Multichannel Ballistocardiography Based on Virtual Bioinstrumentation

Tato diplomová práce se zabývá zpracováním signálu pořízeného pomocí vícekanálové balistokardiografie. Balistokardiografie je metoda snímání pohybů provázejících kontrakci myokardu a rozšíření arterií v důsledku vypuzení krve. V rešeršní části práce jsou popsány metody snímání a zpracování BKG signálu a jeho využití v různých aplikacích. Studie byla provedena naměřením signálů skupiny dobrovolníků v laboratorních podmínkách. Naměřené signály byly zpracovávány pomocí diskrétní vlnkové transformace a Hilbertovy transformace. Byla také představena metoda detekce J vln v balistokardiografickém signálu na základě rozhodovacích procesů. Z tepových frekvencí byla vykreslována křivka variability srdečního rytmu. Všechny výstupy práce byly statisticky analyzovány porovnáváním se zlatým standardem – EKG.This diploma thesis deals with the processing of a signal acquired using multichannel ballistocardiography. Ballistocardiography is a method of sensing the movements that accompany myocardial contraction and dilation of arteries due to blood expulsion. The research part of the thesis describes the methods of sensing and processing the BCG signal and its use in various applications. The study was performed by measuring the signals of a group of volunteers in a laboratory setting. The measured signals were processed using discrete wavelet transform and Hilbert transform. A method of detecting J waves in a ballistocardiographic signal based on decision-making processes was also introduced. The heart rate variability waveform was then plotted from the heart rates. All outputs of the thesis were statistically analyzed by comparison with the gold standard – ECG.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Wearable and BAN Sensors for Physical Rehabilitation and eHealth Architectures

The demographic shift of the population towards an increase in the number of elderly citizens, together with the sedentary lifestyle we are adopting, is reflected in the increasingly debilitated physical health of the population. The resulting physical impairments require rehabilitation therapies which may be assisted by the use of wearable sensors or body area network sensors (BANs). The use of novel technology for medical therapies can also contribute to reducing the costs in healthcare systems and decrease patient overflow in medical centers. Sensors are the primary enablers of any wearable medical device, with a central role in eHealth architectures. The accuracy of the acquired data depends on the sensors; hence, when considering wearable and BAN sensing integration, they must be proven to be accurate and reliable solutions. This book is a collection of works focusing on the current state-of-the-art of BANs and wearable sensing devices for physical rehabilitation of impaired or debilitated citizens. The manuscripts that compose this book report on the advances in the research related to different sensing technologies (optical or electronic) and body area network sensors (BANs), their design and implementation, advanced signal processing techniques, and the application of these technologies in areas such as physical rehabilitation, robotics, medical diagnostics, and therapy