MIT course addresses cardiorespiratory physiology for engineers
Engineers play an increasingly important role in medicine, designing medical electronics devices for clinical and home environments. Unfortunately, there can be an impedance mismatch inhibiting the flow of information between engineers and clinicians, according to Thomas Heldt, a professor in biomedical engineering at MIT.
Facilitating communications between engineers and physicians is one goal of an MIT program titled Quantitative Cardiorespiratory Physiology and Clinical Applications for Engineers. Lead instructors are Heldt and Roger G. Mark, a professor of health sciences and technology and a professor of electrical engineering at MIT who also received MD from Harvard Medical School. They will be joined during the five-day course, scheduled for June 12 through June 16 Cambridge, by guest lecturers, including clinical experts from local hospitals.
This course is an update of the three-day course titled “Quantitative Cardiovascular Physiology and Clinical Applications for Engineers” held over the last two years; this year’s version adds the component on respiratory physiology.
The course grew out of the recognition that engineers are developing a growing number of smart wearable and other healthcare devices focused on managing cardiovascular disease, which remains the number-one killer in America and worldwide. However, these engineers frequently lack a solid understanding of underlying physiology of cardiovascular and respiratory systems. Engineers, physicians, and patients would all benefit, Heldt said in a recent phone interview, if engineers had a better understanding of the physiological systems for which they are designing their electronics.
Unfortunately there are few opportunities to gain that understanding. Heldt said an engineer perusing medical-school literature would quickly become discouraged at the molecular-level detail. Consequently, “There is often a mismatch between what an engineer wants to develop and what physicians need to improve their way of taking care of patients,” Heldt said. “Even if the engineer’s invention is sleek, if it doesn’t fit into the physician’s workflow it is unlikely to be successful.” (Heldt noted that the situation is similar to that with electronic medical records, which doctors resist.)
For cardiovascular applications, Heldt proposes a “resistors and capacitors” approach to viewing the heart as an electrophysiological pump with a control system that regulates parameters such as blood pressure. The goal is to help break down the language barrier between the engineer and physician.
Heldt’s “resistors and capacitors” phrase may suggest a model-based approach to learning, and indeed students will learn how to represent and analyze the function of the cardiovascular and respiratory systems using simple circuit models. But they will also gain an understanding the functional anatomy of the cardiovascular system through the dissection of a bovine heart, Heldt said.
Other takeaways will include an understanding of the function of the heart, the peripheral circulation, and the respiratory system in health and disease states; of the major neurohumoral control mechanisms that maintain blood-pressure homeostasis; and of commonly measured hemodynamic signals and what they reveal about the state of the cardiovascular system. Students will also learn the physical basis of clinical electrocardiography and learn how to analyze arrhythmias from electrocardiographic recordings.
The course places a needed emphasis on the clinical environment that’s often missing in the simulation and big-data environments in which engineers might address medical design and development. During a session focused on medicine during a 2014 MIT online course on big data, John Guttag, a professor of electrical engineering and computer science who makes use of data from sources ranging from ECG signals to biomarkers and video-based monitoring, said, “I believe firmly that over the next decade or so, computer scientists will do more to change medicine than anybody else on earth.”
Heldt acknowledged a role for big data. But he emphasized a need for quality control and preprocessing to throw out records that are suspect. Clinicians are very good at knowing which data elements to discount, he said, noting that many data sets are sparsely sampled and biased toward people who are very sick.
“Don’t put all your eggs in the analytical basket and throw out 200 years of clinical experience just because you have a few more data sets,” he added. “I don’t expect in my lifetime that a computer will take over for a doctor.”
The course targets R&D engineers and managers from industry, academia, and healthcare settings who are actively engaged in biomedical engineering applications (from hardware development and signal processing to clinical applications). It will also be of interest to hardware engineers and managers working on wearable device development for mobile and ubiquitous vital-sign monitoring, software engineers and managers working on algorithm development for patient-monitoring applications, and clinical engineers and managers working in hospital environments to support clinical operations.
The course will be held June 6-12 in Cambridge. For more information and to register, visit MIT Professional Education. The course can also be offered at your organization’s site for groups of employees.
Source: Evaluation Engineering