The field of voice and speech analysis has become increasingly popular over the last 10 years, and articles on its use in detecting neurodegenerative diseases have proliferated. Many studies have ...identified characteristic speech features that can be used to draw an accurate distinction between healthy aging among older people and those with mild cognitive impairment and Alzheimer's disease. Speech analysis has been singled out as a cost-effective and reliable method for detecting the presence of both conditions. In this research, a systematic review was conducted to determine these features and their diagnostic accuracy.
Peer-reviewed literature was located across multiple databases, involving studies that apply new procedures of automatic speech analysis to collect behavioral evidence of linguistic impairments along with their diagnostic accuracy on Alzheimer's disease and mild cognitive impairment. The risk of bias was assessed by using JBI and QUADAS-2 checklists.
Thirty-five papers met the inclusion criteria; of these, 11 were descriptive studies that either identified voice features or explored their cognitive correlates, and the rest were diagnostic studies. Overall, the studies were of good quality and presented solid evidence of the usefulness of this technique. The distinctive acoustic and rhythmic features found are gathered. Most studies record a diagnostic accuracy over 88% for Alzheimer's and 80% for mild cognitive impairment.
Automatic speech analysis is a promising tool for diagnosing mild cognitive impairment and Alzheimer's disease. The reported features seem to be indicators of the cognitive changes in older people. The specific features and the cognitive changes involved could be the subject of further research.
War is an unbearable and unforeseen burden on the human psyche. Threat to existence, fear for life, loss of loved ones lead to an increase of non-psychotic borderline disorders, including ...post-traumatic stress disorder.
Children represent the most unprotected and vulnerable part of the population. Being in the zone of military conflict, they acquire a tragic experience that deforms their consciousness, their values and outlook. Children experience mood swings, depression, unmotivated aggression, obsessive states, overwhelming fear and anticipation of retelling the experienced events. The article is devoted to the analysis of speech characteristics of children who witnessed the Russo-Ukrainian war, which began on February 24, 2022. The study focuses on the description of the verbalization of the psychological state of a child who witnessed bombings and shelling, children from the occupied territories who had to leave their homes, and children who, not being direct witnesses of military operations, have been forced to live in temporary refugee camps for six months unable to return to their houses. The authors analyze ways of verbalizing fear, anxiety, obsessive states, types of verbal aggression. The article deals also with the influence of parents on overcoming or, vice versa, increasing children's stress.
This study classified speech impairment in 200 patients with Parkinson's disease (PD) into five levels of overall severity and described the corresponding type (voice, articulation, fluency) and ...extent (rated on a five-point scale) of impairment for each level. From two-minute conversational speech samples, parameters of voice, fluency and articulation were assessed by two trained-raters. Voice was found to be the leading deficit, most frequently affected and impaired to a greater extent than other features in the initial stages. Articulatory and fluency deficits manifested later, articulatory impairment matching voice impairment in frequency and extent at the 'Severe' stage. At the final stage of 'Profound' impairment, articulation was the most frequently impaired feature at the lowest level of performance. This study illustrates the prominence of voice and articulatory speech motor control deficits, and draws parallels with deficits of motor set and motor set instability in skeletal controls of gait and handwriting.
Imaginative thinking is the main type of thinking in children of senior preschool age. The state of its formation largely determines the success of children in acquiring knowledge, forming skills and ...abilities following the Basic Component of Preschool Education, and in the future, the requirements of school curricula. The study aims to outline the results of the research on the state of formation of figurative thinking in older preschool children with speech disorders in comparison with children with typical speech development. The following methods of scientific research were used in the study: Analysis and synthesis of scientific and methodological literature on the research problem, experiment, testing, comparison, and quantitative and qualitative analysis of the experimental data. According to the results of the diagnostics carried out according to the author's methodology, which is based on a modification of the study of figurative memory, it was found that children with speech disorders have an insufficient level of figurative thinking, especially its topological, projective, ordered, and compositional substructures. These results indicate that children have difficulty creating mental images of objects or phenomena, operating with previously created and stored images, as well as analysing, synthesising, abstracting, mediating, comparing, and generalising perceived information. These difficulties are at the heart of the problems with preparation for studying at the New Ukrainian School. The practical value of the work is to inform specialists of special and inclusive preschool education institutions about the specific features of the state of formation of imaginative thinking in older preschool children with speech disorders. The results of the study can be used for the development and implementation of methods for the formation of imaginative thinking in senior preschool children with speech disorders
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms that significantly impact an individual's quality of life. Voice changes have shown promise as ...early indicators of PD, making voice analysis a valuable tool for early detection and intervention. This study aims to assess and detect the severity of PD through voice analysis using the mobile device voice recordings dataset. The dataset consisted of recordings from PD patients at different stages of the disease and healthy control subjects. A novel approach was employed, incorporating a voice activity detection algorithm for speech segmentation and the wavelet scattering transform for feature extraction. A Bayesian optimization technique is used to fine-tune the hyperparameters of seven commonly used classifiers to optimize the performance of machine learning classifiers for PD severity detection. AdaBoost and K-nearest neighbor consistently demonstrated superior performance across various evaluation metrics among the classifiers. Furthermore, a weighted majority voting (WMV) technique is implemented, leveraging the predictions of multiple models to achieve a near-perfect accuracy of 98.62%, improving classification accuracy. The results highlight the promising potential of voice analysis in PD diagnosis and monitoring. Integrating advanced signal processing techniques and machine learning models provides reliable and accessible tools for PD assessment, facilitating early intervention and improving patient outcomes. This study contributes to the field by demonstrating the effectiveness of the proposed methodology and the significant role of WMV in enhancing classification accuracy for PD severity detection.
•Voice impairments show promise as an early indicator of Parkinson's disease (PD).•Voice activity detection, wavelet transform and tuned models improve PD classification.•Weighted majority voting achieves 98.62% accuracy in PD severity detection.
There has been increased interest in the use of transoral surgery (TOS) for the treatment of oropharyngeal cancer (OPC). This systematic review summarizes the available evidence for validated ...functional outcomes following TOS for OPC, within the early postoperative period. Key databases were searched. Primary TOS resections of human subjects were included. Validated functional outcomes extracted included instrumental assessment, clinician rated, and patient reported measures. Database searches yielded 7186 titles between 1990 and December 2020. Full‐text articles were obtained for 296 eligible studies, which were screened and a resulting 14 studies, comprising 665 participants were included in the review. Oropharyngeal dysfunction following TOS was observed across all three categories of outcome measures (OMs) reported and was dependent on pretreatment function, T‐classification, and tumor volume. Future investigations should include optimal OMs to be used in the postoperative setting to allow for conclusive comparisons.
The article presents a design and development of a generic assistive system to establish an independent conversation-platform for hearing-speech impaired and visually impaired persons.
The developed ...software system is accomplished through programming using python and html.
Considering the constraints associated to the above mentioned impairments, the system implements both speech-to-text/gesture and text/gesture-to-speech conversion in its operation. In real-time hand-gesture to speech generation process is implemented using static image tracking, CNN based deep learning technique and MediaPipe hand-tracking solution. The software-prototype-terminals can be accessed through internet using MQTT protocol to accomplish the communicative conversation between visually impaired and hearing-speech impaired persons.
The software system exhibits an average prediction time of less than approximately 1 s and 2 s for a four-letter based audio-word and a single hand-gesture, respectively, which are commensurate to the average time-complexity during human-to-human conversation. The average accuracy and loss for the hand-gestures through the CNN based deep learning are 0.9996 and 0.0008, respectively. The confusion matrix related to the prediction of alphabet-specific hand-gestures shows its satisfactory performance in gesture recognition.
The software-prototype of the generic assistive device shows its potential to establish an exclusive communication between a visually impaired and a hearing-speech impaired person through the internet. The same software-interface can also be used to accomplish a communicative conversation between either only visually-impaired persons or only hearing-speech impaired persons.
IMPLICATIONS FOR REHABILITATION
The article presents a design and development of a generic assistive interface to establish an independent conversation-platform for hearing-speech impaired and visually impaired people via internet network.
The same software-interface can also be used to accomplish a communicative conversation between either only visually-impaired persons or only hearing-speech impaired persons.
The design can be further extended by incorporating multi-modal impairments to make a universal assistive device for all-in-one communication.
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