In order to accurately detect the heart rate in the ECG signal, filter banks analysis in Matlab is used on the filtered ECG signal. This algorithm can also be used to detect abnormalities in the ECG signal. LabVIEW is then used to notify the user of the results. This includes displaying the heart rate and alerting the user if an abnormality is detected.

This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done on the MIT Server in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.

This Collection contains all the necessary background information you need to build an ECG that not only detects the heart rate but can also detect other heart abnormalities automatically. We include the circuit we used to build a three lead ECG as well as the LabVIEW and Matlab code we used.

How to build a circuit that allows for the live collection of ECG signals using the three lead set-up. Also, this module describes the filters used to remove noise from the signal. Since the ECG is a relatively low frequency signal, most of the high frequency noise can be filtered out. However, due to arm muscle movements, there will also be low frequency noise that will always remain with the signal.

This course covers the following topics: conduction, diffusion, convection in electrolytes; fields in heterogeneous media; electrical double layers; Maxwell stress tensor and electrical forces in physiological systems; and fluid and solid continua: equations of motion useful for porous, hydrated biological tissues. Case studies considered include membrane transport; electrode interfaces; electrical, mechanical, and chemical transduction in tissues; electrophoretic and electroosmotic flows; diffusion/reaction; and ECG. The course also examines electromechanical and physicochemical interactions in biomaterials and cells; orthopaedic, cardiovascular, and other clinical examples.

This course covers the following topics: conduction, diffusion, convection in electrolytes; fields in heterogeneous media; electrical double layers; Maxwell stress tensor and electrical forces in physiological systems; and fluid and solid continua: equations of motion useful for porous, hydrated biological tissues. Case studies considered include membrane transport; electrode interfaces; electrical, mechanical, and chemical transduction in tissues; electrophoretic and electroosmotic flows; diffusion/reaction; and ECG. The course also examines electromechanical and physicochemical interactions in biomaterials and cells; orthopaedic, cardiovascular, and other clinical examples.

Students design and carry out an experimental procedure that will allow them to determine the effect of an experimental variables on pulse rate, blood pressure, respiratory volumes, or other related cardiopulmonary functions such as rate of breathing.

In this lab, the student will review the physiology of the organ systems by using images of models, experiments, and videos. Then the student will be asked to assess his or her knowledge, which can eventually be put to practical or experimental use. Upon successful completion of this lab supplement, students will be able to: describe techniques used to measure the function of organ systems; relate diagnostic tools, such as those used to measure ECG, EEG, and EMG activity, and those used in spirometry and urinalysis tests, to the physiological processes; relate diagnostic tests, such as the patellar and plantar reflex tests, to physiological processes; perform laboratory observations and experiments; collect, analyze, and interpret data; and form conclusions. (Biology 304 Laboratory)

Background information necessary to build an ECG that automatically detects heart arrhythmias and abnormalities. This includes the physiologic background of the ECG, how it works and the ECG characteristics of two heart abnormalities that our system can detect.