Extracting a cardiac signal from the extracorporeal pressure sensors of a hemodialysis machine

Reproduction of human blood pressure waveform using physiology-based cardiovascular simulator

This study presents a cardiovascular simulator that mimics the human cardiovascular system's physiological structure and properties to reproduce the human blood pressure waveform. Systolic, diastolic blood pressures, and its waveform are key indicators of cardiovascular health. The blood pressure waveform is closely related to the pulse wave velocity and the overlap of the forward and reflected pressure waves. The presented cardiovascular simulator includes an artificial aorta made of biomimetic silicone. The artificial aorta has the same shape and stiffness as the human standard and is encased with a compliance chamber. The compliance chamber prevents distortion of the blood pressure waveform from strain-softening by applying extravascular pressure. The blood pressure waveform reproduced by the simulator has a pressure range of 80-120 mmHg, a pulse wave velocity of 6.58 m/s, and an augmentation index of 13.3%. These values are in the middle of the human standard range, and the reproduced blood pressure waveform is similar to that of humans. The errors from the human standard values are less than 1 mmHg for blood pressure, 0.05 m/s for pulse wave velocity, and 3% for augmentation index. The changes in blood pressure waveform according to cardiovascular parameters, including heart rate, stroke volume, and peripheral resistance, were evaluated. The same pressure ranges and trends as in humans were observed for systolic and diastolic blood pressures according to cardiovascular parameters.

Noninvasive continuous intradialytic blood pressure monitoring: the key to improving haemodynamic stability

PURPOSE OF REVIEW

Intradialytic hypotension (IDH) occurs in 20% of haemodialysis treatments, leading to end-organ ischaemia, increased morbidity and mortality; and contributing to poor quality of life for patients. Treatment of IDH is reactive since brachial blood pressure (BP) is recorded only intermittently during haemodialysis, making early detection and prediction of hypotension impossible. Noninvasive continuous BP monitoring would allow earlier detection of IDH and thus support the development of methods for its prediction and consequently prevention.

RECENT FINDINGS

Noninvasive continuous BP monitoring is not yet part of routine practice in renal dialysis units, with a small number of devices (e.g. finger cuffs) having occasionally been used in research settings. In use, patients frequently report pain or discomfort at measurement sites. Additionally, these devices can be unreliable in patients with reduced blood flow to the digits, often manifest in dialysis patients. All existing methods are sensitive to patient movement.A new method for continuously estimating BP has been developed by monitoring arterial pressure near the arteriovenous fistula which can be achieved without any extraneous monitoring equipment attached to the patient. Additionally, artificial intelligence-based methods for real-time prediction of IDH are currently emerging.

SUMMARY

Key monitoring technologies and computational methods are emerging to support the development of real-time IDH prediction.

A Feasibility Study of Non-Invasive Continuous Estimation of Brachial Pressure Derived From Arterial and Venous Lines During Dialysis

Objective: Intradialytic haemodynamic instability is a significant clinical problem, leading to end-organ ischaemia and contributing to morbidity and mortality in haemodialysis patients. Non-invasive continuous blood pressure monitoring is not currently part of routine practice but may aid detection and prevention of significant falls in blood pressure during dialysis. Brachial blood pressure is currently recorded intermittently during haemodialysis via a sphygmomanometer. Current methods of continuous non-invasive blood pressure monitoring tend to restrict movement, can be sensitive to external disturbances and patient movement, and can be uncomfortable for the wearer. Additionally, poor patient blood circulation can lead to unreliable measurements. In this feasibility study we performed an initial validation of a novel method and associated technology to continuously estimate blood pressure using pressure sensors in the extra-corporeal dialysis circuit, which does not require any direct contact with the person receiving dialysis treatment. Method: The paper describes the development of the measurement system and subsequent in vivo patient feasibility study with concurrent measurement validation by Finapres Nova physiological measurement device. Real-time physiological data is collected over the entire period of (typically 4-hour) dialysis treatment. Results: We identify a quasi-linear mathematical function to describe the relationship between arterial line pressure and brachial artery BP, which is confirmed in a patient study. The results from this observational study suggest that it is feasible to derive a continuous measurement of brachial pressure from continuous measurements of arterial and venous line pressures via an empirically based and updated mathematical model. Conclusion: The methodology presented requires no interfacing to proprietary dialysis machine systems, no sensors to be attached to the patient directly, and is robust to patient movement during treatment and also to the effects of the cyclical pressure waveforms induced by the hemodialysis peristaltic blood pump. This represents a key enabling factor to the development of a practical continuous blood pressure monitoring device for dialysis patients.

Pitfall of heart rate variability analyses for autonomic nervous system activity with photoplethysmography

The purpose of this study is to measure the temporary intervals between R peak with ECG and pulse peak with photoplethysmography (PPG) and then to compare their precisions of two types of heart rate variability (HRV) analyses, power spectral analysis and Tone-Entropy analysis. A lot of papers used to measure cardiac autonomic nervous system (CANS) activity with HRV from PPI without awareness of the issue on another variability except CANS activity. Fifteen young male subjects were participated in this study. Simultaneous PPG and ECG were recorded with a portable device in three different postures; supine, sitting and upright positions. Our results show that, although there are no significant differences on heart rate between R-R interval (RRI) and pulse peak interval (PPI), analytic outputs on HRV analyses between RRI and PPI are different; especially, in upright position, there are significant differences on LF and HF (p<; 0.05) and also Tone-Entropy plots are clearly distant between RRI and PPI. In conclusion, our results indicate that PPG should not be used for measurement of CANS activity from HRV because of analytic error depending on physiological states like posture change though PPG probably has little problem to be used as a heart rate monitor.

Increase of Input Resistance of a Normal-Mode Helical Antenna (NMHA) in Human Body Application

In recent years, the development of healthcare monitoring devices requires high performance and compact in-body sensor antennas. A normal-mode helical antenna (NMHA) is one of the most suitable candidates that meets the criteria, especially with the ability to achieve high efficiency when the antenna structure is in self-resonant mode. It was reported that when the antenna was placed in a human body, the antenna efficiency was decreased due to the increase of its input resistance (Rin). However, the reason for Rin increase was not clarified. In this paper, the increase of Rin is ensured through experiments and the physical reasons are validated through electromagnetic simulations. In the simulation, the Rin is calculated by placing the NMHA inside a human's stomach, skin and fat. The dependency of Rin to conductivity (σ) is significant. Through current distribution calculation, it is verified that the reason of the increase in Rin is due to the decrease of antenna current. The effects of Rin to bandwidth (BW) and electrical field are also numerically clarified. Furthermore, by using the fabricated human body phantom, the measured Rin and bandwidth are also obtained. From the good agreement between the measured and simulated results, the condition of Rin increment is clarified.

Detection of Needle Dislodgement Using Extracorporeal Pressure Signals: A Feasibility Study

Venous needle dislodgement (VND) during dialysis is a rarely occurring adverse event, which becomes life-threatening if not handled promptly. Because the standard venous pressure alarm, implemented in most dialysis machines, has low sensitivity, a novel approach using extracted cardiac information to detect needle dislodgement is proposed. Four features are extracted from the arterial and venous pressure signals of the dialysis machine, characterizing the mean venous pressure, the venous cardiac pulse pressure, the time delay, and the correlation between the two pressure signals. The features serve as input to a support vector machine (SVM), which determines whether dislodgement has occurred. The SVM is first trained on a set of laboratory data, and then tested on another set of laboratory data as well as on a small data set from clinical hemodialysis sessions. The results show that dislodgement can be detected after 12-17 s, corresponding to 24-143 ml blood loss. The standard venous pressure alarm used in clinical routine only detects 50% of the VNDs, whereas the novel method detects all VNDs and has a false alarm rate of 0.12 per hour, provided that the amplitude of the extracted cardiac pressure signal exceeds 1 mmHg. The results are promising; however, the method needs to be tested on a larger set of clinical data to better establish its performance.

A New Method for Continuous Relative Blood Volume and Plasma Sodium Concentration Estimation During Hemodialysis

OBJECTIVE

Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this paper, we present a new method for joint estimation of two important hemodialysis-related physiological parameters-relative blood volume and plasma sodium concentration.

METHODS

Our method makes use of a non-invasive sensor setup and a mathematical estimator. The estimator, based on the Kalman filter, allows merging data from multiple sensors, newly designed as well as onboard, with modeling knowledge about the hemodialysis process. The system was validated on in vitro hemodialysis sessions using bovine blood.

RESULTS

The estimation error we obtained (0.97 ± 0.73% on relative blood volume and 0.47 ± 0.19 mM on plasmatic sodium) proved to be comparable with that of the reference data for both parameters-the system is sufficiently accurate to be relevant in a clinical context.

CONCLUSION

Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing onboard sensors are required.

SIGNIFICANCE

Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis.

Substitution-rate based screening model to assess stenosis progression in experimental stenotic arteriovenous grafts

An arteriovenous graft (AVG) has a higher patency rate in stenosis progression at the venous anastomosis site, which causes coexisting inflow and outflow stenoses. This leads to increases in blood pressure, flow velocity, and flow resistance, resulting in hemodialysis (HD) vascular access dysfunction from early clots and thrombosis to the progression of coexisting stenoses. To prevent vascular access complications such as inflow or outflow stenoses, this study proposes a novel examination method in an experimental AVG system using a substitution-rate based screening model. In our practical measurements, we found that inflow and outflow channeled through a narrowed access indicated both pressure and resistance differences as the degree of stenosis (DOS) gradually increased. A substitution-rate matrix was conducted to replace bilateral pressure variations, while a transition probability matrix was calculated. Differences in transition probabilities were then used to distinguish between normal conditions and flow instabilities using the distance estimation method. The joint probability decayed from < 0.81 to 0.00 could be specified to identify the progression in stenosis levels from a DOS% = 50.0-95.0%. Average joint probabilities were found to be inversely related with the DOS using a non-linear regression (R>2 0.90). Hence, the joint probability could be specified as a critical threshold, < 0.81, to identify the severity stenosis level, DOS% ⩾ 70%, in the assessment of coexisting inflow and outflow stenoses. Experimental results suggest that the proposed model is superior to hemodynamic analysis and traditional intelligent method, and can be used for dysfunction screening during HD treatment.

Optical and Electrical Characterization of Biocompatible Polymeric Lines for Hemodialysis Applications

During hemodialysis (HD), blood is circulated through an extracorporeal tubing system (bloodline) made of medical-grade polymeric material. Sensors of various types that do not come into contact with blood (optical, electromagnetic, etc.) are applied directly across the bloodline for clinical purposes and for therapy customization. Thus, a detailed knowledge of the bloodline’s physical properties is useful for the development of next-generation HD sensors. In this work, we performed a novel comparative analysis of the materials used by the manufacturers of the bloodlines. We focused on signals and characterization techniques matching those of the abovementioned sensors; consequently, this is an application-specific study of the optical and electrical characterization of bloodline material. Such properties are analyzed and compared for bloodlines from seven different manufacturers by optical absorbance spectroscopy and electrical impedance spectroscopy (EIS). Absorbance spectrum measurements are carried out in the VIS-NIR range. Absorbance spectra are pre-processed and data from both types of analyses are normalized with respect to sample thickness. Optical analysis shows that all bloodlines except one have similarly shaped spectra with slight quantitative differences. In all optical spectra, we find a decreasing trend of specific absorption from 0.14 mm⁻¹ at 400 nm to 0.06 mm⁻¹ at 1000 nm, with an absorption peak at 915 nm. In one case, a large absorption peak centered at ≃600 nm is found. Electrical analysis shows that all bloodlines have the electrical properties of a constant-phase element (CPE), with statistically significant differences in parameters’ values. Estimation of electrical CPE parameters for all bloodline returns a range of 0.942–0.957 for parameter n and a range of 12.41–16.64 for parameter Q₀’. In conclusion, we find that, although some statistically significant differences are present, bloodlines from a representative group of manufacturers share similar electrical and optical properties. Therefore, contactless sensing devices developed for HD will work on different bloodlines if a simple recalibration is performed.

Detection of ventricular premature beats based on the pressure signals of a hemodialysis machine

Monitoring of ventricular premature beats (VPBs), being abundant in hemodialysis patients, can provide information on cardiovascular instability and electrolyte imbalance. In this paper, we describe a method for VPB detection which explores the signals acquired from the arterial and the venous pressure sensors, located in the extracorporeal blood circuit of a hemodialysis machine. The pressure signals are mainly composed of a pump component and a cardiac component. The cardiac component, severely overshadowed by the pump component, is estimated from the pressure signals using an earlier described iterative method. A set of simple features is extracted, and linear discriminant analysis is performed to classify beats as either normal or ventricular premature. Performance is evaluated on signals from nine hemodialysis treatments, using leave-one-out crossvalidation. The simultaneously recorded and annotated photoplethysmographic signal serves as the reference signal, with a total of 149,686 normal beats and 3574 VPBs. The results show that VPBs can be reliably detected, quantified by a Youden's J statistic of 0.9, for average cardiac pulse pressures exceeding 1 mmHg; for lower pressures, the J statistic drops to 0.55. It is concluded that the cardiac pressure signal is suitable for VPB detection, provided that the average cardiac pulse pressure exceeds 1 mmHg.

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.

Assistive technology using integrated flexible sensor and virtual alarm unit for blood leakage detection during dialysis therapy

Blood leakages and blood loss are both serious complications during dialysis therapies. According to dialysis survey reports, these events are life-threatening issues for nephrology nurses, medical staff, and patients. When venous needle dislodgement occurs, it takes only <2.5 min of reaction time for blood loss in an adult patient, resulting in mortality. As an early-warning design, a wireless assistive technology using an integrated flexible sensor and virtual alarm unit was developed to detect blood leakage during dialysis therapies. The flexible sensor was designed using a screen print technique with printing electronic circuits on a plastic substrate. A self-organising algorithm was used to design a virtual alarm unit, consisting of a virtual direct current grid and a virtual alarm driver. In other words, this warning device was employed to identify the blood leakage levels via wireless fidelity wireless network in cloud computing. The feasibility was verified, and commercialisation designs can also be implemented in an embedded system.

Cardiac signal estimation based on the arterial and venous pressure signals of a hemodialysis machine

Continuous cardiac monitoring is usually not performed during hemodialysis treatment, although a majority of patients with kidney failure suffer from cardiovascular disease. In the present paper, a method is proposed for estimating a cardiac pressure signal by combining the arterial and the venous pressure sensor signals of the hemodialysis machine. The estimation is complicated by the periodic pressure disturbance caused by the peristaltic blood pump, with an amplitude much larger than that of the cardiac pressure signal. Using different techniques for combining the arterial and venous pressure signals, the performance is evaluated and compared to that of an earlier method which made use of the venous pressure only. The heart rate and the heartbeat occurrence times, determined from the estimated cardiac pressure signal, are compared to the corresponding quantities determined from a photoplethysmographic reference signal. Signals from 9 complete hemodialysis treatments were analyzed. For a heartbeat amplitude of 0.5 mmHg, the median absolute deviation between estimated and reference heart rate was 1.3 bpm when using the venous pressure signal only, but dropped to 0.6 bpm when combining the pressure signals. The results show that the proposed method offers superior estimation at low heartbeat amplitudes. Consequently, more patients can be successfully monitored during treatment without the need of extra sensors. The results are preliminary, and need to be verified on a separate dataset.

Detection of venous needle dislodgement during haemodialysis using fractional order shape index ratio and fuzzy colour relation analysis

Venous needle dislodgement (VND) is a life-threatening complication during haemodialysis (HD) treatment. When VND occurs, it only takes a few minutes for blood loss in an adult patient. According to the ANNA (American Nephrology Nurses' Association) VND survey reports, VND is a concerning issue for the nephrology nurses/staff and patients. To ensure HD care and an effective treatment environment, this Letter proposes a combination of fractional order shape index ratio (SIR) and fuzzy colour relation analysis (CRA) to detect VND. If the venous needle drops out, clinical examinations show that both heart pulses and pressure wave variations have a low correlation at the venous anatomic site. Therefore, fractional order SIR is used to quantify the differences in transverse vibration pressures (TVPs) between the normal condition and meter reading. Linear regression shows that the fractional order SIR has a high correlation with the TVP variation. Fuzzy CRA is designed in a simple and visual message manner to identify the risk levels. A worst-case study demonstrated that the proposed model can be used for VND detection in clinical applications.