Continuous PPG-Based Blood Pressure Monitoring Using Multi-Linear Regression

Haddad, Serj; Boukhayma, Assim; Caizzone, Antonino

doi:10.1109/jbhi.2021.3128229

Cited by 60 publications

(18 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The importance of an HQ classifier is obvious, given the number of significant applications that have been proposed in the last few years. Features extracted from PPG morphology could be used, for example, for stress detection purposes [ 26 , 54 , 55 ] or blood pressure estimation [ 56 , 57 , 58 ], thus allowing for continuous monitoring with a simple wristband. A large part of the population at risk of developing, e.g., burnout syndromes or cardiovascular disease, would benefit from this achievement.…”

Section: Discussionmentioning

confidence: 99%

Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis

Moscato

Giudice

Massaro

et al. 2022

Sensors

View full text Add to dashboard Cite

Photoplethysmographic (PPG) signals are mainly employed for heart rate estimation but are also fascinating candidates in the search for cardiovascular biomarkers. However, their high susceptibility to motion artifacts can lower their morphological quality and, hence, affect the reliability of the extracted information. Low reliability is particularly relevant when signals are recorded in a real-world context, during daily life activities. We aim to develop two classifiers to identify PPG pulses suitable for heart rate estimation (Basic-quality classifier) and morphological analysis (High-quality classifier). We collected wrist PPG data from 31 participants over a 24 h period. We defined four activity ranges based on accelerometer data and randomly selected an equal number of PPG pulses from each range to train and test the classifiers. Independent raters labeled the pulses into three quality levels. Nineteen features, including nine novel features, were extracted from PPG pulses and accelerometer signals. We conducted ten-fold cross-validation on the training set (70%) to optimize hyperparameters of five machine learning algorithms and a neural network, and the remaining 30% was used to test the algorithms. Performances were evaluated using the full features and a reduced set, obtained downstream of feature selection methods. Best performances for both Basic- and High-quality classifiers were achieved using a Support Vector Machine (Acc: 0.96 and 0.97, respectively). Both classifiers outperformed comparable state-of-the-art classifiers. Implementing automatic signal quality assessment methods is essential to improve the reliability of PPG parameters and broaden their applicability in a real-world context.

show abstract

Section: Discussionmentioning

confidence: 99%

Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis

Moscato

Giudice

Massaro

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…When l ( x i , y i , z i ) is 1, it shows that the calculation results of the whole function are relatively complete, and there is no abnormality in the process of collecting damage causes. When l ( x i , y i , z i ) is 0, it shows that the damage cause has reached the limit in the whole collection process, and the coordination of the damage cause is better [ 15 ]. When l ( x i , y i , z i ) is 0.5, it shows that the coordination of damage causes and the collection process are better, and the whole damage causes are in the best.…”

Section: Related Conceptsmentioning

confidence: 99%

[Retracted] Research on Injury Causes and Prevention Effect of College Rowing Athletes Based on Multiple Regression and Residual Algorithm

2022

Journal of Environmental and Public Health

View full text Add to dashboard Cite

Rowing competition in colleges and universities is an international competition, and it is also a favorite competition for college students. However, in the course of rowing competition, the stability of athletes’ injuries often occurs, which is difficult to solve effectively. Aiming at the problem that the loss of athletes in rowing competition in colleges and universities cannot be accurately prevented, this paper puts forward a multiple regression prevention effect model and makes a comprehensive analysis combined with complex reasons. Through the integration of multiple regression and residual analysis, we can better find out the influencing factors, aiming at finding out the causes of athletes’ injuries and putting forward corresponding countermeasures. First of all, analyze the causes of loss, establish a framework of injury prevention for college rowers, and the overall diagnosis framework is reasonable. Then, according to the “University Rowing Prevention and Control Standards” divided into various prevention measures, through the comprehensive prevention and control measure mechanism to get the cause of injury, finally, the optimal combination of various control measures forms a control system. The results of MATLAB show that the combination of multiple regression and residual analysis can improve the accuracy of athletes’ injury prevention and treatment, make the accuracy more than 90%, shorten the diagnosis time less than 10 minutes, and meet the requirements of athletes’ injury diagnosis under normal rowing competition.

show abstract

“…However, when the LED power drops, a remarkable difference in the performance of the two sensors is observed: While the PVT can still reserve all the waveform features without distortion, the organic PT-based PPG has lost a substantial portion of the arterial waveform, as the slow response of the detector can no longer capture the dynamic change of the light absorption by the blood vessels. Notably, the signal fidelity of PPG is important to precisely extract the temporal variation of the systolic peaks to characterize the heart rate ( 44 ) and blood pressure ( 45 ) and that of the diastolic peaks (the second major peak) to estimate artery stiffness ( 46 ).…”

Section: Resultsmentioning

confidence: 99%

Addressing gain-bandwidth trade-off by a monolithically integrated photovoltaic transistor

Chen

Zhao

et al. 2022

Sci. Adv.

View full text Add to dashboard Cite

The gain-bandwidth trade-off limits the development of high-performance photodetectors; i.e., the mutual restraint between the response speed and gain has intrinsically limited performance optimization of photomultiplication phototransistors and photodiodes. Here, we show that a monolithically integrated photovoltaic transistor can solve this dilemma. In this structure, the photovoltage generated by the superimposed perovskite solar cell, acting as a float gate, is amplified by the underlying metal oxide field-effect transistor. By eliminating deep-trap defects through processing optimization, we achieved devices with a maximum responsivity close to 6 × 10 4 A/W, a specific detectivity ( D *) of 1.06 × 10 13 Jones, and an f 3dB of 1.2 MHz at a low driving voltage of 3 V. As a result, a record gain-bandwidth product is achieved. The device further exhibits the advantage in photoplethysmography detection with weak illuminations, where our device accurately detects the detailed features that are out of the capability of conventional photodetectors.

show abstract

Continuous PPG-Based Blood Pressure Monitoring Using Multi-Linear Regression

Cited by 60 publications

References 33 publications

Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis

Wrist Photoplethysmography Signal Quality Assessment for Reliable Heart Rate Estimate and Morphological Analysis

[Retracted] Research on Injury Causes and Prevention Effect of College Rowing Athletes Based on Multiple Regression and Residual Algorithm

Addressing gain-bandwidth trade-off by a monolithically integrated photovoltaic transistor

Contact Info

Product

Resources

About