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John O | September 2017

Software turns mobile phones into thermal breathing monitors


researchers from university college london (u.k.) have created a new software program that turns mobile phones into low-cost, thermal cameras that can track how fast a person is breathing and has the potential for monitoring breathing issues in people.

 


new software allows low-cost, thermal cameras attached to mobile phones to track breathing patterns. (youngjun cho, university college london)

 

according to a report from the optical society (osa), the research team demonstrated the camera’s effectiveness during real-world simulations, movements, and temperature changes.

 

“in addition to detecting breathing problems, the new approach could one day allow the camera on your computer to detect subtle breathing irregularities associated with pain or stress and then send prompts that help you relax and regulate breathing,” the report explained.

 

“although traditional video cameras can be used to track breathing, they don’t work well in low-light situations and can cause privacy concerns when used for monitoring in nursing homes, for example.”

 

to overcome issues with movement or variable temperatures, the researchers created algorithms applicable to any thermal imaging camera to accurately track the nostrils of a person who is moving. the algorithms also read the nostril area as a 3-d surface to create a more accurate measurement of temperature.

 

“in addition to indoor laboratory tests,” the report continued, “the researchers used the mobile thermal imaging approach to measure the breathing of volunteers in a scenario that involved breathing exercises with changes in ambient temperature and in a fully unconstrained test where volunteers walked around inside and outside of a building.”

 

during those tests, the camera was kept 20-30 centimeters from a person’s face thanks to a rig attached to a hat. the camera was connected by a cord to the subject’s phone. the researchers showed that the new algorithm works better than other methods.

 

according to the article, “the researchers took their work one step further by inferring a person’s mental load or stress through automatic breathing analysis. they used their thermal imaging software to track the breathing of people who were free to move around while performing various types of tasks, and the results aligned well with findings from studies that used much more sophisticated equipment, indicating the portable thermal-camera based approach could be a useful tool for apps that help people relax.”

 

the research was recently published in biomedical optics express. the abstract read:

 

“the ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. in many situations, mobile methods, which allow users to undertake everyday activities, are required. however, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. alternatively, contactless digital image sensor based remote-photoplethysmography (ppg) can be used.

 

“however, remote ppg requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. however, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors).

 

“this challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. in this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes.

 

“the approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. it has three main contributions. the first is a novel optimal quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. the second is the thermal gradient flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. finally, we introduce the thermal voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method.

 

“we demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). we also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion.

 

“we open the tracked roi sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.”

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