One of the most frequently diagnosed neurodegenerative disorders, along with Alzheimer's disease, is Parkinson's disease. It is a slowly progressing disease of the central nervous system that affects parts of the brain which are responsible for one's motor functions. Despite the frequency of its occurrence among the elderly population, there has not yet been established a universal approach towards its certain diagnostics ante mortem. The study presents a pilot experiment regarding the assessment of the usefulness of simultaneous processing and analysis of speech signal and hand tremor accelerations for patient's screening and monitoring of the progress in healing, using the data acquired with a mid-range Android smartphone. During the study, a mobile device of this kind was used to record the patients of the Department of Neurology, University Hospital of the Jagiellonian University in Kraków and a control group of healthy persons over the age of 50. The samples were then analysed and an attempt towards classification was made using statistical methods and machine learning techniques (PCA, SVM, LDA). It was shown that even for a limited population, the classifier reaches about 85% accuracy. Another topic discussed in the study is the possibility of implementing a fully automated mobile system for the monitoring of the disease's progression. Propositions of further research were also drawn.
Temporomandibular joints are part of the stomatognathic system and play an important role in chewing, swallowing and speech articulating and expressing emotions. Unfortunately, they often do not work properly. Occasional disorder, postural defects, increased muscle tone bearing down due to stress deprivation through such parafunctions as clenching and grinding teeth, long-term chewing gum, nail biting or chewing lips and cheeks can lead to the appearance of dysfunctions in the temporomandibular joints. Analysis of vibrations caused by dysfunctions enables a more accurate diagnosis and an objective way of monitoring the treatment process. The article presents the results of pilot studies carried out in this area by Authors on a group of 13 people (9 women and 4 men) suffering from various diseases within the stomatognathic system. Particular attention was paid to the problems associated with vibroacoustic registration of temporomandibular joint cracks that occurred during the determination of the test methodology.
Nasal blockage belongs to the most common symptoms of nasal diseases in vocal tract area. At the same frequency there appear acoustic symptoms, existing as the change of human voice color. Vocal and articulation disorders of the ear, nose ane throat are usually observed in the form of closed rhinolalia and this observation can be performed both by patients and other listeners as well. Nasal polyps and nasal septum deviation are frequent reason of nasal blockage connected in consequence with decreased nasal ventilation. One of the main principles of the surgical treatment performed in mentioned situations is the restoration of nasal patency. The evaluation of the influence of nasal surgery on intensification of acoustic symptoms depends on verification of parameters of the human speech signal, so it was necessary to apply objective methods. That allowed to combine results of acoustic analysis with patient's subjective feeling and rhinomanometric evaluation of nasal patency. The main purpose of this research was to objectively evaluate the influence of surgical treatment improving nasal patency on deformation of the voice of operated patients.
With the present development of digital registration and methods for processing speech it is possible to make effective objective acoustic diagnostics for medical purposes. These methods are useful as all pathologies and diseases of the human vocal tract influence the quality of a patient's speech signal. Diagnostics of the voice organ can be defined as an unambiguous recognition of the current condition of a specific voice source. Such recognition is based on an evaluation of essential acoustic parameters of the speech signal. This requires creating a vibroacoustic model of selected deformations of Polish speech in relation to specific human larynx diseases. An analysis of speech and parameter mapping in 29-dimensional space is reviewed in this study. Speech parameters were extracted in time, frequency and cepstral (quefrency) domains resulting in diagrams that qualified symptoms and conditions of selected human larynx diseases. The paper presents graphically selected human larynx diseases.speech analysis pathological speech surgical treatment
Developing eective methods for automatic identication of noise sources is currently one of the most important tasks in long-term acoustical climate monitoring of the environment. Manual verication of recorded data, when it comes to proper determination of noise levels, is time-consuming and costly. A possible solution is to use pattern recognition techniques for acoustic signal recorded by a monitoring station. This paper presents usefulness of special directed measurement techniques, acoustic signal processing, and classication methods using articial intelligence (the Sammon mapping) and learning systems methods (Support Vector Machines) in the recognition of corona audible noise from ultra-high voltage AC transmission lines.
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