A screening protocol incorporating brain-computer interface feature matching considerations for augmentative and alternative communication

Purpose: The purpose of this article is to consider how, alongside engineering advancements, noninvasive brain–computer interface (BCI) for augmentative and alternative communication (AAC; BCI-AAC) developments can leverage implementation science to increase the clinical impact of this technology. We offer the Consolidated Framework for Implementation Research (CFIR) as a structure to help guide future BCI-AAC research. Specifically, we discuss CFIR primary domains that include intervention characteristics, the outer and inner settings, the individuals involved in the intervention, and the process of implementation, alongside pertinent subdomains including adaptability, cost, patient needs and recourses, implementation climate, other personal attributes, and the process of engaging. The authors support their view with current citations from both the AAC and BCI-AAC fields. Conclusions: The article aimed to provide thoughtful considerations for how future research may leverage the CFIR to support meaningful BCI-AAC translation for those with severe physical impairments. We believe that, although significant barriers to BCI-AAC development still exist, incorporating implementation research may be timely for the field of BCI-AAC and help account for diversity in end users, navigate implementation obstacles, and support a smooth and efficient translation of BCI-AAC technology. Moreover, the sooner clinicians, individuals who use AAC, their support networks, and engineers collectively improve BCI-AAC outcomes and the efficiency of translation, the sooner BCI-AAC may become an everyday tool in the AAC arsenal.

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

Perspectives on Augmentative and Alternative Communication ◽

10.1044/aac24.1.26 ◽

2015 ◽

Vol 24 (1) ◽

pp. 26-39 ◽

Cited By ~ 1

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.

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Guidelines for Teaching Speech-Language Pathologists About the AAC Assessment Process

Perspectives on Augmentative and Alternative Communication ◽

10.1044/aac20.3.82 ◽

2011 ◽

Vol 20 (3) ◽

pp. 82-86

Author(s):

Iris Fishman

Keyword(s):

Augmentative And Alternative Communication ◽

Communication Systems ◽

Feature Matching ◽

Assessment Process ◽

High Tech ◽

Alternative Communication ◽

Team Process ◽

Basic Principles ◽

Communication Needs ◽

The Individual

Abstract Although students may not become augmentative and alternative communication (AAC) clinical specialists, they often will work with individuals demonstrating complex communication needs who benefit from AAC. This necessitates knowledge of some basic principles of assessment including AAC assessment as a team process involving planning and implementing interventions for current and future communication needs; the inclusion of no-tech, low-tech, and high-tech communication systems; and assessing communication needs with partners in the individual's social network. The assessment also must include a capability profile and feature matching to select the appropriate components of the AAC system. Because the system we provide for today will become the system we use tomorrow, assessment must be considered an ongoing process throughout the lifespan of the individual.

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A Portable P300-Based Brain–Computer Interface as an Alternative Communication Device

10.1007/978-3-030-70316-5_61 ◽

2021 ◽

pp. 383-387

Author(s):

Víctor Martínez-Cagigal ◽

Eduardo Santamaría-Vázquez ◽

Roberto Hornero

Keyword(s):

Brain Computer Interface ◽

Computer Interface ◽

Alternative Communication ◽

Communication Device

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Behind the Scenes of Noninvasive Brain–Computer Interfaces: A Review of Electroencephalography Signals, How They Are Recorded, and Why They Matter

Perspectives of the ASHA Special Interest Groups ◽

10.1044/2019_pers-19-00059 ◽

2019 ◽

Vol 4 (6) ◽

pp. 1622-1636

Author(s):

Kevin M. Pitt ◽

Jonathan S. Brumberg ◽

Jeremy D. Burnison ◽

Jyutika Mehta ◽

Juhi Kidwai

Keyword(s):

Augmentative And Alternative Communication ◽

Computer Interface ◽

Computer Access ◽

Alternative Communication ◽

Primary Interest ◽

Physical Impairments ◽

Computer Interfaces ◽

Brain Signals ◽

Speech Science ◽

Sensorimotor Rhythms

Purpose Brain–computer interface (BCI) techniques may provide computer access for individuals with severe physical impairments. However, the relatively hidden nature of BCI control obscures how BCI systems work behind the scenes, making it difficult to understand “how” electroencephalography (EEG) records the BCI-related brain signals, “what” brain signals are recorded by EEG, and “why” these signals are targeted for BCI control. Furthermore, in the field of speech-language-hearing, signals targeted for BCI application have been of primary interest to clinicians and researchers in the area of augmentative and alternative communication (AAC). However, signals utilized for BCI control reflect sensory, cognitive, and motor processes, which are of interest to a range of related disciplines, including speech science. Method This tutorial was developed by a multidisciplinary team emphasizing primary and secondary BCI-AAC–related signals of interest to speech-language-hearing. Results An overview of BCI-AAC–related signals are provided discussing (a) “how” BCI signals are recorded via EEG; (b) “what” signals are targeted for noninvasive BCI control, including the P300, sensorimotor rhythms, steady-state evoked potentials, contingent negative variation, and the N400; and (c) “why” these signals are targeted. During tutorial creation, attention was given to help support EEG and BCI understanding for those without an engineering background. Conclusion Tutorials highlighting how BCI-AAC signals are elicited and recorded can help increase interest and familiarity with EEG and BCI techniques and provide a framework for understanding key principles behind BCI-AAC design and implementation.

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Using Think-Alouds to Uncover Expert-Novice Gaps in AAC Intervention Planning Skills

Teaching and Learning in Communication Sciences & Disorders ◽

10.30707/tlcsd4.2/cqjo9452 ◽

2020 ◽

Vol 4 (2) ◽

Author(s):

Allison Sauerwein ◽

Jane Wegner

Keyword(s):

Augmentative And Alternative Communication ◽

Feature Matching ◽

Alternative Communication ◽

Companion Article ◽

Think Alouds ◽

Clinical Practica ◽

Verbal Data ◽

Intervention Planning ◽

Expert Novice ◽

Materials Planning

Because few studies have explored preservice speech-language pathologists’ (SLP’s) learning outcomes in augmentative and alternative communication (AAC) coursework and clinical practica, there is a need to investigate student learning in this area. This article represents a portion of a larger study that explored the expert-novice gap in planning for intervention with children who use AAC. The companion article reports clinical reasoning skills, whereas the present study revealed intervention planning skills. The methods are the consistent with those reported in the companion article. In summary, eight novice (i.e. preservice) SLPs and eight expert SLPs completed think-aloud tasks while they developed intervention plans. Verbal data were transcribed and analyzed qualitatively. Eight intervention planning skills emerged from the data: selecting treatment style, planning activities, selecting or developing materials, planning teaching strategies, selecting targets, goal setting, collecting data, and feature matching. Considerable overlap across expert and novice performance was observed in some areas, while minor differences were noted in other skills. Expert-novice gaps were identified in two areas, developing a treatment style and feature matching. Familiarity with expert-novice gaps in intervention planning has implications for preservice instruction in AAC.

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