2017
Elgin-Skye McLaren, Alissa N. Antle. 2017. Exploring and Evaluating Sound for Helping Children Self-Regulate with a Brain-Computer Application Proceedings Article . In Proceedings of the 2017 Conference on Interaction Design and Children, IDC '17 Association for Computing Machinery, Stanford, California, USA, 393–398, .
@inproceedings{10.1145/3078072.3084299,
title = {Exploring and Evaluating Sound for Helping Children Self-Regulate with a Brain-Computer Application},
author = {Elgin-Skye McLaren and Alissa N. Antle},
url = {https://doi.org/10.1145/3078072.3084299},
doi = {10.1145/3078072.3084299},
isbn = {9781450349215},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of the 2017 Conference on Interaction Design and Children},
pages = {393–398},
publisher = {Association for Computing Machinery},
address = {Stanford, California, USA},
series = {IDC '17},
abstract = {Children in North America are more likely to suffer from attentional challenges than any other mental health issue. Studies suggest that neurofeedback treatments may be useful for helping these children learn to self-regulate. Applying neurofeedback treatments in real-world, school settings poses a challenge, however, as these environments are often noisy and filled with distractions. The addition of ambient audio to neurofeedback systems may help reduce these disruptions. Further, research suggests that certain auditory treatments, such as binaural beats and white noise, may improve children's focus and aid memory recall. In the following paper we present the theories supporting this idea as well as a mixed methods framework for evaluating whether sound can help children focus while learning to self-regulate using a neurofeedback system. Specifically, we wish to investigate whether these treatments may help children (1) achieve an attentive state sooner and (2) maintain an attentive state for longer, when compared to the same system without sound.},
keywords = {adhd, brain-computer interfacing, children, design, neurofeedback, sound},
pubstate = {published},
tppubtype = {inproceedings}
}
Children in North America are more likely to suffer from attentional challenges than any other mental health issue. Studies suggest that neurofeedback treatments may be useful for helping these children learn to self-regulate. Applying neurofeedback treatments in real-world, school settings poses a challenge, however, as these environments are often noisy and filled with distractions. The addition of ambient audio to neurofeedback systems may help reduce these disruptions. Further, research suggests that certain auditory treatments, such as binaural beats and white noise, may improve children's focus and aid memory recall. In the following paper we present the theories supporting this idea as well as a mixed methods framework for evaluating whether sound can help children focus while learning to self-regulate using a neurofeedback system. Specifically, we wish to investigate whether these treatments may help children (1) achieve an attentive state sooner and (2) maintain an attentive state for longer, when compared to the same system without sound.
2015
Alissa N. Antle, Leslie Chesick, Aaron Levisohn, Srilekha Kirshnamachari Sridharan, Perry Tan. 2015. Using Neurofeedback to Teach Self-Regulation to Children Living in Poverty Proceedings Article . In Proceedings of the 14th International Conference on Interaction Design and Children, IDC '15 Association for Computing Machinery, Boston, Massachusetts, 119–128, .
Abstract | BibTeX | Tags: brain computer interfaces, children, developing countries, evaluation, games for learning, neurofeedback, self-regulation
@inproceedings{10.1145/2771839.2771852,
title = {Using Neurofeedback to Teach Self-Regulation to Children Living in Poverty},
author = {Alissa N. Antle and Leslie Chesick and Aaron Levisohn and Srilekha Kirshnamachari Sridharan and Perry Tan},
url = {https://doi-org.proxy.lib.sfu.ca/10.1145/2771839.2771852},
doi = {10.1145/2771839.2771852},
isbn = {9781450335904},
year = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the 14th International Conference on Interaction Design and Children},
pages = {119–128},
publisher = {Association for Computing Machinery},
address = {Boston, Massachusetts},
series = {IDC '15},
abstract = {In this paper we describe a neuro-feedback system and applications we designed and deployed to help vulnerable children at an NGO-funded school, called Nepal House Kaski, in Pokhara, Nepal. The system, called Mind-Full, enables traumatized children to learn and practice self-regulation by playing simple, culturally appropriate games using an EEG headset connected to an interactive tablet. Children can interact with Mind-Full using body actions that may change their physiology and brain states, which are sensed by the EEG headset and used as input to the games. One of the key challenges was to build an application that the children could immediately understand how to use when they are illiterate, don't speak English and have no computer experience. We describe Mind-Full and highlight the design principles we used to meet these constraints. We report on a subset of findings from a 14-week field experiment in which we use a mixed-methods approach to determine if children improved their ability to self-regulate during gameplay as well as in the classroom, playground and in therapy sessions. Findings from quantitative and qualitative assessment measures suggest that the treatment group significantly improved their ability to calm down and focus in a variety of contexts.},
keywords = {brain computer interfaces, children, developing countries, evaluation, games for learning, neurofeedback, self-regulation},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we describe a neuro-feedback system and applications we designed and deployed to help vulnerable children at an NGO-funded school, called Nepal House Kaski, in Pokhara, Nepal. The system, called Mind-Full, enables traumatized children to learn and practice self-regulation by playing simple, culturally appropriate games using an EEG headset connected to an interactive tablet. Children can interact with Mind-Full using body actions that may change their physiology and brain states, which are sensed by the EEG headset and used as input to the games. One of the key challenges was to build an application that the children could immediately understand how to use when they are illiterate, don't speak English and have no computer experience. We describe Mind-Full and highlight the design principles we used to meet these constraints. We report on a subset of findings from a 14-week field experiment in which we use a mixed-methods approach to determine if children improved their ability to self-regulate during gameplay as well as in the classroom, playground and in therapy sessions. Findings from quantitative and qualitative assessment measures suggest that the treatment group significantly improved their ability to calm down and focus in a variety of contexts.