Cuffless Blood Pressure Estimation Using Single Channel Photoplethysmography: A Two-Step Method

Khalid, Syed Ghufran; Liu, Haipeng; Zia, Tahir; Zhang, Jufen; Chen, Fei; Zheng, Dingchang

doi:10.1109/access.2020.2981903

Cited by 51 publications

(27 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the small sample size, it is difficult to extrapolate their success to larger populations. Other algorithms propose first classifying PPG waveforms into one of three categories (hypotensive, normotensive, or hypertensive), calculating BP according to the category to which the PPG pulse was assigned ( 86 ). This method is an improvement over traditional techniques which apply a generic algorithm to calculate BP regardless of the subject's BP range.…”

Section: Discussion Perspectives and Future Outlookmentioning

confidence: 99%

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Steinman

Barszczyk

Sun

et al. 2021

Front. Digit. Health

View full text Add to dashboard Cite

Regular blood pressure (BP) monitoring enables earlier detection of hypertension and reduces cardiovascular disease. Cuff-based BP measurements require equipment that is inconvenient for some individuals and deters regular home-based monitoring. Since smartphones contain sensors such as video cameras that detect arterial pulsations, they could also be used to assess cardiovascular health. Researchers have developed a variety of image processing and machine learning techniques for predicting BP via smartphone or video camera. This review highlights research behind smartphone and video camera methods for measuring BP. These methods may in future be used at home or in clinics, but must be tested over a larger range of BP and lighting conditions. The review concludes with a discussion of the advantages of the various techniques, their potential clinical applications, and future directions and challenges. Video cameras may potentially measure multiple cardiovascular metrics including and beyond BP, reducing the risk of cardiovascular disease.

show abstract

Section: Discussion Perspectives and Future Outlookmentioning

confidence: 99%

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Steinman

Barszczyk

Sun

et al. 2021

Front. Digit. Health

View full text Add to dashboard Cite

show abstract

“…For the novelty of personalized BP healthcare, the proposed intelligent BP system, using an ultra-lightweight AI algorithm, can establish the tailored BP model from the measured signals from each subject. Compared to the AI-based cuffless BP algorithm in existing datasets, such as the MIMIC [11,14,15], the proposed system provides an adaptive BP regression model for each person based on individually measured signals. Such an intelligent BP system design is suitable for personalized healthcare development.…”

Section: Innovation Of Proposed Intelligent Bio-impedance Systemmentioning

confidence: 99%

“…For the AI in the cuffless BP studies, some groups establish the deep learning model between the physiological signals and arterial BP (ABP) waveforms from the existing databases. For example, Khalid et al [11] provided the single-channel PPG-based cuffless BP estimation model that involved the two databases from the Queensland [12] and the multiparameter intelligent monitoring in intensive care II (MIMIC-II) datasets [13] and satisfied the Association for the Advancement of Medical Instrumentation (AAMI) standard criteria. El-Hajj et al [14] proposed recurrent neural networks (RNN) to establish the correlation between the PPG and BP signals from the MIMIC-II datasets.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement

et al. 2022

View full text Add to dashboard Cite

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.

show abstract

“…Despite these technologies present the high reliable BP performance, the PTT-based method required at least two sensors that could make them unfeasible for wearable applications. Khalid et al [19] provided the single-channel PPG for cuffless BP estimation based on the Queensland and MIMC datasets. Although the technique is calibration-free for BP estimation, it required manual PPG signal pre-processing from datasets during the algorithm training that is not suitable for realistic application.…”

Section: Ccomparison With Previous Studiesmentioning

confidence: 99%

Single-Channel Impedance Plethysmography Neck Patch Device for Unobtrusive Wearable Cardiovascular Monitoring

et al. 2020

View full text Add to dashboard Cite

Background: Wearable and unobtrusive sensing devices are rapidly evolving for long-term cardiovascular monitoring. However, most of the cardiovascular device requires multi-channel physiological signals acquisition, especially in continuous blood pressure (BP) measurement using pulse transition time (PTT) based methods. The multi-devices implementation could impede wearable applications. Objective: This study developed a wearable neck patch device using single-channel impedance plethysmography (IPG) sensing for cardiovascular monitoring, including continuous BP and heart rate (HR) measurement. Methods: IPG-based BP model was derived based on the Bramwell-Hill equation. A patch IPG device was designed and installed above the carotid artery of the subject neck. To validate the BP and HR functions of our device, the Bland-Altman plots were performed to evaluate the estimation error between the reference and the proposed devices within 20 healthy subjects. Results: The BP performance indicates that systolic BP (SBP) estimation error was-0.16 ± 2.97 mmHg and 2.43 ± 1.71 mmHg in terms of mean error (ME) and mean absolute error (MAE), and 0.09 ± 3.30 mmHg and 2.83 ± 1.68 mmHg for diastolic BP (DBP) estimation. Moreover, the HR accuracy has the ME and MAE of 0.02 ± 0.17 bpm and 0.14 ± 0.08 bpm; mean percentage error (MPE) and mean absolute percentage error (MAPE) obtained 0.04 ± 0.23 % and 0.19 ± 0.12 %. Based on statistical results, the BP and HR function of our device satisfied with AAMI/ANSI criteria below 5 ± 8 mmHg and ± 5 bpm or ± 10%. Conclusion: This study implemented a wearable neck patch device with singlechannel IPG acquisition that provided two significant cardiovascular parameters of continuous BP and HR, and its performance agreed with standard criteria based on validation with reference sensors. Significance: The proposed proof-of-concept IPG neck patch device has a high potential for wearable applications and lowcost manufacturing in cardiovascular monitoring.

show abstract

Cuffless Blood Pressure Estimation Using Single Channel Photoplethysmography: A Two-Step Method

Cited by 51 publications

References 28 publications

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement

Single-Channel Impedance Plethysmography Neck Patch Device for Unobtrusive Wearable Cardiovascular Monitoring

Contact Info

Product

Resources

About