東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Advancing Clinical Decision-Making f...

O'Leary, Michael Sean,

FindBook

Google Book

Amazon

博客來

Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience // Michael Sean O'Leary.
作者:	O'Leary, Michael Sean,
面頁冊數:	1 electronic resource (211 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-10, Section: B.
Contained By:	Dissertations Abstracts International86-10B.
標題:	Speech therapy. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31940679
ISBN:	9798314808139

Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience /
O'Leary, Michael Sean,

Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience /Michael Sean O'Leary. - 1 electronic resource (211 pages)

Source: Dissertations Abstracts International, Volume: 86-10, Section: B.

Speech-Language Pathologists (SLP) rely on an unstandardized and informal evaluation process to recommend speech-generating devices (SGD) with control interfaces to a patient. A control interface is an input technology used to make selections on an SGD (i.e. touch, eye gaze, switch, head tracking, etc.). Existing frameworks, such as the participation and feature matching models, guide AAC control interface evaluations but do not specify the types or amount of data needed to determine the most effective control interface. As a result, SLPs rely heavily on clinical intuition and trial-and-error approaches due to the lack of precise, measurable performance criteria.This study aimed to address the gaps and deficits in control interface evaluations and provide a potential solution to automatically collect comparative control interface performance data to enhance clinical recommendations. Study 1, a scoping review of existing literature, identified gaps in the performance measures used to determine control interface success. Few comparative or multimodal studies have examined the effectiveness of different control interfaces. Given the need for standardized performance measures, Study 2 investigated SLPs' current clinical evaluation methods. Findings indicated that SLPs lack consistent and reliable measures for assessing control interfaces and desire a more uniform, data-driven approach. To address this need, Study 3 evaluated the usability and clinical acceptability of a prototype Selection Rate Application (SR App). The SR App is designed to provide an accessible and standardized measurement of selection rate, in bits per second, to identify the most effective control interface and optimal grid display size. Through interviews, surveys, and benchmark testing, SLPs determined that the SR App prototype has the potential to be a clinically viable tool for control interface evaluation.

English

ISBN: 9798314808139Subjects--Topical Terms:

520446
Speech therapy.
Subjects--Index Terms:

Alternative access methods

Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience /
LDR:03542nmm a22004573i 4500 001 2437212
005 20251118105046.5
006 m o d
007 cr|nu||||||||
008 261011s2025 miu||||||m |||||||eng d
020 $a 9798314808139
035 $a (MiAaPQD)AAI31940679
035 $a AAI31940679
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a O'Leary, Michael Sean, $e author. $3 3828124
245 1 0 $a Advancing Clinical Decision-Making for Speech-Generating Device Control Interfaces: Investigating Performance, Assessment, and User Experience / $c Michael Sean O'Leary.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2025
300 $a 1 electronic resource (211 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-10, Section: B.
500 $a Advisors: Hill, Katya Committee members: Brienza, Dave; Evans, William S.; Ding, Dan; Chen, Szu-Han Kay.
502 $b Ph.D. $c University of Pittsburgh $d 2025.
520 $a Speech-Language Pathologists (SLP) rely on an unstandardized and informal evaluation process to recommend speech-generating devices (SGD) with control interfaces to a patient. A control interface is an input technology used to make selections on an SGD (i.e. touch, eye gaze, switch, head tracking, etc.). Existing frameworks, such as the participation and feature matching models, guide AAC control interface evaluations but do not specify the types or amount of data needed to determine the most effective control interface. As a result, SLPs rely heavily on clinical intuition and trial-and-error approaches due to the lack of precise, measurable performance criteria.This study aimed to address the gaps and deficits in control interface evaluations and provide a potential solution to automatically collect comparative control interface performance data to enhance clinical recommendations. Study 1, a scoping review of existing literature, identified gaps in the performance measures used to determine control interface success. Few comparative or multimodal studies have examined the effectiveness of different control interfaces. Given the need for standardized performance measures, Study 2 investigated SLPs' current clinical evaluation methods. Findings indicated that SLPs lack consistent and reliable measures for assessing control interfaces and desire a more uniform, data-driven approach. To address this need, Study 3 evaluated the usability and clinical acceptability of a prototype Selection Rate Application (SR App). The SR App is designed to provide an accessible and standardized measurement of selection rate, in bits per second, to identify the most effective control interface and optimal grid display size. Through interviews, surveys, and benchmark testing, SLPs determined that the SR App prototype has the potential to be a clinically viable tool for control interface evaluation.
546 $a English
590 $a School code: 0178
650 4 $a Speech therapy. $3 520446
650 4 $a Health sciences. $3 3168359
650 4 $a Biomedical engineering. $3 535387
650 4 $a Information technology. $3 532993
653 $a Alternative access methods
653 $a Augmentative and Alternative Communication
653 $a Control interfaces
653 $a Human-computer interaction
653 $a Performance measurement
653 $a Selection rate
690 $a 0460
690 $a 0566
690 $a 0489
690 $a 0541
710 2 $a University of Pittsburgh. $b Rehabilitation Science and Technology. $e degree granting institution. $3 3828125
720 1 $a Hill, Katya $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-10B.
790 $a 0178
791 $a Ph.D.
792 $a 2025
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31940679