The aim of this paper was to present an analysis of the feasibility of voice quality prediction on the roughness, breathiness, hoarseness (RBH) scale for children with vocal nodules on the basis of both acoustic parameters and electroglottographic (EGG) examination. The first step to achieve this goal involved the creation of a dedicated database, Voice Pathology Analysis Database (VPADB), containing voice recordings from patients, the EGG signal, medical diagnosis, and the classification of voice quality on the above-mentioned scale. The database also contains data concerning the patients' age and sex. The next step involved performing statistical analyses to test the relationship between the values of objective parameters, such as peak slope and normalized amplitude quotient, and the classification of voice quality. The study made use of voice recordings of 57 patients with vocal nodules and 37 healthy individuals. The RBH classification was carried out by two independent voice specialists. It was found that speech signal parameters can be used to predict expert evaluation with regard to roughness and hoarseness.INDEX TERMS Vocal nodules, acoustic database, voice quality, acoustic analysis, electroglottography. I. INTRODUCTION

The application of IT solutions in medicine makes it possible to develop new, more accurate, and noninvasive medical diagnostics. The aim of this study was to propose this kind of solution. It enables the accurate assessment of vocal nodules in children while measuring glottal insufficiency. The input data includes voice and electroglottographic recordings of patients' voices as well as diagnoses made by practitioners. The recordings were parameterized and used to develop a classifier to assess glottal insufficiency of vocal nodules. The classifier was designed with the help of a genetic algorithm. The diagnoses established thanks to the classifier show a 92% agreement with those reached through medical examination. Such effective performance renders the classifier a useful noninvasive screening tool. We compared our method with Deep Neural Network classifier and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) evolutionary algorithm. The solution that we propose offers a more accurate continuous diagnosis in comparison with the discrete diagnosis of a deep neural network as well as greater accuracy in relation to the CMA-ES algorithm. Another advantage of the proposed solution is the ease with which it can be implemented by healthcare professionals. A Visual Basic for the Applications (VBA) code for LibreOffice macro for the classifier is attached at the end of this paper.

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Electromyography (EMG) is a diagnostic technique allowing for the detection of signals generated by changes in electrical potentials of striated muscles. The application of this technology is becoming an increasingly popular subject of scientific research. With the appearance of new devices retrieving EMG data, novel methods of its processing for various purposes are being developed. One such device is the Myo movement controller, produced by Thalmic Labs (now North). The device has been used for the analysis of muscle activation levels in patients with "tennis elbow" and "golfer’s elbow"—conditions of upper limbs which usually result from occupational injuries. The process of their rehabilitation is complex and requires a continuous monitoring of its progress. The data obtained by means of the Myo controller was used for pattern recognition of an injured hand with relation to the healthy one. The study involved examining ten subjects, including five controls. The results indicate that the muscle activation force is considerably lower in injured individuals. The arithmetic mean for the 6 analyzed motions in the injured group is 38.54% lower. The SmartEMG application ( https://www.smartemg.com ) enables the implementation of procedures performed during an examination as well as those involved in the management of the collected recordings. The study produced satisfactory results, which indicates the possibility of using the Myo controller in the treatment of elbow enthesopathy.

This paper describes the influence of the presence of an obstacle near the flue pipe’s mouth on the air jet, which directly affects the parameters of the sound generated by the flue pipe. Labial pipes of the most common types of mouth were tested. The method of interval calculus was used instead of invasive measuring instruments. The obtained results prove that the proximity of an obstacle affects the sound’s fundamental frequency, as the airflow speed coming out of the flue pipe’s mouth changes. The relationship between the airflow speed, the value of the Reynolds number, and the Strouhal number was also established. The thesis of the influence of the proximity of an obstacle on the fundamental frequency of the sound of a flue pipe was generalized, and formulas for calculating the untuning of the sound of the pipe were presented for various types of mouth.

The chest organ, which gained popularity at the beginning of the 17th century, is a small pipe organ the size of a large box. Several years ago, while compiling an inventory, a previously unidentified chest organ was discovered at St. John the Baptist’s Co-Cathedral in Kamień Pomorski. Regrettably, the instrument did not possess any of its original pipes. What remained, however, was an image of the front pipes preserved on the chest door. The main issue involved in the reconstruction of a historic instrument is the restoration of its original tuning (temperament). Additionally, it is important to establish the frequency of A4, as this sound serves as a standard pitch reference in instrument tuning. The study presents a new method that aims to address the above-mentioned problems. To this end, techniques to search for the most probable temperament and establish the correct A4 frequency were developed. The solution is based on the modeling of sound generation in flue pipes, as well as statistical analysis to help match a model to the parameters preserved in the chest organ drawing. Additionally, differentalues of the A4 sound values were defined for temperatures ranging from 10 ∘C to 20 ∘C. The tuning system proposed in 1523 by Pietro Aaron proved to be the most probable temperament. In the process of testing the developed flue pipe model, the maximum tuning temperature was established as 15.8 ∘C.

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