Non-contact Heart Rate Measurement Research Articles

Non-contact video-based estimation of heart rate variability spectrogram from hemoglobin composition

Non-contact HR measurement is becoming an active research area. Recently, remote photoplethysmography (rPPG) measurement based on simple skin optics model has been proposed and shown to be effective. In this paper, we propose an accurate remote observation of the heart rate (HR) and heart rate variability (HRV) based on hemoglobin component estimation which is based on a detailed skin optics model. We perform experiments to measure subjects at rest and under cognitive stress with the proposed method putting a polarized filter in front of the camera to evaluate the principle of the framework. From the results of the experiments, the proposed method shows a high correlation with the electrocardiograph (ECG) which is assumed as the ground truth. We also evaluate the proposed method without putting any polarized filter and confirm the usefulness for the remote observation of HRV which requires accurate detection of HR.

Non-contact robust heart rate estimation using HSV color model and matrix-based IIR filter in the face video imaging.

The heart rate (HR) is one of the important indicators for observing the patient condition. Therefore, many estimation techniques for acquiring heart rate have been developed. The photoplethysmography (PPG) and electrocardiography (ECG) are the common measurement techniques for estimating the heart rate. However, they should contact on the human skin in order to estimate the accurate heart rate. In this paper, we propose a non-contact robust heart rate measurement method using a webcam device. In addition, we evaluated the performance of the proposed algorithm in comparison with other algorithms.

Letter to the Editor “On the Feasibility of Noncontact ECG Measurements”

The article by Kranjec et al. [1] , “Novel methods of noncontact heart rate measurement: A feasibility study” is interesting and informative as it compares different contactless methods for heart rate detection. Nevertheless, the use of the term “capacitively coupled ECG” (CCECG) in the article is confusing and may mislead readers.

Spatio-temporal filtering of thermal video sequences for heart rate estimation

In this paper, a novel method for non-contact measurement of heart rate using thermal imaging was proposed. Thermal videos were recorded from subjects’ faces. The measurements are performed on three different areas: the whole face, the upper half of the face and the supraorbital region. A tracker was used to track these regions to make the algorithm invulnerable to the subject's motion. After tracking, the videos were spatially filtered using a full Laplacian pyramid decomposition to increase the signal to noise ratio; next, the video frames were successively temporally filtered using an ideal bandpass filter for extracting the thermal variations caused by blood circulation. Finally, the heart rate was calculated by using two methods including zero crossing and Fast Fourier Transform. For evaluating the results, the complement of absolute normalized difference (CAND) index was used which was introduced by Pavlidis. This index was 99.42% in the best case and 92.472% in average for 22 subjects. These results showed a growth in CAND index in comparison with previous work. Zerocrossing outperformed FFT because of the nonstationary nature of thermal signals. Another benefit of our method is that, the videos are taken from the face unlike most of the studies that take it from the neck and Carotid. Neck and carotid are less accessible than faces. Finally, the optimum ROI for estimating the heart rate from face was identified.

Noncontact measurement of heart rate using facial video illuminated under natural light and signal weighted analysis.

Non-contact and remote measurements of vital physical signals are important for reliable and comfortable physiological self-assessment. We presented a novel optical imaging-based method to measure the vital physical signals. Using a digital camera and ambient light, the cardiovascular pulse waves were extracted better from human color facial videos correctly. And the vital physiological parameters like heart rate were measured using a proposed signal-weighted analysis method. The measured HRs consistent with those measured simultaneously with reference technologies (r=0.94, p<0.001 for HR). The results show that the imaging-based method is suitable for measuring the physiological parameters, and provide a reliable and comfortable measurement mode. The study lays a physical foundation for measuring multi-physiological parameters of human noninvasively.

Novel Methods for Noncontact Heart Rate Measurement: A Feasibility Study

The following paper investigates four novel methods for noncontact measurement of heart rate (HR) and consequently its derivate HR variability, an important marker of autonomic activity proven to be predictive of likelihood of future health related events. Feasibility study of basic principles is focused on measurements of signal-to-noise ratio with respect to the distance between the subject and HR sensor/apparatus. The discussed methods are divided into the following two groups: the methods measuring electromagnetic energy generated by the bioelectrical activity within the cardiac muscle (referred to as direct methods), and the methods measuring displacement of a part of the subject's body caused by the periodic physical contractions of the heart (referred to as indirect methods). The first group is represented by a measuring device which detects changes in surrounding electric field, whereas the second group consists of measuring devices that use the Doppler effect phenomena (microwave radar, ultrasound radar) and audio signal acquired by a condenser microphone. All measuring devices were assembled and put to test. The results indicate that noncontact measuring of HR is possible, especially for distances of less than 50 cm meeting essential requirements for HR diagnostic purposes.

A Novel Thermal Measurement for Heart Rate

Heart rate is an important indicator for the mental and physical state, but it is usually measured through physical contact. In this paper, a novel non-contact method of heart rate measurement has been proposed from the infrared sequence images. First, a square region of interest (ROI) was manually selected to cover the temple on the first frame. Then a head movement detection algorithm based on the centroid coordinate change of the extracted skin area was applied to the infrared sequence images, and according to the movement result, the ROI location in subsequent frames could be identified. After that, the distance between the gravity center and the top-left corner in every ROI is computed to get a time-lapse signal. Finally, the discrete wavelet transform and an autoregressive model were used respectively to recognize the heart rate. Fourteen healthy subjects (24-29 years of age, 4 females and 10 males) participated in the experiment. Compared with the concomitant ECG, mean accuracy rate of 94.5% was acquired. The results show the potential of our method for non-contact heart rate measurement.

Need for a Revision of the Normal Limits of Resting Heart Rate

The current definition of sinus tachycardia is a heart rate >100 beats per minute (bpm).1 This limit was set arbitrarily when heart rate was not yet regarded as a risk factor for cardiovascular disease, probably with the main purpose of distinguishing between a disease state (fever, thyrotoxicosis, anemia, congestive heart failure, etc) and a normal condition. In recent years, interest has been aroused by the awareness that fast heart rate is a potent precursor of hypertension, atherosclerosis, and their sequelae.2 3 4 5 6 7 8 9 10 In addition, many leading epidemiological studies have shown that tachycardia is associated with an increased risk of death from cardiovascular and noncardiovascular causes. This relationship has been found in general populations,3 4 5 6 7 in elderly individuals,9 and in hypertensive cohorts.10 In all of these studies, the heart rate value above that in which a significant increase in risk was observed was below the 100 bpm threshold (Table 1⇓). Only in the study by Levy et al3 was tachycardia defined as a heart rate >99 bpm, but in that study the cutoff between normal and high heart rate was chosen arbitrarily, and the highest heart rate value measured during the examination was taken to define the subject’s heart rate. In all the other studies, the threshold level between normal and fast heart rate was between 79 and 90 bpm. View this table: Table 1. Heart Rate Values Above Which a Significant Increase in Risk Was Found: Data From 9 Epidemiological Studies The normalcy limits of a clinical variable can be established according to different criteria. For many parameters, such as most biochemical indexes, the 95% confidence interval is calculated to identify the upper normal limit of the variable. This statistical approach does not appear suitable for those clinical variables …