This study investigated the acoustic features of vowel production in Mandarin-speaking patients with post-stroke dysarthria (PSD). The subjects included 31 native Mandarin-speaking patients with PSD (age: 25–83 years old) and 38 neurologically normal adults in a similar age range (age: 21–76 years old). Each subject was recorded producing a list of Mandarin monosyllables that included six monophthong vowels (i.e., /a, i, u, ɤ, y, o/) embedded in the /CV/ context. The patients’ speech samples were evaluated by two native Mandarin speakers. The evaluation scores were then used to classify all patients into two levels of severity: mild or moderate-to-severe. Formants (F1 and F2) were extracted from each vowel token. Results showed that all vowel categories in the patients with PSD were produced with more variability than in the healthy speakers. Great overlaps between vowel categories and reduced vowel space were observed in the patients. The magnitude of the vowel dispersion and overlap between vowel categories increased as a function of the severity of the disorder. The deviations of the vowel acoustic features in the patients in comparison to the healthy speakers may provide guidance for clinical rehabilitation to improve the speech intelligibility of patients with PSD.
This paper proposes the use of Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units for determining whether Mandarin-speaking individuals are afflicted with a form of Dysarthria based on samples of syllable pronunciations. Several LSTM network architectures are evaluated on this binary classification task, using accuracy and Receiver Operating Characteristic (ROC) curves as metrics. The LSTM models are shown to significantly improve upon a baseline fully connected network, reaching over 90% area under the ROC curve on the task of classifying new speakers, when a sufficient number of cepstrum coefficients are used. The results show that the LSTM's ability to leverage temporal information within its input makes for an effective step in the pursuit of accessible Dysarthria diagnoses.
Aims: The aim of this survey was to investigate the background of speech-language pathologists and their training needs to provide a profile of the current state of the profession in Mainland China. Methods: A survey was conducted of 293 speech-language therapists. The questionnaire used asked questions related to their career background and had a 24-item ranking scale covering almost all of the common speech-language-hearing disorders. A summary of the raw data was constructed by calculating the average ranking score for each answer choice in order to determine the academic training needs with the highest preference among the respondents. Results: The majority of respondents were female, <35 years old and with a total service time of <5 years. More than three quarters of the training needs with the highest preference among the 24 items involved basic-level knowledge of common speech-language-hearing disorders, such as diagnosis, assessment and conventional treatment, but seldom specific advanced technology or current progress. Conclusion: The results revealed that speech-language therapists in Mainland China tend to be young, with little total working experience and at the first stage of their career. This may be due to the lack of systematic educational programs and national certification systems for speech-language therapists.
BACKGROUND
Lower body positive pressure (LBPP) treadmill has potential applications for improving the gait of patients after stroke, but the related mechanism remains unclear.
CASE SUMMARY
A 62-year-old male patient suffered from ischemic stroke with hemiplegic gait. He was referred to our hospital because of a complaint of left limb weakness for 2 years. The LBPP training was performed one session per day and six times per week for 2 wk. The dynamic plantar pressure analysis was taken every 2 d. Meanwhile, three-digital gait analysis and synchronous electromyography as well as clinical assessments were taken before and after LBPP intervention and at the 4-wk follow-up. During LBPP training, our patient not only improved his lower limb muscle strength and walking speed, but more importantly, the symmetry index of various biomechanical indicators improved. Moreover, the patient’s planter pressure transferring from the heel area to toe area among the LBPP training process and the symmetry of lower body biomechanical parameters improved.
CONCLUSION
In this study, we documented a dynamic improvement of gait performance in a stroke patient under LBPP training, which included lower limb muscle strength, walking speed, and symmetry of lower limb biomechanics. Our study provides some crucial clues about the potential dynamic mechanism for LBPP training on gait and balance improvement, which is related to rebuilding foot pressure distribution and remodeling symmetry of biomechanics of the lower limb.
The Objectives of this study are (1) to evaluate tone production in Mandarin-speaking patients with post-stroke dysarthria (PSD) using an artificial neural network (ANN), (2) to investigate the efficacy of recognition performance of the ANN model contrast to the human listeners and the convolutional neural network (CNN) model, and (3) to explore rehabilitation application of the artificial intelligence recognition for lexical tone production disorder with PSD. The subjects include two groups of native Mandarin speaking adults: 31 patients with PSD and 42 normal-speaking adults (NA) in a similar age range as controls. Each subject was recorded producing a list of 7 Mandarin monosyllables with 4 tones (i.e., a total of 28 tokens). The fundamental frequency (F0) of each monosyllable was extracted using auto-correlation algorithm. The ANN was trained with F0 data of the tone tokens from the NA, to generate the final model. The recognition rates of the human ears, ANN model, and CNN model were 87.78% ± 8.96% (mean ± SD), 89.11% ±11.80%, 65.91% ± 8.79% respectively for tone production of NA group; 70.28% ± 17.61%, 63.35% ± 17.40%, 34.71% ± 6.92% respectively for tone production of PSD group. For PSD group, there was significant correlation between the performance of the ANN model and human listeners (r = 0.826, P < 0.001). However, the performance of CNN model was not correlated with that of the human ears (r = −0.108, P = 0.562). Thus, the experiments show that ANN is more objective and efficient, which could replace human listeners in the assessment of lexical tone production disorder in Mandarin-speaking patients with PSD. Furthermore, using ANN may reduce the heterogeneity of rehabilitation evaluation among different speech therapists and may give the feedback for achievement of rehabilitation treatment more accurately. INDEX TERMS Lexical tone rehabilitation, post-stroke dysarthria (PSD), ANN, human listeners, application analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.