Image Sensor-Based Heart Rate Evaluation From Face Reflectance Using Hilbert–Huang Transform

Abstract

Monitoring heart rates using conventional electrocardiogram equipment requires patients to wear adhesive gel patches or chest straps that can cause skin irritation and discomfort. Commercially available pulse oximetry sensors that attach to the fingertips or earlobes also cause inconvenience for patients and the spring-loaded clips can be painful to use. Therefore, a novel robust face-based heart rate monitoring technique is proposed to allow for the evaluation of heart rate variation without physical contact with the patient. Face reflectance is first decomposed from a single image and then heart rate evaluation is conducted from consecutive frames according to the periodic variation of reflectance strength resulting from changes to hemoglobin absorptivity across the visible light spectrum as heartbeats cause changes to blood volume in the blood vessels in the face. To achieve a robust evaluation, ensemble empirical mode decomposition of the Hilbert-Huang transform is used to acquire the primary heart rate signal while reducing the effect of ambient light changes. Our proposed approach is found to outperform the current state of the art, providing greater measurement accuracy with smaller variance and is shown to be feasible in real-world environments.Index Terms-Computer vision, biomedical signal processing.

Smartphone-based heart-rate measurement using facial images and a spatiotemporal alpha-trimmed mean filter

“…Figures 5(a) and 5(b) show the results of the second experiment via Bland-Altman plots. In [11], the error variation range was approximately 17 bpm, and our margin of error was approximately 13 bpm. These results show that in addition to operating as intended, the system proposed in the present study outperformed the PC-based platform, despite the limited computational resources of the mobile phone.…”

“…To understand the relative effectiveness of the proposed system in heart-rate estimation, we used the system proposed in [11] as a comparison target. This system was compared because the same equipment was used to obtain the ground truth.…”

“…This system was compared because the same equipment was used to obtain the ground truth. Furthermore, because a Bland-Altman plot rather was adopted in [11], we used a Bland-Altman plot to compare the performance. The test conditions in [11] were identical to Condition A; therefore, we performed the tests under Condition A to achieve an objective comparison.…”

“…The results indicated that optimal performance can be obtained by estimating the heart rate directly from a green-channel intensity image. Chen et al [11] proposed a framework for decomposing brow reflectance from the green channel and then decomposing intrinsic mode functions by using ensemble empirical mode decomposition to separate the effect component that represents the real heart-rate variation from environmental noise.…”

Remote assessment of heart rate by skin color processing

“…Much research has been done to measure the diffuse reflectance spectra from the original image [11,12]. Indirect information about the reflectance can be obtained if absorption spectrum is known [13,14].…”