtype = {article}
}
We report the results of an experiment designed to construct and test a robust multimodal system for automatic classification of cognitive overload. With the assistance of The Scripps Research Institute, twenty-two experienced gamers performed a first-person shooter combat simulation while multiple biosignals and performance were recorded. Signals included EEG, EOG, EMG, ECG, accuracy, and reaction time measures. A kernel partial least squares or KPLS classifier was trained to distinguish subtle differences in EEG spectra within subjects as they pertained to passive viewing, low-difficulty, and high-difficulty simulations. The KPLS classifier was supported and enhanced by algorithms for preprocessing and normalization of EEG and other biosignals. Results indicated that for some subjects, robust classifiers discriminated passive viewing from active performance with accuracies in the range of 99% to 100% and that such models were stable over two test days, using 35-70 min. of training data from Day 1 and testing on data from Day 2. In addition, for some subjects, classifiers discriminated high-difficulty simulations from low-difficulty and passive simulations with stable accuracies of 80% or better across two test days, using 35-70 min. of training data from Day 1 and testing on data from Day 2. We also tested the effect of alcohol intoxication on simulation performance and classifier accuracy. Performance was slightly altered by drinking alcohol to a blood alcohol level of 0.06%, producing more aggressive behavior than with a placebo across subjects. The KPLS classifiers showed remarkable resilience to alcohol effects, considerably less than the effects of day of testing. Not all subjects had such impressive results. To address the lack of generality across subjects, we are currently performing a modified study design that includes provisions for three calibration tasks. These calibration tasks are intended to serve as brief, simple tasks that a user could easily perform at any time as needed to
recalibrate algorithms that relate physiology to cognitive state. The tasks include a) eyes-open and eyes-closed for general EEG calibration, b) a mental arithmetic task (divide by twos or sevens) for cognitive load classification, and c) passive viewing of the combat simulation task, for calibration of engagement/disengagement of mental resources. We aim to use the data from the calibration tasks to adapt classification algorithms for variations over time and for inclusion of multiple sensor and data modalities, such as electrocardiographic, electrooculographic, and electromyographic sensor data |
2006
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Park, Chulsung; Chou, Pai H; Bai, Ying; Matthews, Robert; Hibbs, Andrew An ultra-wearable, wireless, low power ECG monitoring system Conference 2006 IEEE biomedical circuits and systems conference, IEEE 2006. @conference{park2006ultra,
title = {An ultra-wearable, wireless, low power ECG monitoring system},
author = {Chulsung Park and Pai H Chou and Ying Bai and Robert Matthews and Andrew Hibbs},
doi = {10.1109/BIOCAS.2006.4600353},
year = {2006},
date = {2006-11-29},
booktitle = {2006 IEEE biomedical circuits and systems conference},
pages = {241--244},
organization = {IEEE},
abstract = {Wearable electrocardiograph (ECG) monitoring systems today use electrodes that require skin preparation in advance, and require pastes or gels to make electrical contact to the skin. Moreover, they are not suitable for subjects at high levels of activity due to high noise spikes that can appear in the data. To address these problems, a new class of miniature, ultra low noise, capacitive sensor that does not require direct contact to the skin, and has comparable performance to gold standard ECG electrodes, has been developed. This paper presents a description and evaluation of a wireless version of a system based on these innovative ECG sensors. We use a wearable and ultra low power wireless sensor node called Eco. Experimental results show that the wireless interface will add minimal size and weight to the system while providing reliable, untethered operation.},
keywords = {Multimodal},
pubstate = {published},
tppubtype = {conference}
}
Wearable electrocardiograph (ECG) monitoring systems today use electrodes that require skin preparation in advance, and require pastes or gels to make electrical contact to the skin. Moreover, they are not suitable for subjects at high levels of activity due to high noise spikes that can appear in the data. To address these problems, a new class of miniature, ultra low noise, capacitive sensor that does not require direct contact to the skin, and has comparable performance to gold standard ECG electrodes, has been developed. This paper presents a description and evaluation of a wireless version of a system based on these innovative ECG sensors. We use a wearable and ultra low power wireless sensor node called Eco. Experimental results show that the wireless interface will add minimal size and weight to the system while providing reliable, untethered operation. |
