Abstract
To achieve the simultaneous and unobtrusive breathing rate (BR) and heart rate (HR) measurements during nighttime, we leverage a far-infrared imager and an infrared camera equipped with IR-Cut lens and an infrared lighting array to develop a dual-camera imaging system. A custom-built cascade face classifier, containing the conventional Adaboost model and fully convolutional network trained by 32K images, was used to detect the face region in registered infrared images. The region of interest (ROI) inclusive of mouth and nose regions was afterwards confirmed by the discriminative regression and coordinate conversions of three selected landmarks. Subsequently, a tracking algorithm based on spatio-temporal context learning was applied for following the ROI in thermal video, and the raw signal was synchronously extracted. Finally, a custom-made time-domain signal analysis approach was developed for the determinations of BR and HR. A dual-mode sleep video database, including the videos obtained under environment where illumination intensity ranged from 0 to 3 Lux, was constructed to evaluate the effectiveness of the proposed system and algorithms. In linear regression analysis, the determination coefficient (R2) of 0.831 had been observed for the measured BR and reference BR, and this value was 0.933 for HR measurement. In addition, the Bland-Altman plots of BR and HR demonstrated that almost all the data points located within their own 95% limits of agreement. Consequently, the overall performance of the proposed technique is acceptable for BR and HR estimations during nighttime.
Highlights
Sleep plays an important role in people’s mental and physical health as well as well-being throughout life
To test the performance of breathing rate (BR) and heart rate (HR) measurements using bimodal imaging system in tandem with proposed algorithms in unobtrusive and contactless manner, two statistical analysis methods namely linear correlation analysis and Bland-Altman plot were applied for validating the data from small-scale pilot experiment
A dual-mode imaging system operating on short-wave infrared and long-wave infrared wavelengths associated with the proposed algorithm can synchronously measure BR and HR during nighttime
Summary
Sleep plays an important role in people’s mental and physical health as well as well-being throughout life. Sleep disorders have been considered as a significant public health issue, with nearly 30 percent of the worldwide adults suffering from them [1]. Some chronic health problems, such as obesity and diabetes, are reported to be correlative with the sleep disorders [3]. It is essential to gather the various sleep related information including sleep time, body movement times, sleep position, heart rate (HR) and breathing rate (BR) for the diagnosis of sleep disorders. To record the sleep related data, the patients have to use many on-body sensors and sleep in the strange environments. This may have an impact on the collection of natural and accurate sleep information. The diagnosis of sleep disorders has become an extremely difficult task
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