The Effects of Yoga Breathing Before Motor Speech Practice in Acquired Apraxia of Speech: An n-of-1 Trial.

A previous study discovered that two speakers with moderate apraxia of speech increased their sequential motion rates after unilateral forced-nostril breathing (UFNB) practiced as an adjunct to speech-language therapy in an AB repeated-measures design. The current study sought to: (1) delineate possible UFNB plus practice effects from practice effects alone in motor speech skills; (2) examine the relationships between UFNB integrity, participant-reported stress levels, and motor speech performance; and (3) sample a participant-led UFNB training schedule to contribute to the literature's growing understanding of UFNB dosage. A single-subject (n-of-1 trial), ABAB reversal design was used across four motor speech behaviors. A 60-year-old female with chronic, severe apraxia of speech participated. The researchers developed a breathing app to assess UFNB practice integrity and administer the Simple Aphasia Stress Scale after each UFNB session. The participant improved from overall severe to moderate apraxia of speech on the Apraxia Battery for Adults. Visual inspection of graphs confirmed robust motor speech practice effects for all variables. Articulatory-kinematic variables demonstrated sensitivity to the UFNB-plus-practice condition and correlated to stress scale scores but not UFNB integrity scores. The participant achieved 20-minute UFNB sessions 4 times per week. Removal of UFNB during A2 (UFNB withdrawal) and after a 10-day break during B2 (UFNB full dosage) revealed UFNB practice effects on stress scale scores. UFNB with motor speech practice may benefit articulatory-kinematic skills compared to motor speech practice alone. Regular, cumulative UFNB practice appeared to lower self-perceived stress levels. These findings, along with prior work, provide a foundation to further explore yoga breathing and its use with speakers who have apraxia of speech.

Development of digital voice biomarkers and associations with cognition, cerebrospinal biomarkers, and neural representation in early Alzheimer's disease.

Introduction: Advances in natural language processing (NLP), speech recognition, and machine learning (ML) allow the exploration of linguistic and acoustic changes previously difficult to measure. We developed processes for deriving lexical-semantic and acoustic measures as Alzheimer's disease (AD) digital voice biomarkers. Methods: We collected connected speech, neuropsychological, neuroimaging, and cerebrospinal fluid (CSF) AD biomarker data from 92 cognitively unimpaired (40 Aß+) and 114 impaired (63 Aß+) participants. Acoustic and lexical-semantic features were derived from audio recordings using ML approaches. Results: Lexical-semantic (area under the curve [AUC] = 0.80) and acoustic (AUC = 0.77) scores demonstrated higher diagnostic performance for detecting MCI compared to Boston Naming Test (AUC = 0.66). Only lexical-semantic scores detected amyloid-ß status (p = 0.0003). Acoustic scores associated with hippocampal volume (p = 0.017) while lexical-semantic scores associated with CSF amyloid-ß (p = 0.007). Both measures were significantly associated with 2-year disease progression. Discussion: These preliminary findings suggest that derived digital biomarkers may identify cognitive impairment in preclinical and prodromal AD, and may predict disease progression. Highlights: This study derived lexical-semantic and acoustics features as Alzheimer's disease (AD) digital biomarkers.These features were derived from audio recordings using machine learning approaches.Voice biomarkers detected cognitive impairment and amyloid-ß status in early stages of AD.Voice biomarkers may predict Alzheimer's disease progression.These markers significantly mapped to functional connectivity in AD-susceptible brain regions.

Assessing the phacoemulsification learning curve using duration of each step.

PURPOSE: To assess the phacoemulsification learning curve for ophthalmology residents using duration for each step. SETTING: Single tertiary, training site hospital. DESIGN: Cross-sectional study. METHODS: Emory ophthalmology postgraduate year (PGY) 3 and PGY-4 residents operating at Grady Memorial Hospital between April 2017 and February 2018 were eligible to participate. Duration in seconds for each step of surgery was calculated for incisions, continuous curvilinear capsulorhexis (CCC), hydrodissection, nucleus disassembly, quadrant removal, cortical cleanup, intraocular lens insertion, and closure, and this outcome was analyzed as a function of different experience levels. RESULTS: A total of 528 surgeries were included of 549 total surgeries recorded. 6 categories of experience levels were established as A to F, increasing by increments of 50. There was an overall downward trend across various steps across the 8 case categories, and several adjacent categories demonstrate statistically significant differences. The 3 most time-intensive steps early in training were nucleus disassembly (336.5 ± 16.5 seconds), quadrant removal (275.1 ± 18.0 seconds), and cortical cleanup (244.2 ± 24.6 seconds). There was a sustained drop in mean duration for all steps through at least category D, with most steps showing a drop through category F. CONCLUSIONS: There is a benefit to a higher caseload, well above the Accreditation Council for Graduate Medical Education-mandated 86 cases. Improvements in efficiency were observed after 250 cases, with nuclear disassembly and CCC demonstrating a significant decrease in operative time.

Association analysis of the general environmental conditions and prokaryotes' gene distributions in various functional groups.

The activities of prokaryotes are pivotal in shaping the environment, and at the same time are greatly influenced by the environment. By using the genomic data and environmental descriptions of the complete prokaryotic genomes in NCBI's Microbial Genome Project Database and applying statistical methods, we have identified in a systematic manner those gene groups whose presence/frequency patterns are different for organisms of different environmental conditions. Here environmental conditions are characterized in four dimensions--salinity, oxygen requirement, habitat and temperature, and are based on the controlled vocabularies that NCBI's Microbial Genome Project database uses to specify the organism information; and, gene groups are determined as Clusters of Orthologous Groups (COG) and KEGG Orthology (KO) groups. These identified COG and KO groups are considered as potentially correlated with certain environmental conditions, and are then mapped to the COG general categories and KEGG pathways to determine which part of the functional machinery of prokaryotic cells are correlated with the environments. The observations derived from the analysis of the COG and KO groups that are potentially correlated with the oxygen requirement and habitat conditions are in general consistent with existing studies on properties of organisms living in different conditions of these two environmental factors. To further assess the identified correlation relationships, we have also examined whether the environmental conditions are predictable based on the gene distributions in the selected COG and KO groups. The misclassification rates of the prediction experiments are much smaller than that rendered by random guessing, indicating the existence of the correlation relationships between organisms' environmental conditions and gene distributions in certain functional groups. However, the rather moderate misclassification rates (the 25- and 75-percentiles of the misclassification rates of all prediction experiments are 16.79% and 24.06%, respectively) also indicate that the correlation relationships between environmental conditions and gene distributions in certain functional groups are not strong enough for one to decisively define the other.

App-based data collection, mental imagery, and naming performance in adults with aphasia.

BACKGROUND AND PURPOSE: Naming impairments are often found in aphasia. Combining mHealth technology with mental imagery may offer new insights into novel approaches to naming interventions in persons with aphasia. The aims of this study are to (1) explore whether mental imagery can improve performance during a naming task in adults with aphasia; and, (2) demonstrate the use of app-based data collection for research in aphasia rehabilitation through utilization of an app designed specifically for this study. MATERIALS AND METHODS: A single subject non-concurrent multiple baseline design across participants was utilized. Four participants with anomic and conduction aphasia were included. Each participant's percentage of naming accuracy was measured before the initiating intervention to establish a baseline level of performance. RESULTS: Per overlap metrics, two of the participants demonstrated a strong effect in improving naming from baseline to intervention on items using the app. Two participants showed no effect in naming accuracy from the imagery intervention. CONCLUSION: Some participants showed improvement in naming items following an imagery script, suggesting that this complementary health practice should continue to be explored. Additionally, this study demonstrates the successful use of app-based data collection.

Critical analysis of the impact of glottal features in the classification of clinical depression in speech.

The motivation for this work is in an attempt to rectify the current lack of objective tools for clinical analysis of emotional disorders. This study involves the examination of a large breadth of objectively measurable features for use in discriminating depressed speech. Analysis is based on features related to prosodics, the vocal tract, and parameters extracted directly from the glottal waveform. Discrimination of the depressed speech was based on a feature selection strategy utilizing the following combinations of feature domains: prosodic measures alone, prosodic and vocal tract measures, prosodic and glottal measures, and all three domains. The combination of glottal and prosodic features produced better discrimination overall than the combination of prosodic and vocal tract features. Analysis of discriminating feature sets used in the study reflect a clear indication that glottal descriptors are vital components of vocal affect analysis.

Identification of Affective State Change in Adults With Aphasia Using Speech Acoustics.

Purpose: The current study aimed to identify objective acoustic measures related to affective state change in the speech of adults with post-stroke aphasia. Method: The speech of 20 post-stroke adults with aphasia was recorded during picture description and administration of the Western Aphasia Battery-Revised (Kertesz, 2006). In addition, participants completed the Self-Assessment Manikin (Bradley & Lang, 1994) and the Stress Scale (Tobii Dynavox, 1981-2016) before and after the language tasks. Speech from each participant was used to detect a change in affective state test scores between the beginning and ending speech. Results: Machine learning revealed moderate success in classifying depression, minimal success in predicting depression and stress numeric scores, and minimal success in classifying changes in affective state class between the beginning and ending speech. Conclusions: The results suggest the existence of objectively measurable aspects of speech that may be used to identify changes in acute affect from adults with aphasia. This work is exploratory and hypothesis-generating; more work will be needed to make conclusive claims. Further work in this area could lead to automated tools to assist clinicians with their diagnoses of stress, depression, and other forms of affect in adults with aphasia.

Stress and depression scales in aphasia: relation between the aphasia depression rating scale, stroke aphasia depression questionnaire-10, and the perceived stress scale.

BACKGROUND: Assessment and diagnosis of post-stroke depression (PSD) among patients with aphasia presents unique challenges. A gold standard assessment of PSD among this population has yet to be identified. OBJECTIVES: The first aim was to investigate the association between two depression scales developed for assessing depressive symptoms among patients with aphasia. The second aim was to evaluate the relation between these scales and a measure of perceived stress. METHOD: Twenty-five (16 male; 9 female) individuals with history of left hemisphere cerebrovascular accident (CVA) were assessed for depression and perceived stress using the Stroke Aphasic Depression Questionnaire-10 (SADQ-10), the Aphasia Depression Rating Scale (ADRS), and the Perceived Stress Scale (PSS). RESULTS: SADQ-10 and ADRS ratings were strongly correlated with each other (r = 0.708, p < 0.001). SADQ-10 ratings were strongly correlated with PSS ratings (r = 0.620, p = 0.003), while ADRS ratings were moderately correlated (r = 0.492, p = 0.027). Item analysis of each scale identified items which increased both inter-scale correlation and intra-scale consistency when excluded. CONCLUSIONS: The SADQ-10 and ADRS appear to be acceptable measures of depressive symptoms in aphasia patients. Measurements of perceived stress may also be an important factor in assessment of depressive symptoms.

Comparing objective feature statistics of speech for classifying clinical depression.

Human communication is saturated with emotional context that aids in interpreting a speakers mental state. Speech analysis research involving the classification of emotional states has been studied primarily with prosodic (e.g., pitch, energy, speaking rate) and/or spectral (e.g., formants) features. Glottal waveform features, while receiving less attention (due primarily to the difficulty of feature extraction), have also shown strong clustering potential of various emotional and stress states. This study provides a comparison of the major categories of speech analysis in the application of identifying and clustering feature statistics from a control group and a patient group suffering from a clinical diagnosis of depression.