scholarly journals Guidelines for Feature Matching Assessment of Brain–Computer Interfaces for Augmentative and Alternative Communication

2018 ◽  
Vol 27 (3) ◽  
pp. 950-964 ◽  
Author(s):  
Kevin M. Pitt ◽  
Jonathan S. Brumberg
Keyword(s):  
Motor Imagery ◽  
Augmentative And Alternative Communication ◽  
Feature Matching ◽  
Full Range ◽  
Brain Computer Interfaces ◽  
Alternative Communication ◽  
Access Methods ◽  
Computer Interfaces ◽  
Sensory Motor ◽  
Selection Of

Purpose Brain–computer interfaces (BCIs) can provide access to augmentative and alternative communication (AAC) devices using neurological activity alone without voluntary movements. As with traditional AAC access methods, BCI performance may be influenced by the cognitive–sensory–motor and motor imagery profiles of those who use these devices. Therefore, we propose a person-centered, feature matching framework consistent with clinical AAC best practices to ensure selection of the most appropriate BCI technology to meet individuals' communication needs. Method The proposed feature matching procedure is based on the current state of the art in BCI technology and published reports on cognitive, sensory, motor, and motor imagery factors important for successful operation of BCI devices. Results Considerations for successful selection of BCI for accessing AAC are summarized based on interpretation from a multidisciplinary team with experience in AAC, BCI, neuromotor disorders, and cognitive assessment. The set of features that support each BCI option are discussed in a hypothetical case format to model possible transition of BCI research from the laboratory into clinical AAC applications. Conclusions This procedure is an initial step toward consideration of feature matching assessment for the full range of BCI devices. Future investigations are needed to fully examine how person-centered factors influence BCI performance across devices.

scholarly journals Brain–Computer Interfaces for Augmentative and Alternative Communication: A Tutorial

2018 ◽  
Vol 27 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Jonathan S. Brumberg ◽  
Kevin M. Pitt ◽  
Alana Mantie-Kozlowski ◽  
Jeremy D. Burnison
Keyword(s):  
Clinical Application ◽  
Augmentative And Alternative Communication ◽  
Scope Of Practice ◽  
Brain Computer Interfaces ◽  
Alternative Communication ◽  
Access Methods ◽  
Computer Interfaces ◽  
Current State ◽  
Starting Point ◽  
Areas Of Interest

Purpose Brain–computer interfaces (BCIs) have the potential to improve communication for people who require but are unable to use traditional augmentative and alternative communication (AAC) devices. As BCIs move toward clinical practice, speech-language pathologists (SLPs) will need to consider their appropriateness for AAC intervention. Method This tutorial provides a background on BCI approaches to provide AAC specialists foundational knowledge necessary for clinical application of BCI. Tutorial descriptions were generated based on a literature review of BCIs for restoring communication. Results The tutorial responses directly address 4 major areas of interest for SLPs who specialize in AAC: (a) the current state of BCI with emphasis on SLP scope of practice (including the subareas: the way in which individuals access AAC with BCI, the efficacy of BCI for AAC, and the effects of fatigue), (b) populations for whom BCI is best suited, (c) the future of BCI as an addition to AAC access strategies, and (d) limitations of BCI. Conclusion Current BCIs have been designed as access methods for AAC rather than a replacement; therefore, SLPs can use existing knowledge in AAC as a starting point for clinical application. Additional training is recommended to stay updated with rapid advances in BCI.

scholarly journals Noninvasive Brain–Computer Interfaces for Augmentative and Alternative Communication

2014 ◽  
Vol 7 ◽  
pp. 31-49 ◽  
Author(s):  
Murat Akcakaya ◽  
Betts Peters ◽  
Mohammad Moghadamfalahi ◽  
Aimee R. Mooney ◽  
Umut Orhan ◽  
...  
Keyword(s):  
Augmentative And Alternative Communication ◽  
Brain Computer Interfaces ◽  
Alternative Communication ◽  
Computer Interfaces

Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces

2017 ◽  
Vol 29 (6) ◽  
pp. 1631-1666 ◽  
Author(s):  
Takashi Uehara ◽  
Matteo Sartori ◽  
Toshihisa Tanaka ◽  
Simone Fiori
Keyword(s):  
Motor Imagery ◽  
Tangent Space ◽  
Covariance Matrices ◽  
Space Mapping ◽  
Brain Computer Interfaces ◽  
Robust Estimators ◽  
Computer Interfaces ◽  
Sample Covariance ◽  
Reference Matrix ◽  
Selection Of

The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery–based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)–based MI-BCI. Tangent space mapping is a powerful method of feature extraction and strongly depends on the selection of a reference covariance matrix. In general, the observed signals may include outliers; therefore, taking the geometric mean of SCMs as the reference matrix may not be the best choice. In order to deal with the effects of outliers, robust estimators have to be used. In particular, we discuss and test the use of geometric medians and trimmed averages (defined on the basis of several metrics) as robust estimators. The main idea behind trimmed averages is to eliminate data that exhibit the largest distance from the average covariance calculated on the basis of all available data. The results of the experiments show that while the geometric medians show little differences from conventional methods in terms of classification accuracy in the classification of electroencephalographic recordings, the trimmed averages show significant improvement for all subjects.

New AAC Access Strategy for Gesture Tracking: A Technical Note

2012 ◽  
Vol 21 (1) ◽  
pp. 11-16 ◽  
Author(s):  
Susan Fager ◽  
Tom Jakobs ◽  
David Beukelman ◽  
Tricia Ternus ◽  
Haylee Schley
Keyword(s):  
Augmentative And Alternative Communication ◽  
Technical Note ◽  
Head Tracking ◽  
Alternative Communication ◽  
Access Methods ◽  
Cord Injury ◽  
Physical Limitations ◽  
Gesture Tracking ◽  
Communication Needs ◽  
Tracking Device

Abstract This article summarizes the design and evaluation of a new augmentative and alternative communication (AAC) interface strategy for people with complex communication needs and severe physical limitations. This strategy combines typing, gesture recognition, and word prediction to input text into AAC software using touchscreen or head movement tracking access methods. Eight individuals with movement limitations due to spinal cord injury, amyotrophic lateral sclerosis, polio, and Guillain Barre syndrome participated in the evaluation of the prototype technology using a head-tracking device. Fourteen typical individuals participated in the evaluation of the prototype using a touchscreen.

Word-Finding Support From Mobile Technology Benefits a Woman With Aphasia

2015 ◽  
Vol 24 (1) ◽  
pp. 26-39 ◽  
Author(s):  
Yvonne Gillette
Keyword(s):  
Mobile Technology ◽  
Clinical Education ◽  
Augmentative And Alternative Communication ◽  
Feature Matching ◽  
Mobile Technologies ◽  
Alternative Communication ◽  
Alternative Intervention ◽  
Communication Assessment ◽  
Word Finding ◽  
Intervention Costs

Mobile technology provides a solution for individuals who require augmentative and alternative intervention. Principles of augmentative and alternative communication assessment and intervention, such as feature matching and the participation model, developed with dedicated speech-generating devices can be applied to these generic mobile technologies with success. This article presents a clinical review of an adult with aphasia who reached her goals for greater communicative participation through mobile technology. Details presented include device selection, sequence of intervention, and funding issues related to device purchase and intervention costs. Issues related to graduate student clinical education are addressed. The purpose of the article is to encourage clinicians to consider mobile technology when intervening with an individual diagnosed with mild receptive and moderate expressive aphasia featuring word-finding difficulties.

The Evolution of Augmentative Communication and the Importance of Alternate Access

2011 ◽  
Vol 20 (1) ◽  
pp. 34-37 ◽  
Author(s):  
David Chapple
Keyword(s):  
Augmentative And Alternative Communication ◽  
Cell Phone ◽  
Handheld Devices ◽  
Alternative Communication ◽  
Access Methods ◽  
The Past ◽  
Communication Device ◽  
Internet Browser ◽  
A Cell ◽  
Development Of Language

Abstract Over the past 20 years, there have been many advances in the computer industry as well as in augmentative and alternative communication (AAC) devices. Computers are becoming more compact and have multiple purposes, such as the iPhone, which is a cell phone, mp3 player, and an Internet browser. AAC devices also have evolved to become multi-purpose devices; the most sophisticated devices have functionality similar to the iPhone and iPod. Recently, the idea of having the iPhone and iPad as a communication device was initiated with the development of language applications specifically for this format. It might be true that this idea could become the future of AAC devices; however, there are major access issues to overcome before the idea is a reality. This article will chronicle advancements in AAC devices, specifically on access methods, throughout the years, towards the transition to handheld devices. The newest technologies hold much promise with both features and affordability factors being highly attractive. Yet, these technologies must be made to incorporate alternate access if they are to meet their fullest potential as AAC tools.

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