Sensor systems for automatic control of abdominal stimulation for respiratory support in tetraplegia

Chen, Wei (2007) Sensor systems for automatic control of abdominal stimulation for respiratory support in tetraplegia. MSc(R) thesis, University of Glasgow.

Abstract

This thesis describes the evaluation of using an inertial measurement unit (IMU) device to measure the movement of the abdomen with the aim to detect different breathing activities and to demonstrate the feasibility to use this technique for automatic control of Functional Electrical Stimulation of Abdominal Muscles (FESAM). People with high-level spinal cord injury (SCI) have difficulties on voluntary breathings, as well as forced respiration, such as cough. The method of FESAM can improve respiratory function. Respiratory activity can be obtained directly by measuring the airflow at the mouth and nose, using a face mask connected to a spirometer. While this approach is suitable in a laboratory environment, the face mask is inconvenient for long-term, every day use. An alternative way to detect respiratory activity is to measure the movement of the abdomen, which is less intrusive and more comfortable. Plethysmography is typically used to measure such movement in sleep studies. In this work, the suitability of an IMU sensor device attached to the abdomen is investigated. Experiments were conducted with 5 neurologically intact subjects with both an IMU and spirometer device. Signals recorded from both sensors during different breathing tasks such as quiet breathing, cough, deep breathing and talking are compared. The phase shifts between the signals from the two sensors are analysed and found to be within +/-U. Analysis of the magnitude of the IMU signals and their power spectrum confirm that it is possible to represent different breathing activities with these sensors. A control system which can detect breathing activity in real-time, and controls a stimulator to generate appropriate electrical stimulations to the abdominal muscles, is also presented in this thesis. A multi characteristic-analysis algorithm has been developed. This enhanced control system can analyse multiple characteristics of the breathing signal in real-time, and uses a flowchart structure to detect breathing activities. The results are used to control the stimulator which delivers suitable electrical stimulations during quiet breathing and coughing. A graphical user interface (GUI) was implemented to interface with the sensor system, control system and stimulator system. This GUI was designed to graphically control the parameters of the entire system, and to show the system results visually. By using the GUI, the entire control system is more accessible to non-technical people. In addition, the control of the three systems becomes easier and is simplified. The possibility to save and load profiles for different patients also makes the configuration of the system more convenient.

• Item Type: Thesis (MSc(R))
• Qualification Level: Masters
• Keywords: Biomedical engineering.
• Colleges/Schools: College of Science and Engineering > School of Engineering
• Supervisor's Name: Gollee, Dr. Henrik
• Date of Award: 2007
• Depositing User: Enlighten Team
• Unique ID: glathesis:2007-71132
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 10 May 2019 10:49
• Last Modified: 06 Jul 2021 17:42
• Thesis DOI: 10.5525/gla.thesis.71132
• URI: https://theses.gla.ac.uk/id/eprint/71132

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