Learning and non-learning algorithms for cuffless blood pressure measurement: a review

Agham, Nishigandha Dnyaneshwar; Chaskar, Uttam

doi:10.1007/s11517-021-02362-6

Cited by 12 publications

(6 citation statements)

References 105 publications

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“…The majority of publications focus on new technologies to estimate BP without a cuff, incorporating machine learning [12], deep learning [13], neural networks [14,15], ballistocardiogram gating and wave localization [16], flexible wearable pressure sensors [17], and ECG monitoring with photoplethysmography [18]. There are at least 17 reviews covering, for example, 'learning and nonlearning algorithms' [19], automated detection of hypertension using physiological signals [20], possibilities for artificial intelligence in managing hypertension [21], single [22] and multisite photoplethysmography technologies to monitor BP [23]. Several articles claim to be 'validation studies' but too often no appropriate protocol for cuffless BP devices was used [7].…”

Section: Scientific Patents Publications and Market For Cuffless Bloo...mentioning

confidence: 99%

Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability

Stergiou

Mukkamala

Avolio

et al. 2022

Journal of Hypertension

111

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Background:Many cuffless blood pressure (BP) measuring devices are currently on the market claiming that they provide accurate BP measurements. These technologies have considerable potential to improve the awareness, treatment, and management of hypertension. However, recent guidelines by the European Society of Hypertension do not recommend cuffless devices for the diagnosis and management of hypertension.Objective:This statement by the European Society of Hypertension Working Group on BP Monitoring and Cardiovascular Variability presents the types of cuffless BP technologies, issues in their validation, and recommendations for clinical practice.Statements:Cuffless BP monitors constitute a wide and heterogeneous group of novel technologies and devices with different intended uses. Cuffless BP devices have specific accuracy issues, which render the established validation protocols for cuff BP devices inadequate for their validation. In 2014, the Institute of Electrical and Electronics Engineers published a standard for the validation of cuffless BP devices, and the International Organization for Standardization is currently developing another standard. The validation of cuffless devices should address issues related to the need of individual cuff calibration, the stability of measurements post calibration, the ability to track BP changes, and the implementation of machine learning technology. Clinical field investigations may also be considered and issues regarding the clinical implementation of cuffless BP readings should be investigated.Conclusion:Cuffless BP devices have considerable potential for changing the diagnosis and management of hypertension. However, fundamental questions regarding their accuracy, performance, and implementation need to be carefully addressed before they can be recommended for clinical use.

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Section: Scientific Patents Publications and Market For Cuffless Bloo...mentioning

confidence: 99%

Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability

Stergiou

Mukkamala

Avolio

et al. 2022

Journal of Hypertension

111

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“…Appropriate BP monitoring is a prerequisite for obtaining accurate BP values and providing reliable guidance for perioperative BP management. The two most used methods for BP monitoring are intermittent oscillometric manometry with a noninvasive cuff and continuous intra-arterial invasive catheterization; however, cuffless BP measurement is an emergent popular field due to the clinical need and technology advances [ 17 , 18 ]. Intraoperative BP is measured using intermittent oscillometric manometry [ 19 ], which allows automatic, intermittent BP measurement, usually at 3–5 min intervals.…”

Section: Perioperative Bp Monitoring and Baseline Bpmentioning

confidence: 99%

Provisional Decision-Making for Perioperative Blood Pressure Management: A Narrative Review

Song

Jiang

2022

Oxidative Medicine and Cellular Longevity

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Blood pressure (BP) is a basic determinant for organ blood flow supply. Insufficient blood supply will cause tissue hypoxia, provoke cellular oxidative stress, and to some extent lead to organ injury. Perioperative BP is labile and dynamic, and intraoperative hypotension is common. It is unclear whether there is a causal relationship between intraoperative hypotension and organ injury. However, hypotension surely compromises perfusion and causes harm to some extent. Because the harm threshold remains unknown, various guidelines for intraoperative BP management have been proposed. With the pending definitions from robust randomized trials, it is reasonable to consider observational analyses suggesting that mean arterial pressures below 65 mmHg sustained for more than 15 minutes are associated with myocardial and renal injury. Advances in machine learning and artificial intelligence may facilitate the management of hemodynamics globally, including fluid administration, rather than BP alone. The previous mounting studies concentrated on associations between BP targets and adverse complications, whereas few studies were concerned about how to treat and multiple factors for decision-making. Hence, in this narrative review, we discussed the way of BP measurement and current knowledge about baseline BP extracting for surgical patients, highlighted the decision-making process for BP management with a view to providing pragmatic guidance for BP treatment in the clinical settings, and evaluated the merits of an automated blood control system in predicting hypotension.

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“…Recent development of learning-based methods has largely improved the accuracy of BP estimation based on single PPG waveform analysis. PTT-based BP estimation is being considered at a secondary place due to the significant impact of arterial stiffness, individual instability and physical condition on the predetermined hypothetical relationship ( Agham and Chaskar, 2021 ). However, due to its accuracy and reliability, PTT-based BP estimation is still the commonest solution in wearable devices compared with other approaches.…”

Section: Discussionmentioning

confidence: 99%

Filtering-induced changes of pulse transmit time across different ages: a neglected concern in photoplethysmography-based cuffless blood pressure measurement

Liao¹,

Liu²,

Lin³

et al. 2023

Front. Physiol.

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Background: Pulse transit time (PTT) is a key parameter in cuffless blood pressure measurement based on photoplethysmography (PPG) signals. In wearable PPG sensors, raw PPG signals are filtered, which can change the timing of PPG waveform feature points, leading to inaccurate PTT estimation. There is a lack of comprehensive investigation of filtering-induced PTT changes in subjects with different ages.Objective: This study aimed to quantitatively investigate the effects of aging and PTT definition on the infinite impulse response (IIR) filtering-induced PTT changes.Methods: One hundred healthy subjects in five different ranges of age (i.e., 20–29, 30–39, 40–49, 50–59, and over 60 years old, 20 subjects in each) were recruited. Electrocardiogram (ECG) and PPG signals were recorded simultaneously for 120 s. PTT was calculated from the R wave of ECG and PPG waveform features. Eight PTT definitions were developed from different PPG waveform feature points. The raw PPG signals were preprocessed then further low-pass filtered. The difference between PTTs derived from preprocessed and filtered PPG signals, and the relative difference, were calculated and compared among five age groups and eight PTT definitions using the analysis of variance (ANOVA) or Scheirer–Ray–Hare test with post hoc analysis. Linear regression analysis was used to investigate the relationship between age and filtering-induced PTT changes.Results: Filtering-induced PTT difference and the relative difference were significantly influenced by age and PTT definition (p < 0.001 for both). Aging effect on filtering-induced PTT changes was consecutive with a monotonous trend under all PTT definitions. The age groups with maximum and minimum filtering-induced PTT changes depended on the definition. In all subjects, the PTT defined by maximum peak of PPG had the minimum filtering-induced PTT changes (mean: 16.16 ms and 5.65% for PTT difference and relative difference). The changes of PTT defined by maximum first PPG derivative had the strongest linear relationship with age (R-squared: 0.47 and 0.46 for PTT difference relative difference).Conclusion: The filtering-induced PTT changes are significantly influenced by age and PTT definition. These factors deserve further consideration to improve the accuracy of PPG-based cuffless blood pressure measurement using wearable sensors.

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Learning and non-learning algorithms for cuffless blood pressure measurement: a review

Cited by 12 publications

References 105 publications

Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability

Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability

Provisional Decision-Making for Perioperative Blood Pressure Management: A Narrative Review

Filtering-induced changes of pulse transmit time across different ages: a neglected concern in photoplethysmography-based cuffless blood pressure measurement

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