Continuous ultrasound based tongue movement video synthesis from speech

2016 ◽  
Author(s):  
Jianrong Wang ◽  
Yalong Yang ◽  
Jianguo Wei ◽  
Ju Zhang
Keyword(s):  
Tongue Movement

Automated Acoustic Analysis of Oral Diadochokinesis to Assess Bulbar Motor Involvement in Amyotrophic Lateral Sclerosis

2020 ◽  
Vol 63 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Panying Rong
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Acoustic Analysis ◽  
Speaking Rate ◽  
Disease Stage ◽  
Healthy Controls ◽  
Tongue Movement ◽  
Major Barrier ◽  
Syllable Repetition ◽  
Oral Diadochokinesis ◽  
Lateral Sclerosis

Purpose The purpose of this article was to validate a novel acoustic analysis of oral diadochokinesis (DDK) in assessing bulbar motor involvement in amyotrophic lateral sclerosis (ALS). Method An automated acoustic DDK analysis was developed, which filtered out the voice features and extracted the envelope of the acoustic waveform reflecting the temporal pattern of syllable repetitions during an oral DDK task (i.e., repetitions of /tɑ/ at the maximum rate on 1 breath). Cycle-to-cycle temporal variability (cTV) of envelope fluctuations and syllable repetition rate (sylRate) were derived from the envelope and validated against 2 kinematic measures, which are tongue movement jitter (movJitter) and alternating tongue movement rate (AMR) during the DDK task, in 16 individuals with bulbar ALS and 18 healthy controls. After the validation, cTV, sylRate, movJitter, and AMR, along with an established clinical speech measure, that is, speaking rate (SR), were compared in their ability to (a) differentiate individuals with ALS from healthy controls and (b) detect early-stage bulbar declines in ALS. Results cTV and sylRate were significantly correlated with movJitter and AMR, respectively, across individuals with ALS and healthy controls, confirming the validity of the acoustic DDK analysis in extracting the temporal DDK pattern. Among all the acoustic and kinematic DDK measures, cTV showed the highest diagnostic accuracy (i.e., 0.87) with 80% sensitivity and 94% specificity in differentiating individuals with ALS from healthy controls, which outperformed the SR measure. Moreover, cTV showed a large increase during the early disease stage, which preceded the decline of SR. Conclusions This study provided preliminary validation of a novel automated acoustic DDK analysis in extracting a useful measure, namely, cTV, for early detection of bulbar ALS. This analysis overcame a major barrier in the existing acoustic DDK analysis, which is continuous voicing between syllables that interferes with syllable structures. This approach has potential clinical applications as a novel bulbar assessment.

Speech intelligibility loss due to amyotrophic lateral sclerosis: the effect of tongue movement reduction on vowel and consonant acoustic features

2021 ◽  
pp. 1-22
Author(s):  
Panying Rong ◽  
Evan Usler ◽  
Linda M. Rowe ◽  
Kristen Allison ◽  
Jonghye Woo ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Speech Intelligibility ◽  
Acoustic Features ◽  
Tongue Movement ◽  
Lateral Sclerosis

scholarly journals Adaptive brain activity changes during tongue movement with palatal coverage from fMRI data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuka Inamochi ◽  
Kenji Fueki ◽  
Nobuo Usui ◽  
Masato Taira ◽  
Noriyuki Wakabayashi
Keyword(s):  
Spatial Information ◽  
Brain Activity ◽  
Motor Impairment ◽  
Angular Gyrus ◽  
Tongue Movement ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Oral Environment ◽  
Motor Dexterity ◽  
The Brain

AbstractSuccessful adaptation to wearing dentures with palatal coverage may be associated with cortical activity changes related to tongue motor control. The purpose was to investigate the brain activity changes during tongue movement in response to a new oral environment. Twenty-eight fully dentate subjects (mean age: 28.6-years-old) who had no experience with removable dentures wore experimental palatal plates for 7 days. We measured tongue motor dexterity, difficulty with tongue movement, and brain activity using functional magnetic resonance imaging during tongue movement at pre-insertion (Day 0), as well as immediately (Day 1), 3 days (Day 3), and 7 days (Day 7) post-insertion. Difficulty with tongue movement was significantly higher on Day 1 than on Days 0, 3, and 7. In the subtraction analysis of brain activity across each day, activations in the angular gyrus and right precuneus on Day 1 were significantly higher than on Day 7. Tongue motor impairment induced activation of the angular gyrus, which was associated with monitoring of the tongue’s spatial information, as well as the activation of the precuneus, which was associated with constructing the tongue motor imagery. As the tongue regained the smoothness in its motor functions, the activation of the angular gyrus and precuneus decreased.

Inspiratory coactivation of the genioglossus enlarges retroglossal space in laryngectomized humans

1996 ◽  
Vol 80 (5) ◽  
pp. 1595-1604 ◽  
Author(s):  
I. Kobayashi ◽  
A. Perry ◽  
J. Rhymer ◽  
B. Wuyam ◽  
P. Hughes ◽  
...  
Keyword(s):  
Upper Airway ◽  
Dependent Manner ◽  
Tongue Movement ◽  
Forward Movement ◽  
Upper Airways ◽  
Posterior Aspect ◽  
Airway Patency ◽  
Significant Movement ◽  
Tongue Position ◽  
Tracheal Stoma

To investigate the relationship between the electrical activity of the genioglossus (GG-EMG) and associated tongue movement, seven laryngectomized subjects breathing through a tracheal stoma (without pressure or flow change in the upper airway) were studied in the supine position. Tongue movement, with the use of lateral fluoroscopy, and GG-EMG expressed as a percentage of maximum voluntary genioglossal activation were monitored simultaneously during 1) spontaneous inspiration (SI), 2) resistive loaded inspiration (LI), and 3) rapid inspiration (RI). Tongue position during each maneuver was compared with its position during spontaneous expiration. Peak GG-EMG during the three maneuvers was significantly different from each other (SI: 5.4 +/- 1.6, LI: 11.9 +/- 1.8, and RI: 51.6 +/- 9.4 (SE) %, respectively). Associated forward movement of the posterior aspect of the tongue was minimum during SI; however, significant movement was observed during LI, and this was increased during RI. Significant covariance existed between peak GG-EMG and this movement. Genioglossal coactivation with inspiration enlarges the glossopharyngeal airway, particularly in its caudal part. In subjects with intact upper airways, this activation may protect or enhance upper airway patency in an effort-dependent manner.

scholarly journals Worster-Drought Syndrome Associated With LINS Mutations

2018 ◽  
Vol 5 ◽  
pp. 2329048X1879108 ◽  
Author(s):  
Hugh J. McMillan ◽  
Anne-Lise Holahan ◽  
Julie Richer
Keyword(s):  
Intellectual Disability ◽  
Neuropsychological Testing ◽  
Receptive Language ◽  
Receptive Vocabulary ◽  
Tongue Movement ◽  
Nonsense Mutations ◽  
Prior Testing ◽  
Molecular Etiology ◽  
Nonverbal Reasoning ◽  
The Brain

Worster-Drought syndrome is a congenital, pseudobulbar paresis. There is no identified molecular etiology despite familial cases reported. The authors report a boy who was diagnosed with Worster-Drought syndrome due to longstanding drooling, dysphagia, and impaired tongue movement. Magnetic resonance imaging of the brain was unrevealing. At 14 years old, he remains aphonic with normal facial and extraocular movements. Nonsense mutations in the LINS gene, p.Glu366X and p.Lys393X, were found. Results from neuropsychological testing at 14 years old were consistent with a diagnosis of intellectual disability and revealed nonverbal reasoning skills at a 5-year-old level with relative sparing of his receptive vocabulary and visual attention. Compared to prior testing at 9 years old, his receptive language improved from a 6-year-old to an 8.5-year-old level. The authors report LINS mutations associated with Worster-Drought syndrome. This highlights that despite severe and persistent aphonia, receptive language improvements can be observed within the context of intellectual disability.

scholarly journals Additively manufactured 4D human head model with tongue movement

2019 ◽  
Vol 30 (S19) ◽  
pp. 168-168
Author(s):  
Gunpreet Oberoi ◽  
Ivo Rausch ◽  
Francesco Moscato ◽  
Unger Ewald
Keyword(s):  
Human Head ◽  
Head Model ◽  
Tongue Movement ◽  
Human Head Model

An Alternative Method to Treat Ankyloglossia

2016 ◽  
Vol 40 (4) ◽  
pp. 319-321 ◽  
Author(s):  
Gabriel Ferreira Nicoloso ◽  
Iuri Silveira dos Santos ◽  
Jorge Abel Flores ◽  
Bruno Lopes da Silveira ◽  
Marta Dutra Machado Oliveira
Keyword(s):  
Clinical Report ◽  
Alternative Technique ◽  
Tongue Movement ◽  
Laser Device ◽  
Laser Technology ◽  
Dental Procedures ◽  
Surgical Pain ◽  
Surgical Field ◽  
The Many ◽  
Lingual Frenum

Ankyloglossia entails short lingual frenum, impairing satisfactory tongue movement and leading to problems related to deglutition, feeding and diction. This clinical report uses laser technology, rather than traditional surgical procedure with scalpel, to perform a lingual frenulotomy on a 9-year old child diagnosed with ankyloglossia, aiming to investigate more conservative and less traumatic dental procedures. Due to the many advantages of the laser device, such as bloodless surgical field, absence of sutures, minimal swelling and post-surgical pain, the high intensity diode laser is a viable alternative technique in soft tissue surgeries.

Visualization and quantification of tongue movement during articulation: Is ultrasound a valid alternative to magnetic resonance imaging?

2018 ◽  
Vol 46 (11) ◽  
pp. 1924-1933 ◽  
Author(s):  
Katinka Kansy ◽  
Jürgen Hoffmann ◽  
Nicole Mistele ◽  
Veronika Shavlokhova ◽  
Martin Bendszus ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Tongue Movement ◽  
Resonance Imaging

scholarly journals An ECoG-Based Binary Classification of BCI Using Optimized Extreme Learning Machine

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Xinman Zhang ◽  
Qi Xiong ◽  
Yixuan Dai ◽  
Xuebin Xu ◽  
Guokun Song
Keyword(s):  
Extreme Learning Machine ◽  
Binary Classification ◽  
Tongue Movement ◽  
Common Spatial Pattern ◽  
Large Dataset ◽  
Electrocorticogram Ecog ◽  
Learning Machine ◽  
Bci System ◽  
System Approaches

In order to improve the accuracy of brain signal processing and accelerate speed meanwhile, we present an optimal and intelligent method for large dataset classification application in this paper. Optimized Extreme Learning Machine (OELM) is introduced in ElectroCorticoGram (ECoG) feature classification of motor imaginary-based brain-computer interface (BCI) system, with common spatial pattern (CSP) to extract the feature. When comparing it with other conventional classification methods like SVM and ELM, we exploit several metrics to evaluate the performance of all the adopted methods objectively. The accuracy of the proposed BCI system approaches approximately 92.31% when classifying ECoG epochs into left pinky or tongue movement, while the highest accuracy obtained by other methods is no more than 81%, which substantiates that OELM is more efficient than SVM, ELM, etc. Moreover, the simulation results also demonstrate that OELM will significantly improve the performance with p value being far less than 0.001. Hence, the proposed OELM is satisfactory in addressing ECoG signal.

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