Search

Purpose: The primary aim of this study was to establish the reliability of candidate items as a step in the development of the Amyotrophic Lateral Sclerosis-Bulbar Dysfunction Index-Remote (ALS-BDI-Remote), a novel tool being developed for the detection and monitoring of bulbar signs and symptoms in remote settings., Method: The set of candidate items included 40 items covering three domains: cranial nerve examination, auditory-perceptual evaluation, and functional assessment. Forty-eight participants diagnosed with ALS and exhibiting a range of bulbar disease severity were included. Data collection for each participant took place on Zoom over three sessions. During Session 1, the participants were instructed to adjust their Zoom settings and to optimize their recording environment (e.g., lighting, background noise). Their cognition and eating were screened to determine their ability to follow instructions and their eligibility to perform the swallowing and chewing tasks. During Session 2, two speech-language pathologists (SLPs) administered the tool consecutively to determine the items' interrater reliability. During Session 3, one of the SLPs readministered the tool within 2 weeks of Session 1 to assess test-retest reliability. The reliability of each item was estimated using weighted kappa and the percentage of agreement. To be considered reliable, the items had to reach a threshold of 0.5 weighted kappa or 80% percentage agreement (if skewed distribution of the scores) for both interrater and test-retest reliability., Results: In total, 33 of the 40 candidate items reached the reliability cutoff for both reliability analyses. All assessment domains included reliable items. Items requiring very good visualization of structures or movements were generally less reliable., Conclusions: This study resulted in the selection of reliable items to be included in the next version of the ALS-BDI-Remote, which will undergo psychometric evaluation (reliability, validity, and responsiveness analyses). Additionally, the results contributed to our understanding of the remote administration of SLP assessments for telehealth applications.

Purpose: There is increasing interest in using automatic speech recognition (ASR) systems to evaluate impairment severity or speech intelligibility in speakers with dysarthria. We assessed the clinical validity of one currently available off-the-shelf (OTS) ASR system (i.e., a Google Cloud ASR API) for indexing sentence-level speech intelligibility and impairment severity in individuals with amyotrophic lateral sclerosis (ALS), and we provided guidance for potential users of such systems in research and clinic., Method: Using speech samples collected from 52 individuals with ALS and 20 healthy control speakers, we compared word recognition rate (WRR) from the commercially available Google Cloud ASR API (Machine WRR) to clinician-provided judgments of impairment severity, as well as sentence intelligibility (Human WRR). We assessed the internal reliability of Machine and Human WRR by comparing the standard deviation of WRR across sentences to the minimally detectable change (MDC), a clinical benchmark that indicates whether results are within measurement error. We also evaluated Machine and Human WRR diagnostic accuracy for classifying speakers into clinically established categories., Results: Human WRR achieved better accuracy than Machine WRR when indexing speech severity, and, although related, Human and Machine WRR were not strongly correlated. When the speech signal was mixed with noise (noise-augmented ASR) to reduce a ceiling effect, Machine WRR performance improved. Internal reliability metrics were worse for Machine than Human WRR, particularly for typical and mildly impaired severity groups, although sentence length significantly impacted both Machine and Human WRRs., Conclusions: Results indicated that the OTS ASR system was inadequate for early detection of speech impairment and grading overall speech severity. While Machine and Human WRR were correlated, ASR should not be used as a one-to-one proxy for transcription speech intelligibility or clinician severity ratings. Overall, findings suggested that the tested OTS ASR system, Google Cloud ASR, has limited utility for grading clinical speech impairment in speakers with ALS.

Purpose: Hypernasality and atypical voice characteristics are common features of dysarthric speech due to amyotrophic lateral sclerosis (ALS). Existing acoustic measures have been developed to primarily target either hypernasality or voice impairment, and the effects of co-occurring hypernasality-voice problems on these measures are unknown. This report explores (a) the extent to which acoustic measures are affected by concurrent perceptually identified hypernasality and voice impairment due to ALS and (b) candidate acoustic measures of early indicators of hypernasality and voice impairment in the presence of multisystem involvement in individuals with ALS., Method: Two expert listeners rated severity of hypernasality and voice impairment in sentences produced by individuals with ALS ( n = 27). The samples were stratified based on perceptual ratings: voice/hypernasality asymptomatic, predominantly hypernasal, predominantly voice impairment, and mixed (co-occurring hypernasality and voice impairment). Groups were compared using established acoustic measures of hypernasality (one-third octave analysis) and voice (cepstral/spectral analysis) impairment., Results: The one-third octave analysis differentiated all groups; the cepstral peak prominence differentiated all groups except asymptomatic versus mixed, whereas the low-to-high spectral ratio did not differ among groups. Additionally, one-third octave analyses demonstrated promising speech diagnostic potential., Conclusions: The results highlight the need to consider the validity of measures in the context of multisubsystem involvement. Our preliminary findings further suggest that the one-third octave analysis may be an optimal approach to quantify hypernasality and voice abnormalities in the presence of multisystem speech impairment. Future evaluation of the diagnostic accuracy of the one-third octave analysis is warranted.