Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Respiratory Muscle Strength Training to Improve Vocal Function of Patients with Presbyphonia

Background: Presbyphonia is an age-related voice disorder characterized by vocal fold atrophy, and its effects on voice are potentially compounded by declines in respiratory function. We assessed: 1) the relationships between respiratory and voice function; 2) the effect of adding respiratory exercises to voice therapy; and 3) the impact of baseline respiratory function on the response to therapy in patients with presbyphonia. Methods: Twenty-one participants underwent respiratory and voice assessments, from which relationships were drawn. Ten of these participants were blocked-randomized to receive either voice exercises only, or voice exercises combined with inspiratory muscle strength training or expiratory muscle strength training, for a duration of four weeks. Results: FVC, FEV1, and MEP had an impact on phonation physiology through their effect on aerodynamic resistance and vocal fold pliability. Percent predicted values of FVC and FEV1 were strong predictors of perceived voice handicap. IMST induced the largest improvements in perceived handicap, and a lower baseline respiratory function was associated with a greater improvement, regardless of the intervention received. Conclusion: Respiratory function impacts voice and the response to behavioral voice therapy. Adding IMST to voice exercises improves self-reported outcomes even in patients with a normal respiratory function

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Effect of nutritional factors on the growth and production of biosurfactant by Pseudomonas aeruginosa strain 181

The growth and production of biosurfactant by P. seudomonas aeruginosa (181) was dependant on nutritional factors. Among the eleven carbon sources tested, glucose supported the maximum growth (0.25 g/L) with the highest biosurfactant yield and this was followed by glycerol. Glucose reduced the surface tension to 35.3 dyne/ cm and gave an E24 reading of 62.7%. Butanol gave the lowest growth and had no biosurfactant production. For the nitrogen sources tested, casamino acid supported a growth of 0.21 g/L which reduced the surface tension to 41.1 dyne/cm and gave an E24 reading of 56%. Soytone was assimilated similarly, with good growth and high biosurfactant production. Corn steep liquor gave the lowest growth and did not show any biosurfactant activity

Passive acoustic monitoring for assessment of natural and anthropogenic sound sources in the marine environment using automatic recognition

In the marine environment, sound can be an efficient source of information. Indeed, several marine species, including fish, use sound to navigate, select habitats, detect predators and prey, and to attract mates. Therefore, all the abiotic, biotic and manmade sounds that comprise the soundscape, have the potential to be used to assess and monitor species and marine environments. Passive acoustic monitoring (PAM) involves the use of acoustic sensors to record sound in the environment, from which relevant ecological information can be inferred. This thesis studied marine soundscapes, with special attention on fish communities, anthropogenic noise, and applied several methods to analyse acoustic recordings. Most of the focus was on the Tagus estuary, where the presence of two highly vocal species is known: the Lusitanian toadfish (Halobatrachus didactylus) and the meagre (Argyrosomus regius). Azorean and Mozambique soundscapes were also analysed. Several methods were applied to extract information and to visualize soundscape characteristics, including sound recognition systems based on hidden Markov models to recognize fish sounds and boat passages. Analysis of several types of marine environments and time scales showed several advantages and disadvantages of different methods. The use of sound pressure level on different frequency bands allowed the quantification of daily and seasonal patterns. Ecoacoustic indices appear to be cost-effective tools to monitor biodiversity in some marine environments. Using automatic recognition, vocal rhythms (diel and seasonal patterns) and vocal interactions among individuals were also characterized. Furthermore, boat noise effects on fish were studied: we encountered impacts on the audition, vocal behaviour and reproduction. Overall, we used PAM as a tool to remotely assess and monitor soundscapes, biodiversity, fish communities’ seasonal patterns, fish behaviour, species presence, and the effect of anthropogenic noise aiming to contribute for the management and conservation of marine ecosystems

Signal processing for automated EEG quality assessment

An automated signal quality assessment method was proposed for the EEG signals, which will help in testing new BCI algorithms so that the testing can be made on high quality signals only. This research includes the development of novel feature extraction technique and a new clustering algorithm for EEG signals

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 197, September 1979

This bibliography lists 193 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1979

Signal Processing Using Non-invasive Physiological Sensors

Non-invasive biomedical sensors for monitoring physiological parameters from the human body for potential future therapies and healthcare solutions. Today, a critical factor in providing a cost-effective healthcare system is improving patients' quality of life and mobility, which can be achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions

Medical Informatics and Data Analysis

During recent years, the use of advanced data analysis methods has increased in clinical and epidemiological research. This book emphasizes the practical aspects of new data analysis methods, and provides insight into new challenges in biostatistics, epidemiology, health sciences, dentistry, and clinical medicine. This book provides a readable text, giving advice on the reporting of new data analytical methods and data presentation. The book consists of 13 articles. Each article is self-contained and may be read independently according to the needs of the reader. The book is essential reading for postgraduate students as well as researchers from medicine and other sciences where statistical data analysis plays a central role