Use of Motion Artifact for the Detection of Respiratory Effort in Polysomnography

Measuring respiratory effort is critical when diagnosing sleep disordered breathing. In this thesis work, the use of detecting respiratory effort by using the movement artifact found in the electromyographic (EMG) and electrocardiographic (ECG) recordings used in polysomnography was investigated. The resulting signals were compared to effort measured with respiratory inductance plethysmography (RIP). The EMG and ECG signals were filtered using the Savitzy-Golay method of smoothing and differentiation of data by simplified least squares to extract the movement artifact. The validity of each resultant waveform was measured using a Pearson product moment correlation coefficient and were studied to determine the most reliable signal. A total of 12 subjects were recorded in a clinical setting, all being evaluated for obstructive sleep apnea. The ability to detect respiratory effort using movement artifact was found to perform best in the masseter. This work shows that movement artifact recovered from the EMG and ECG may be a reliable alternative for the detection of respiratory effort.

Name thesis:degree_name

Master of Science in Biomedical Engineering

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Biomedical Engineering

Grantor

University of Houston

Year dc:date.issued

2018

Author dc:creator

• Tekchandani, Jatin Murlidhar

Advisor dc:contributor.advisor

• Zhang, Yingchun

Committee members dc:contributor.committeemember

• Tiu, Alexander
• Ince, Nuri F.

• Polysomnography, Electromyography, Respiratory Effort

Statement dc:rights

• The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/10657/7872

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/7872