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Changing the way we monitor breathing volume in hospitals and at home.

Computer Science faculty and students develop wireless monitoring system.

Diseases such as asthma, tuberculosis and chronic obstructive pulmonary disease (COPD) are characterized by a decreased flow of oxygen, which can be measured and determined by continuous monitoring of breathing volume.

A team of faculty and students from the Department of Computer Science and Engineering, in collaboration with the CU School of Medicine and Children’s Hospital Colorado, have developed a wireless system called WiSpiro to continuously monitor breathing volume in an unobtrusive manner. Tam Vu, assistant professor of computer science, is leading the effort, along with associate professor Min Choi, professor Ann Halbower from the CU School of Medicine, and computer science PhD student Phuc Nguyen. The National Science Foundation awarded the project $575,000 to improve the technology they’ve developed.

“Essentially what we’re trying to do is improve the practice of sleep monitoring and child care through wireless and mobile technologies,” said Vu. “Our solution is less expensive, more efficient, more convenient and has a higher efficacy.”

Current sleep monitoring practices typically involve attaching a number of sensors to a person’s face and to their chest, which makes it difficult for the subject to sleep normally. To monitor breathing, use of a camera requires a direct line of sight between the camera and the person. This is problematic in that people are typically covered in clothing and blankets and tend to change position while sleeping. Vu’s solution aims to overcome these obstacles.

WiSpiro consists of a transmitter and a receiver, and it moves autonomously. The sensors are designed to detect posture based on a determined point on the person’s chest. When the subject’s posture changes during sleep, the machine autonomously moves to follow them.

According to Vu, the high-level idea is to beam a signal to the person’s chest. When the signal returns, one property of the signal—the phase—will change. The phase depends on the distance between the transmitter and the chest. WiSpiro uses an algorithm to extract changes in phase. From that, it determines the distance, which is then used to determine the volume. Breathing volume will show whether airflow is normal; the data collected is then used to diagnose disease related to lung defects or disorders such as sleep apnea.

“Existing technology is obtrusive and prone to error,” Vu said. “We hope to make it less obtrusive for safer, long-term monitoring.”

Thanks to funds from the university’s Office of Research Services, the team has developed a WiSpiro prototype to demonstrate it can continuously monitor the user’s breathing volume with precision.

“Our system is accurate and practical,” says Vu. “When compared with current gold-standard technologies (e.g., the FDA-approved spirometer) used to measure accuracy, we’re just as accurate more than 95 percent of the time.”

While there are challenges to overcome, Vu and his team continue to make progress, improving accuracy and overcoming some of the challenges they’ve faced in developing the system. The goal, however, remains the same: to improve the practice of sleep monitoring through wireless and mobile technologies.

Follow the progress of the WiSpiro project at

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