Purpose This study investigated the factors that influence the prognosis of swallowing function rehabilitation therapy in patients with dysphagia after medullary infarction. Patients and Methods This retrospective study was conducted using the clinical data of 51 patients who were diagnosed with dysphagia after medullary infarction and hospitalized at our institution between January 2019 and January 2021. As per the water swallow test (WST) grade at 1 month after rehabilitation treatment, patients were classified into the good prognosis group and the poor prognosis group. Univariate analysis as well as univariate and multivariate logistic regression analysis were used to analyze factors that influence the prognosis of swallowing function rehabilitation therapy in patients with dysphagia after medullary infarction. Receiver operating characteristic (ROC) curves were then used to test the predictive ability of the significant parameters to predict the prognosis of the rehabilitation therapy in these patients. Results Univariate analysis and univariate logistic regression analysis showed that previous stroke (odds ratio [OR] = 1.361), dysarthria (OR = 3.771), disease course (OR = 1.112), National Institutes of Health Stroke Scale (NIHSS) score at admission (OR = 2.596), and infarct site (OR = 11.071) were all significantly correlated with the prognosis of swallowing function rehabilitation therapy in patients with dysphagia after medullary infarction ( P < 0.05). Multivariate logistic regression analysis showed that dysarthria (OR = 5.519, 95% confidence interval (CI) 1.413–21.566), infarct site (OR = 18.634, 95% CI 1.696–204.73), and the NIHSS score (OR = 1.001, 95% CI 1.536–4.820) were independent influencing factors of the prognosis of swallowing function rehabilitation therapy in these patients. The ROC curve showed that the area under the curve for the combined prediction of the three indicators was 0.943. Conclusion The NIHSS score, dysarthria, and infarct site are independent influencing factors for the prognosis of swallowing function rehabilitation therapy in patients with dysphagia after medullary infarction.

Background Speech recognition is a technology that enables machines to understand human language. Objective In this study, speech recognition of isolated words from a small vocabulary was applied to the field of mental health counseling. Methods A software platform was used to establish a human-machine chat for psychological counselling. The software uses voice recognition technology to decode the user's voice information. The software system analyzes and processes the user's voice information according to many internal related databases, and then gives the user accurate feedback. For users who need psychological treatment, the system provides them with psychological education. Results The speech recognition system included features such as speech extraction, endpoint detection, feature value extraction, training data, and speech recognition. Conclusions The Hidden Markov Model was adopted, based on multithread programming under a VC2005 compilation environment, to realize the parallel operation of the algorithm and improve the efficiency of speech recognition. After the design was completed, simulation debugging was performed in the laboratory. The experimental results showed that the designed program met the basic requirements of a speech recognition system.

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