Noninvasive blood pressure monitoring from the supraorbital artery using an artificial neural network oscillometric algorithm

Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic

Functional near‐infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task‐evoked and spontaneous hemodynamic oscillations of non‐cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task‐evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency‐resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi‐channel and multi‐distance recordings. We found significant task‐related fluctuations for oxy‐ and deoxy‐hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non‐cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro‐visceral link.

We proposed the use of rhythmic mental arithmetic tasks to induce cyclic oscillations in multi‐distance fNIRS signals measured on the forehead, suitable for effective frequency‐domain analysis to better identify the actual neural functional response. We confirm the impairment of deep signals by task‐evoked non‐cerebral confounds, while providing evidence for an inverse oxygenation response in the frontopolar cortex.

Artificial Intelligence Based Blood Pressure Estimation From Auscultatory and Oscillometric Waveforms: A Methodological Review

Cardiovascular disease is the number one cause of death globally, with elevated blood pressure (BP) being the single largest risk factor. Hence, BP is an important physiological parameter used as an indicator of cardiovascular health. The use of automated non-invasive blood pressure (NIBP) measurement devices is growing, as measurements can be taken by patients at home. While the oscillometric technique is most common, some automated NIBP measurement methods have been developed based on the auscultatory technique. By utilizing (relatively) large BP data annotated by experts, models can be trained using machine learning and statistical concepts to develop novel NIBP estimation algorithms. Amongst artificial intelligence (AI) techniques, deep learning has received increasing attention in different fields due to its strength in data classification and feature extraction problems. This paper reviews AI-based BP estimation methods with a focus on recent advances in deep learning-based approaches within the field. Various architectures and methodologies proposed todate are discussed to clarify their strengths and weaknesses. Based on the literature reviewed, deep learning brings plausible benefits to the field of BP estimation. We also discuss some limitations which can hinder the widespread adoption of deep learning in the field and suggest frameworks to overcome these challenges.

Bayesian fusion algorithm for improved oscillometric blood pressure estimation

A variety of oscillometric algorithms have been recently proposed in the literature for estimation of blood pressure (BP). However, these algorithms possess specific strengths and weaknesses that should be taken into account before selecting the most appropriate one. In this paper, we propose a fusion method to exploit the advantages of the oscillometric algorithms and circumvent their limitations. The proposed fusion method is based on the computation of the weighted arithmetic mean of the oscillometric algorithms estimates, and the weights are obtained using a Bayesian approach by minimizing the mean square error. The proposed approach is used to fuse four different oscillometric blood pressure estimation algorithms. The performance of the proposed method is evaluated on a pilot dataset of 150 oscillometric recordings from 10 subjects. It is found that the mean error and standard deviation of error are reduced relative to the individual estimation algorithms by up to 7 mmHg and 3 mmHg in estimation of systolic pressure, respectively, and by up to 2 mmHg and 3 mmHg in estimation of diastolic pressure, respectively.

Beat-to-beat measurement of the finger arterial pressure pulse shape index at rest and during exercise

Arterial pressure waveform can be characterized by the pulse shape index kpulse determined as kpulse = (Pmean - Pdiast) / (Psyst - Pdiast). For brachial artery, the shape index value of 0.33 is usually applied to approximate Pmean from the measured Psyst and Pdiast. Our purpose was to test whether this value can validly be applied to finger vascular beds under different experimental conditions. By using Finapres, we non-invasively estimated the beat-to-beat values of kpulse in the fingers of young healthy persons in supine position at rest and during a 4-min moderate exercise (rhythmical exercise with the quadricep muscles in combination with handgrip compression). To detect intensive peripheral vasoconstrictions, a laser-Doppler probe was attached to the thumb pulp of the same hand. Periods of 30 s without intensive vasoconstriction for rest, different stages of exercise and recovery were involved in the analysis in every subject. The results demonstrated that the group-averaged value of kpulse (median with a 95% confidence interval) in the fingers of 11 healthy volunteers aged from 20 to 24, equalled 0.33 (0.31- 0.34), 0.31 (0.28-0.34), 0.35 (0.33-0.39) and 0.38 (0.34-0.43) for rest, first and second stages of exercise and recovery, respectively. We conclude that in the fingers of young healthy persons in supine position formula Pmean = Pdiast + 1/3 (Psyst - Pdiast) gives an adequate approximation for rest and low intensity exercise (first stage), and slightly underestimates the actual finger mean blood pressure during moderate exercise (second stage) and recovery.

Oscillometric blood pressure measurement: progress and problems

Oscillometric blood pressure measurement has become very popular, but although a number of devices have now passed both the Association for the Advancement of Medical Instrumentation and British Hypertension Society criteria, complacency with the state of the technique is as yet premature. In individual subjects, a substantial number of readings may deviate more than a clinically relevant 5 mmHg in devices that have earned a British Hypertension Society grade A rating. The marketing of pressure-wave-simulating devices is a welcome development as monitors can now be tested for reproducibility; an intra-device standard deviation of less than 2 mmHg has been proposed as the limit. Authors suggest that these simulators are currently better suited to intra- than between-device testing since they are not yet fully confident that the simulated waveforms are indistinguishable from the man-made pressure waves. Simulators should, however, be incorporated into our standard validation protocols in order eventually to obviate the human, fallible, factor in the validation protocols. The currently employed maximal amplitude algorithm has many drawbacks as the parameter identification points for systolic and diastolic pressure depend on many factors, for example pulse pressure, heart rate and arterial stiffness. These errors have now been demonstrated in clinical studies. Modern pattern recognition algorithms are being constructed but have not yet produced convincing results. As repeatedly stated, the development of a more robust and more widely applicable algorithm than the maximal amplitude approach should be allocated a high priority.

Comparison of blood pressure measured by oscillometry from the supraorbital artery and invasively from the radial artery

In previous studies, oscillometric blood pressure measured from the supraorbital artery has been shown to agree quite well with pressure measured from the brachial artery in normal subjects. In this study, surgical patients whose conditions warranted the use of invasive blood pressure monitoring during the surgery were chosen. We compared systolic and diastolic blood pressure measured oscillometrically from the supraorbital artery with intraarterial blood pressures, measured invasively from the radial artery. A pressure bladder was attached to the forehead of each patient. The bladder was connected to a forehead blood pressure monitor. A catheter was inserted in a radial artery, and connected to a pressure monitor. Forehead blood pressure was measured every 5 min. Radial arterial pressure was averaged over the same period during which the forehead measurement was made. Blood pressures measured with the two methods were compared. For the systolic pressure, the difference between the two methods was -9.9 +/- 17.9 mm Hg (mean +/- SD). For diastolic pressure, the difference was -8.0 +/- 10.9 mm Hg. There was a significant difference between the two methods in the patient population chosen in this study.

Supraorbital artery as an alternative site for oscillometric blood pressure measurement

OBJECTIVE

Noninvasive blood pressure measured from the superficial temporal artery has been shown to correlate well with pressure in the brachial artery. The supraorbital artery may be an even better site for monitoring blood pressure on the forehead because it originates from the internal carotid artery, and it is easier to locate anatomically. This study compares mean pressure measured oscillometrically over the supraorbital artery and at the upper arm.

METHODS

Oscillometric signals from the supraorbital artery were recorded in 20 surgical patients under general anesthesia using a 2.5- x 1-cm bladder attached to the forehead with a self-adhesive pad. Blood pressure was measured simultaneously from the arm using a Dinamap 1846 blood pressure monitor, and the resulting data compared with the supraorbital artery measurements.

RESULTS

The mean difference between 219 pairs of blood pressure measurements, from the forehead and the arm, was 3.8 mm Hg. The standard deviation of the differences was 7.4 mm Hg. The linear regression equation for the data was y = 0.98x + 3.25, with a standard error of estimate of 7.31 mm Hg. The correlation coefficient between the two measurements was 0.82.

CONCLUSIONS

The results show that mean blood pressures measured oscillometrically from the supraorbital and brachial arteries agree and correlate well with each other. The supraorbital artery should be a good alternative site for blood pressure measurement.

Optimal sites for forehead oscillometric blood pressure monitoring

OBJECTIVE

Blood pressure is usually measured noninvasively with a cuff on the arm of the leg. Circumstances exist, however, when an alternative site for blood pressure measurement is desirable. This study is designed to identify a location on the forehead where blood pressure can be reliably measured noninvasively.

METHODS

We mapped the superficial temporal artery and/or the supraorbital artery in 65 volunteers and found a rectangular area where an adhesive pressure pad could be placed over each artery. Oscillometric signals were recorded from four different locations over the forehead in 19 of the 65 volunteers to compare the amplitude of the signal and mean blood pressure between locations.

RESULTS

The course of the supraorbital artery is quite consistent. It passed through a 2.5- x 1-cm rectangular area on the forehead in all volunteers in which it was mapped. The medial border of the rectangle is 0.5-cm medial and 1-cm above the medial corner of the left eyebrow. The course of the superficial temporal artery differed remarkably from person to person. We could not find an area of reasonable size to cover the artery in all wounds. Mean blood pressures were the same in all forehead locations. The signal was the weakest on the center of the forehead and strongest directly over the superficial temporal artery.

CONCLUSIONS

Our results show that the supraorbital artery, an end-artery of the internal carotid artery, which emerges through the supraorbital foramen and cross the forehead near the center, is the preferred site to monitor blood pressure noninvasively on the forehead with an adhesive pressure bladder.