| Cardiovascular Diseases (CVDs) have been a major cause for deaths in both men and women in United States. Cerebrovascular Diseases like Strokes are known to have origins in CVDs as well. Moreover, nearly 18 Million Americans have a history of myocardial infarction and are currently undergoing cardiac rehabilitation. Consequently, CVDs are the highest costing disease groups and cost more than all types of cancer combined. However, significant cost reduction is possible through the effective use of the vast advances in embedded and pervasive electronic devices for healthcare. These devices can automate and move a significant portion of disease management to the patient's home through cyber connectivity, a concept known as point-of-care (POC) diagnostics and healthcare services. POC can minimize hospital visits and potentially avoid admission altogether with prognostic tools that give advanced notice of any abnormalities or chronic illnesses so that the treatment can be planned in advance. The POC concept requires continuous remote health monitoring. Therefore, the various sensors needed for comprehensive monitoring need to be worn daily and throughout the day. Moreover, true "roaming" capability is necessary so that it does not restrict the user's travel or his/her quotidian activities. Two biomedical signals namely, Electrocardiogram (ECG) and Blood Pressure are important diagnostic tests in assessing the cardiac health of a person. To that end, the research presented in this thesis: First , describes the development of a remote monitoring solution based on Bluetooth(TM), smartphones and cyber infrastructure for cardiac care called e-nanoflex. Second, Sensors for ECG that are compatible with everyday life style namely, (a) dry, gel-less vertically aligned gold nanowire electrodes, (b) dry textile-based conductive sensor electrodes to address the need for this technology to monitor cardiovascular diseases in women are tested with e-nanoflex and discussed. Third, non-invasive, cuff-less Blood pressure estimation based on Pulse Transit Time with multiple synchronized sensor nodes, is implemented with e-nanoflex and the results are discussed. |
