XXII International Conference on Mechanics in Medicine and Biology - Abstracts Book

This book contain the abstracts presented the XXII ICMMB, held in Bologna in September 2022. The abstracts are divided following the sessions scheduled during the conference

International Conference on NeuroRehabilitation 2012

This volume 3, number 2 gathers a set of articles based on the most outstanding research on accessibility and disability issues that was presented in the International Conference on NeuroRehabilitation 2012 (ICNR).The articles’ research present in this number is centred on the analysis and/or rehabilitation of body impairment most due to brain injury and neurological disorders.JACCES thanks the collaboration of the ICNR members and the research authors and reviewers that have collaborated for making possible that issue

Електроенцефалографски сигнали за управљање рачунарским интерфејсом у неурорехабилитацији

Мозак-рачунар интерфејс (МоРИ) системи могу искористити карактеристичне промене мождане активности корисника као контролне сигнале уређаја (рачунара). Различити ментални задаци или спољашњи стимулуси (визуелни, аудитивни или соматосензорни) индукују промене које су кодиране у спонтаној неуралној активности. Генерисане промене се могу идентификовати мерењем можданих сигнала који представљају директну или индиректну меру електричне активности мозга...Brain Computer Interface (BCI) systems can use characteristic brain neural alterations as control signals of the device/computer. Various mental tasks or external stimulation (visual, auditory or somatosensory) induce changes which are embedded in the spontaneous neural activity. Generated changes can be extracted and identified from the brain-signal recordings that represent the (direct or indirect) measure of electrical neural activity..

Biomedical Sensing and Imaging

This book mainly deals with recent advances in biomedical sensing and imaging. More recently, wearable/smart biosensors and devices, which facilitate diagnostics in a non-clinical setting, have become a hot topic. Combined with machine learning and artificial intelligence, they could revolutionize the biomedical diagnostic field. The aim of this book is to provide a research forum in biomedical sensing and imaging and extend the scientific frontier of this very important and significant biomedical endeavor

A Physiological Signal Processing System for Optimal Engagement and Attention Detection.

In today’s high paced, hi-tech and high stress environment, with extended work hours, long to-do lists and neglected personal health, sleep deprivation has become common in modern culture. Coupled with these factors is the inherent repetitious and tedious nature of certain occupations and daily routines, which all add up to an undesirable fluctuation in individuals’ cognitive attention and capacity. Given certain critical professions, a momentary or prolonged lapse in attention level can be catastrophic and sometimes deadly. This research proposes to develop a real-time monitoring system which uses fundamental physiological signals such as the Electrocardiograph (ECG), to analyze and predict the presence or lack of cognitive attention in individuals during task execution. The primary focus of this study is to identify the correlation between fluctuating level of attention and its implications on the physiological parameters of the body. The system is designed using only those physiological signals that can be collected easily with small, wearable, portable and non-invasive monitors and thereby being able to predict well in advance, an individual’s potential loss of attention and ingression of sleepiness. Several advanced signal processing techniques have been implemented and investigated to derive multiple clandestine and informative features. These features are then applied to machine learning algorithms to produce classification models that are capable of differentiating between the cases of a person being attentive and the person not being attentive. Furthermore, Electroencephalograph (EEG) signals are also analyzed and classified for use as a benchmark for comparison with ECG analysis. For the study, ECG signals and EEG signals of volunteer subjects are acquired in a controlled experiment. The experiment is designed to inculcate and sustain cognitive attention for a period of time following which an attempt is made to reduce cognitive attention of volunteer subjects. The data acquired during the experiment is decomposed and analyzed for feature extraction and classification. The presented results show that to a fairly reasonable accuracy it is possible to detect the presence or lack of attention in individuals with just their ECG signal, especially in comparison with analysis done on EEG signals. The continual work of this research includes other physiological signals such as Galvanic Skin Response, Heat Flux, Skin Temperature and video based facial feature analysis