scholarly journals Motion and Illumination Resistant Facial Video based Heart Rate Estimation Method using Levenberg-Marquardt Algorithm Optimized Undercomplete Independent Component Analysis

Author(s):  
Ankit Gupta ◽  
Antonio G. Ravelo-García ◽  
Fernando Morgado-Dias

<div>Heart Rate (HR) estimation is of utmost need due to its applicability in diverse fields. Conventional methods for HR estimation require skin contact and are not suitable for scenarios such as sensitive skin or prolonged unobtrusive HR monitoring. Therefore remote photoplethysmography (rPPG) methods have been an active area of research. These methods utilize the facial videos acquired using a camera followed by extracting the Blood Volume Pulse (BVP) signal for heart rate calculation. The existing rPPG methods either used a single color channel or weighted color differences, which has limitations dealing with motion and illumination artifacts. This study considers BVP extraction as an undercomplete problem and proposed a method U-LMA. First, a non-linear Cumulative Density Function (CDF) approximated by a hyperbolic tangent (tanh) was used to deal with the non-linearity associated with rigid and non-rigid motions and illumination variations. Then, the entropy of the proposed non-linear CDF was optimized using a customized LMA for BVP signal extraction, followed by maximum peak estimation for HR calculation. The performance of the proposed method was tested under three scenarios: constrained, motion, and illumination variations scenarios. High Pearson correlation coefficient values and smaller lower-upper statistical limits of bland-altman plots , justified the good performance of the U-LMA. Comparative analysis of U-LMA with undercomplete ICA with negentropy (U-neg) and other state-of-the-art methods demonstrated its best performance of U-LMA by achieving the lowest error and highest correlation values (0.01 significance level) . Additionally, higher accuracy satisfying the clinically accepted error differences also justified its clinical relevance.</div>

2021 ◽  
Author(s):  
Ankit Gupta ◽  
Antonio G. Ravelo-García ◽  
Fernando Morgado-Dias

<div>Heart Rate (HR) estimation is of utmost need due to its applicability in diverse fields. Conventional methods for HR estimation require skin contact and are not suitable for scenarios such as sensitive skin or prolonged unobtrusive HR monitoring. Therefore remote photoplethysmography (rPPG) methods have been an active area of research. These methods utilize the facial videos acquired using a camera followed by extracting the Blood Volume Pulse (BVP) signal for heart rate calculation. The existing rPPG methods either used a single color channel or weighted color differences, which has limitations dealing with motion and illumination artifacts. This study considers BVP extraction as an undercomplete problem and proposed a method U-LMA. First, a non-linear Cumulative Density Function (CDF) approximated by a hyperbolic tangent (tanh) was used to deal with the non-linearity associated with rigid and non-rigid motions and illumination variations. Then, the entropy of the proposed non-linear CDF was optimized using a customized LMA for BVP signal extraction, followed by maximum peak estimation for HR calculation. The performance of the proposed method was tested under three scenarios: constrained, motion, and illumination variations scenarios. High Pearson correlation coefficient values and smaller lower-upper statistical limits of bland-altman plots , justified the good performance of the U-LMA. Comparative analysis of U-LMA with undercomplete ICA with negentropy (U-neg) and other state-of-the-art methods demonstrated its best performance of U-LMA by achieving the lowest error and highest correlation values (0.01 significance level) . Additionally, higher accuracy satisfying the clinically accepted error differences also justified its clinical relevance.</div>


2018 ◽  
Vol 7 (4) ◽  
pp. 42-49 ◽  
Author(s):  
Korkmaz YİĞİTER ◽  
Hakan TOSUN

The aim of this study is to investigate the effects of participation in a 1-week summer camp on thehopelessness and self-esteem of the university students attending Sport Sciences Faculty. Participants were 36university students assigned to experiment group using a random procedure. Coopersmith Self-esteem and Beck Hopelessness Scales were completed at the beginning and end of the summer camp by designed the university. The obtained data were analysed in the SPSS 18.0 program and the significance level was taken as 0.05. The descriptive statistics, independent simple t test, paired simple t test and Pearson correlation were used for analyse the data in the study. According to the results of the research, no significant difference was observed in the comparison of the hopelessness and self-esteem levels between pre and post-test. In addition, there was a significant difference in the hopelessness level of male and female students but any significant difference was not observed in terms of self-esteem. There was a significant relationship between hopelessness and self-esteem pre and post-test. These result shows that a 1-week summer camp cannot change the hopelessness or self-esteem level. However, as the self-esteem rises, the rate of despair decreases whereas as the despair rises, the selfesteem decreases.


2020 ◽  
Vol 16 (1) ◽  
pp. 47-53
Author(s):  
Vicente Benavides-Córdoba ◽  
Mauricio Palacios Gómez

Introduction: Animal models have been used to understand the pathophysiology of pulmonary hypertension, to describe the mechanisms of action and to evaluate promising active ingredients. The monocrotaline-induced pulmonary hypertension model is the most used animal model. In this model, invasive and non-invasive hemodynamic variables that resemble human measurements have been used. Aim: To define if non-invasive variables can predict hemodynamic measures in the monocrotaline-induced pulmonary hypertension model. Materials and Methods: Twenty 6-week old male Wistar rats weighing between 250-300g from the bioterium of the Universidad del Valle (Cali - Colombia) were used in order to establish that the relationships between invasive and non-invasive variables are sustained in different conditions (healthy, hypertrophy and treated). The animals were organized into three groups, a control group who was given 0.9% saline solution subcutaneously (sc), a group with pulmonary hypertension induced with a single subcutaneous dose of Monocrotaline 30 mg/kg, and a group with pulmonary hypertension with 30 mg/kg of monocrotaline treated with Sildenafil. Right ventricle ejection fraction, heart rate, right ventricle systolic pressure and the extent of hypertrophy were measured. The functional relation between any two variables was evaluated by the Pearson correlation coefficient. Results: It was found that all correlations were statistically significant (p <0.01). The strongest correlation was the inverse one between the RVEF and the Fulton index (r = -0.82). The Fulton index also had a strong correlation with the RVSP (r = 0.79). The Pearson correlation coefficient between the RVEF and the RVSP was -0.81, meaning that the higher the systolic pressure in the right ventricle, the lower the ejection fraction value. Heart rate was significantly correlated to the other three variables studied, although with relatively low correlation. Conclusion: The correlations obtained in this study indicate that the parameters evaluated in the research related to experimental pulmonary hypertension correlate adequately and that the measurements that are currently made are adequate and consistent with each other, that is, they have good predictive capacity.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daisuke Miyamori ◽  
Takeshi Uemura ◽  
Wenliang Zhu ◽  
Kei Fujikawa ◽  
Takaaki Nakaya ◽  
...  

AbstractThe recent increase of the number of unidentified cadavers has become a serious problem throughout the world. As a simple and objective method for age estimation, we attempted to utilize Raman spectrometry for forensic identification. Raman spectroscopy is an optical-based vibrational spectroscopic technique that provides detailed information regarding a sample’s molecular composition and structures. Building upon our previous proof-of-concept study, we measured the Raman spectra of abdominal skin samples from 132 autopsy cases and the protein-folding intensity ratio, RPF, defined as the ratio between the Raman signals from a random coil an α-helix. There was a strong negative correlation between age and RPF with a Pearson correlation coefficient of r = 0.878. Four models, based on linear (RPF), squared (RPF2), sex, and RPF by sex interaction terms, were examined. The results of cross validation suggested that the second model including linear and squared terms was the best model with the lowest root mean squared error (11.3 years of age) and the highest coefficient of determination (0.743). Our results indicate that the there was a high correlation between the age and RPF and the Raman biological clock of protein folding can be used as a simple and objective forensic age estimation method for unidentified cadavers.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Aline dos Santos Silva ◽  
Hugo Almeida ◽  
Hugo Plácido da Silva ◽  
António Oliveira

AbstractMultiple wearable devices for cardiovascular self-monitoring have been proposed over the years, with growing evidence showing their effectiveness in the detection of pathologies that would otherwise be unnoticed through standard routine exams. In particular, Electrocardiography (ECG) has been an important tool for such purpose. However, wearables have known limitations, chief among which are the need for a voluntary action so that the ECG trace can be taken, battery lifetime, and abandonment. To effectively address these, novel solutions are needed, which has recently paved the way for “invisible” (aka “off-the-person”) sensing approaches. In this article we describe the design and experimental evaluation of a system for invisible ECG monitoring at home. For this purpose, a new sensor design was proposed, novel materials have been explored, and a proof-of-concept data collection system was created in the form of a toilet seat, enabling ECG measurements as an extension of the regular use of sanitary facilities, without requiring body-worn devices. In order to evaluate the proposed approach, measurements were performed using our system and a gold standard equipment, involving 10 healthy subjects. For the acquisition of the ECG signals on the toilet seat, polymeric electrodes with different textures were produced and tested. According to the results obtained, some of the textures did not allow the acquisition of signals in all users. However, a pyramidal texture showed the best results in relation to heart rate and ECG waveform morphology. For a texture that has shown 0% signal loss, the mean heart rate difference between the reference and experimental device was − 1.778 ± 4.654 Beats per minute (BPM); in terms of ECG waveform, the best cases present a Pearson correlation coefficient above 0.99.


Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2092
Author(s):  
Songbai Song ◽  
Yan Kang ◽  
Xiaoyan Song ◽  
Vijay P. Singh

The choice of a probability distribution function and confidence interval of estimated design values have long been of interest in flood frequency analysis. Although the four-parameter exponential gamma (FPEG) distribution has been developed for application in hydrology, its maximum likelihood estimation (MLE)-based parameter estimation method and asymptotic variance of its quantiles have not been well documented. In this study, the MLE method was used to estimate the parameters and confidence intervals of quantiles of the FPEG distribution. This method entails parameter estimation and asymptotic variances of quantile estimators. The parameter estimation consisted of a set of four equations which, after algebraic simplification, were solved using a three dimensional Levenberg-Marquardt algorithm. Based on sample information matrix and Fisher’s expected information matrix, derivatives of the design quantile with respect to the parameters were derived. The method of estimation was applied to annual precipitation data from the Weihe watershed, China and confidence intervals for quantiles were determined. Results showed that the FPEG was a good candidate to model annual precipitation data and can provide guidance for estimating design values


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kilin Shi ◽  
Tobias Steigleder ◽  
Sven Schellenberger ◽  
Fabian Michler ◽  
Anke Malessa ◽  
...  

AbstractContactless measurement of heart rate variability (HRV), which reflects changes of the autonomic nervous system (ANS) and provides crucial information on the health status of a person, would provide great benefits for both patients and doctors during prevention and aftercare. However, gold standard devices to record the HRV, such as the electrocardiograph, have the common disadvantage that they need permanent skin contact with the patient. Being connected to a monitoring device by cable reduces the mobility, comfort, and compliance by patients. Here, we present a contactless approach using a 24 GHz Six-Port-based radar system and an LSTM network for radar heart sound segmentation. The best scores are obtained using a two-layer bidirectional LSTM architecture. To verify the performance of the proposed system not only in a static measurement scenario but also during a dynamic change of HRV parameters, a stimulation of the ANS through a cold pressor test is integrated in the study design. A total of 638 minutes of data is gathered from 25 test subjects and is analysed extensively. High F-scores of over 95% are achieved for heartbeat detection. HRV indices such as HF norm are extracted with relative errors around 5%. Our proposed approach is capable to perform contactless and convenient HRV monitoring and is therefore suitable for long-term recordings in clinical environments and home-care scenarios.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Kanghyu Lee ◽  
David K. Han ◽  
Hanseok Ko

We propose a novel remote heart rate (HR) estimation method using facial images based on video analytics. Most of previous methods have been demonstrated in well-controlled indoor environments. In contrast, this paper proposes a practical video analytic framework under actual driving conditions by extracting key HR inducing features. In particular, when cars are driven, effective and stable HR estimation becomes challenging as there are many dynamic elements, such as rapid illumination changes, vibrations, and ambient lighting that can exist in the vehicle interior. To overcome those disturbances of HR estimation, the driver face region is first detected and cropped to the region of interest (RoI). Second, the components related to HR are extracted from mixed noisy components using ensemble empirical mode decomposition (EEMD). Finally, the extracted signal is analyzed in frequency domain and smoothed with temporal filtering. To verify our approach, the proposed method is compared with recent prominent methods employing a public HCI dataset. It has been demonstrated that the proposed approach delivers superior performance under driving conditions using Bland-Altman plots.


Author(s):  
Jeremiah Chinnadurai ◽  
Vidhya Venugopal ◽  
Kumaravel P ◽  
Paramesh R

Purpose – Raise in temperatures due to climate change is likely to increase the heat stress in occupations that are physically exerting and performed outdoors which might potentially have adverse health and productivity consequences. The purpose of this paper is to estimate the productivities in construction work under the influence of heat stress using the predicted mean vote (PMV) index. Design/methodology/approach – Field studies were conducted during May 2014 which is summer time in Chennai. Continuous heart rate of workers and wet bulb globe temperature measurements are conducted for workers engaged in different jobs in construction. Metabolic rates and the workload of the workers from heart rate were calculated using the ISO method 8996 and the PMV values are calculated using the tool developed by Malchaire based on the method ISO 7730. Direct observations and personal interviews were conducted to substantiate the productivity estimations. Findings – The results showed that workers working outdoors with moderate and heavy workload exceeded the threshold limit value of 28°C and had adverse productivity impacts (18-35 per cent productivity loss), whereas the workers engaged in light indoor work was not affected by heat stress and consequent productivity losses. The productivity estimations using the PMV index is found to be statistically significant for three types of construction works (Pearson correlation coefficient value of −0.78) and also correlated well with the observations and self-reported productivities of the workers. Originality/value – The method used in this paper provides a scientific and reliable estimation of the productivities which may benefit the industry to set realistic project completion goals in hot weather and also implement interventions and policies to protect workers’ health. Developing adaptive strategies and implementing control measures are the need of the hour to protect worker’s health and economic losses in the face of climate change.


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