This course examines the growing importance of medicine in culture, economics and politics. It uses an historical approach to examine the changing patterns of disease, the causes of morbidity and mortality, the evolution of medical theory and practice, the development of hospitals and the medical profession, the rise of the biomedical research industry, and the ethics of health care in America.

An important diagnostic tool for the electrophysiologist is Electrocardiography (ECG). ECG is utilized clinically to diagnose heart electrical problems. If a cardiac device is indicated, permanent pacing or defibrillation leads are positioned through passive tines or by active fixation with a fixed or an extendable-retractable helix. Often, the myocardial tissue undergoes some localized injury post lead implantation called the current of injury (COI). The device analyzer records a heightened, broadened R-waveform. The clinician is unable to identify if an adequate R-wave is present or if the signal is confounded with the (COI). Clinicians may think an acceptable R-wave ( ≥ 5mV) is captured; however, a R-wave of 10mV during surgery can be reading 3mV one day after implantation once the COI subsides. Moreover, this R-wave over-estimation is correctable by repositioning the lead, but it will not be discovered until post implant, a situation requiring re-opening of the pocket and subjecting the sickly patient to more risks. Therefore, the goal of this project is to develop a research protocol to study the R-wave and (COI) in order to mitigate or to eliminate possible R-wave over-estimation. (J Am Coll Cardiol 2005;45:412-7)

This protocol focuses on active fixation Medtronic leads for atrial/ventricular applications.

This protocol will first attempt to reproduce the methodology of Redferan et al. Then, after lead implantation, the lead will be connected to a Pruka 3 for ten minutes to collect data with time.

This activity will build upon the concepts taught in the lesson The Strongest Pump of All. The activity will pull together the concepts of bioelectricity, electrical circuits, and biology. It will allow the students the opportunity to use deductive and analytical thinking skills in connection with an engineering education. The students will be able to interact with a rudimentary Electrocardiograph circuit and examine the simplicity of the device. The students will be to visualize their own cardiac signal and test the device themselves. The second part of the activity will be a series of worksheets where the students examine different EKG printouts and look for irregularities. The irregularities will be connected to disease detection using EKG.

We propose to develop a blood pressure (BP) monitoring system which can be used for continuous ambulatory blood pressure measurement. The system will be used to measure blood pressure cycles for a person by recording a person’s blood pressure 24 hours a day for 7 days. Blood pressure cycles give an idea of a person’s chronobiological cycle. It has proved that if treatment is administered to a person at appropriate times based on the chronobiological cycle the treatment is more effective. A lot of diseases such as heart attack, stroke, kidney disease, retinopathy, and other major handicapping and fatal diseases can be cured effectively using this method. Presently available BP monitors are bulky, sensitive to motion and cannot be used for continuous monitoring. The proposed system is based on Chen et.al, US Patent No. 6,599,251 which measures blood pressure non invasively using arterial pulse delay. The questions we plan to raised in this project are - what kind of sensors can be used to compute pulse delay, how can we get rid of the motion artifacts and how to make the sensors independent of position sensitivity. To answer these questions we conducted experiments on different sensor configurations and characterized the sensor using the data received. The experimental setup used two piezoelectric sensors that are placed on the wrist and mid arm. The signals from both the sensors are then compared to compute the arterial pulse delay. The sensor characterization results thus achieved are presented in this paper.