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Signals, Systems, and Biomedical Engineering

Background Information

Biomedical signal processing aims at extracting significant information from physiological signals, which includes:

  • heart rate
  • blood pressure
  • oxygen saturation levels
  • blood glucose
  • nerve conduction
  • brain activity

These signals can then be analyzed in order to provide information to physicians about what is going on in the body and allows them to make a diagnosis if any sort of abnormality is detected. This ultimately allows one to determine the state of a patient's health through non-invasive measures.

As technology is improving, engineers are discovering new ways to provide information to clinicians upon which they can make decisions. One of these improvements is through real-time monitoring, which can lead to the better management of chronic diseases, earlier diagnosis of disease, and earlier detection of both heart attacks and strokes. Biomedical signal processing is most useful in the critical care setting due to patient data needing to be analyzed in real-time. By doing complex analyses of the body's signals and having real-time monitoring, we can discover early indicators for how conditions manifest.

For more information about signals, systems, and biomedical engineering, follow these links:

Examples of Biomedical Signals and Signal Processing

Electrical Biosignals: The electrical signals produced by the body that are extremely useful in diagnostics includes:

  • Electroencephalogram (EEG) - Monitoring method to record electrical activity of the brain. It is most often used to diagnose epilepsy but can be used to diagnose other conditions such as: sleep disorders, tumors, stroke, coma, encephalopathies, brain death, etc.

For more information on EEG, click here

  • Electrocardiogram (ECG) - Monitoring method to record electrical activity of the heart. Indications for performing ECG includes: suspected myocardial infarction, suspected pulmonary embolism, seizures, fainting, cardiac murmur, etc.

For more information on ECG, click here

  • Electromyogram (EMG) - Monitoring method to record electrical activity of the muscle. EMG is used as a diagnostic tool for identifying neuromuscular diseases (Parkinson's, multiple sclerosis, Huntington's, etc) or as a research tool.

For more information on EMG, click here

All three signals listed above require filtering of background noise (power source, other biosignals, etc.) and often require conversion from continuous time (CT) to discrete time (DT) for analysis.

Biosensors: A biosensor is defined as a piece of hardware that can interact with either a biological or physiological system to acquire a signal for diagnostic or therapeutic purposes. They are analytical devices that convert a biological response into an electric signal. Biosensor technology incorporates a wide range of devices, which includes:

  • Stethoscope
  • Thermometer
  • Blood Pressure Cuff
  • Blood Glucose Device
  • Pregnancy Test
  • Pulse Oximetry

To learn more about biosensors, click here

Imaging: Biomedical imaging concentrates on the capture of images for both diagnostic and therapeutic purposes. Snapshots of in-vivo physiology and physiologic processes can be collected through advances sensors and computer technology. Biomedical imaging technologies include:

  • X-ray
  • Magnetic Resonance Imaging (MRI)
  • Ultrasonography
  • Positron Emission Tomography (PET)
  • Single Photon Emission Computed Tomography (SPECT)
  • Optical Coherence Tomography (OCT)
  • Computed Tomography (CT)

Biomedical imaging processing is very similar in concept to biomedical signal processing due to them both including enhancement, analysis, and display of results.

To learn more about imaging, click here

Wearable and Implantable Technologies: Both wearable and implantable technologies sense parameters of various conditions (diseases, disorders, etc.) and can either transfer the data to a remote center (hospital, physicians office, etc.), direct the patient to take specific action, or automatically perform a function based on what the sensors are reading. Examples of these include:

  • Blood glucose - If blood glucose is running high, insulin could be automatically administered from the device
  • Cardiac Monitoring - Pacemaker is placed just under the skin to help control abnormal heart rhythms
  • Parkinson's - Deep brain simulation sends electrical signals to brain areas responsible for body movement
  • Smart Tattoos - Flat, flexible, stretchable electronic sensor placed on the skin to measure various electric signals produced by the heart, brain, and muscles

To learn more about wearable and implantable technologies, click here

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood