1. Monitoring Breathing Signals in Sleep Apnea Patients Using LabVIEW Allison Campbell Bearden High School Young Scholars Summer Program 23 July 2015 University of Tennessee

2. Sleep Apnea Defined: Disruption of breathing during sleep Chronic disorder Disruptions may last up to a few seconds to several minutes depending on severity 5-2

3. Types of Sleep Apnea: Obstructive Sleep Apnea More common type Temporary collapsed airway Central Sleep Apnea Our focus Underdeveloped brain of infant neglects to send signals to the respiratory system during sleep 5-3

4. The Problem: Sleep Apnea is a common, life-threatening health issue. Infants often succumb from Central Sleep Apnea, and nurses and hospital staff cannot constantly monitor each and every child.  One of the leading causes of death infants 5-4

5. Current Treatment 5-5 Mandibular Advancement Device (MAD) Tongue Retaining Device

6. Objective To create a system that alerts caregivers when pediatric patients’ breathing signals are shallower than normal. 5-6

7. LabVIEW Defined: A Visual Programming System Used for Data Acquisition 5-7

8. Project Overview 5-8 In this project I developed a program on the Block Diagram (back panel) that will continuously monitor the simulated breathing signals (from the DAQ card-waveform generator) of sleep apnea patients. If a signal is not detected for longer than 20 seconds, the code will trigger an alarm that would awake the sleep apnea conditioned child in the hospital bed. I created a LabVIEW front panel from where the caregiver in the hospital can easily monitor the child’s current breathing signals.

9. Program on Block Diagram 5-9

10. What caregivers will see and use: 5-10

11. Why is the Program Important? Sleep Apnea affects 48 million people nationwide. It is a chronic disorder that may lead to other serious health risks, such as stroke. 5-11

12. The Path Forward Pairing this program with the proper sensors to attach to the patient and connected to the monitor Clinical Trials Using this method to monitor other types of patients 5-12

13. Acknowledgements This work was supported primarily by the ERC Program of the National Science Foundation and DOE under NSF Award Number EEC-1041877. Other US government and industrial sponsors of CURENT research are also gratefully acknowledged. 13

14. Questions and Answers 14