Document Type



Master of Science (MS)


Electrical Engineering

First Advisor's Name

Wunnava V. Subbarao

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Shahnaz Duara

Third Advisor's Name

Malcolm Heimer

Fourth Advisor's Name

Tadeusz Babij


Respiration, Data processing, Newborn infants, Physiology, Biomedical engineering

Date of Defense



A useful understanding of the respiratory system of premature infants and the factors contributing to different physiological mechanisms and diseases requires extensive clinical research. This project is the result of a need for a fast and reliable system to process the information obtained from biological sources and to obtain results from which different hypothesis can be tested.

This document presents a description of one such system and its different subsystems. It describes the biosignals of interest as well as the stages they have to go through in order to obtain an accurate and valid analysis.

The system is hardware and software oriented. The system hardware is subdivided into instrumentation system, which is used to pick up and condition the signals, and a data acquisition, monitoring and storage system, where the signals are digitized and stored for later processing. The system software, which is the basic and principal component of the project, participates in the hardware control for the data acquisition, storage and monitoring, as well as the posterior stages of signal processing and analysis, which constitute the key of the system.

The biosignals mentioned above can be classified as muscular or EMG, respiratory, chest wall motion, and cardiac signals. The muscular signals are obtained from measuring the electrical activity of the muscles participating in the process of ventilation and the respiratory signals reflect mechanical characteristics of the lungs and airway passages, the chest wall motion signals give a measurement to evaluate the chest wall stability, and the cardiac signals which are measurements of the electrical activity irradiated by the cardiac muscle.

These biosignals require extensive processing, especially the EMG signals, before analysis. The signal processing stage uses digital signal processing techniques which were developed or adapted for this purpose.

The signal analysis stage is based on research protocols and physical relations to evaluate different respiratory parameters. Special data and file handling software was developed and applied as well as graphics software, to accomplish the stages mentioned above.




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