Robust Arm Impedocardiography Signal Quality Enhancement Using Recursive Signal Averaging and Multi-Stage Wavelet Denoising Methods for Long-Term Cardiac Contractility Monitoring Armbands.

Impedance cardiography (ICG) is a low-cost, non-invasive technique that enables the clinical assessment of haemodynamic parameters, such as cardiac output and stroke volume (SV). Conventional ICG recordings are taken from the patient's thorax. However, access to ICG vital signs from the upper-arm brachial artery (as an associated surrogate) can enable user-convenient wearable armband sensor devices to provide an attractive option for gathering ICG trend-based indicators of general health, which offers particular advantages in ambulatory long-term monitoring settings. This study considered the upper arm ICG and control Thorax-ICG recordings data from 15 healthy subject cases. A prefiltering stage included a third-order Savitzky-Golay finite impulse response (FIR) filter, which was applied to the raw ICG signals. Then, a multi-stage wavelet-based denoising strategy on a beat-by-beat (BbyB) basis, which was supported by a recursive signal-averaging optimal thresholding adaptation algorithm for Arm-ICG signals, was investigated for robust signal quality enhancement. The performance of the BbyB ICG denoising was evaluated for each case using a 700 ms frame centred on the heartbeat ICG pulse. This frame was extracted from a 600-beat ensemble signal-averaged ICG and was used as the noiseless signal reference vector (gold standard frame). Furthermore, in each subject case, enhanced Arm-ICG and Thorax-ICG above a threshold of correlation of 0.95 with the noiseless vector enabled the analysis of beat inclusion rate (BIR%), yielding an average of 80.9% for Arm-ICG and 100% for Thorax-ICG, and BbyB values of the ICG waveform feature metrics A, B, C and VET accuracy and precision, yielding respective error rates (ER%) of 0.83%, 11.1%, 3.99% and 5.2% for Arm-IG, and 0.41%, 3.82%, 1.66% and 1.25% for Thorax-ICG, respectively. Hence, the functional relationship between ICG metrics within and between the arm and thorax recording modes could be characterised and the linear regression (Arm-ICG vs. Thorax-ICG) trends could be analysed. Overall, it was found in this study that recursive averaging, set with a 36 ICG beats buffer size, was the best Arm-ICG BbyB denoising process, with an average of less than 3.3% in the Arm-ICG time metrics error rate. It was also found that the arm SV versus thorax SV had a linear regression coefficient of determination (R2) of 0.84.

Armband Sensors Location Assessment for Left Arm-ECG Bipolar Leads Waveform Components Discovery Tendencies around the MUAC Line.

Sudden cardiac death (SCD) risk can be reduced by early detection of short-lived and transient cardiac arrhythmias using long-term electrocardiographic (ECG) monitoring. Early detection of ventricular arrhythmias can reduce the risk of SCD by allowing appropriate interventions. Long-term continuous ECG monitoring, using a non-invasive armband-based wearable device is an appealing solution for detecting early heart rhythm abnormalities. However, there is a paucity of understanding on the number and best bipolar ECG electrode pairs axial orientation around the left mid-upper arm circumference (MUAC) for such devices. This study addresses the question on the best axial orientation of ECG bipolar electrode pairs around the left MUAC in non-invasive armband-based wearable devices, for the early detection of heart rhythm abnormalities. A total of 18 subjects with almost same BMI values in the WASTCArD arm-ECG database were selected to assess arm-ECG bipolar leads quality using proposed metrics of relative (normalized) signal strength measurement, arm-ECG detection performance of the main ECG waveform event component (QRS) and heart-rate variability (HRV) in six derived bipolar arm ECG-lead sensor pairs around the armband circumference, having regularly spaced axis angles (at 30° steps) orientation. The analysis revealed that the angular range from -30° to +30°of arm-lead sensors pair axis orientation around the arm, including the 0° axis (which is co-planar to chest plane), provided the best orientation on the arm for reasonably good QRS detection; presenting the highest sensitivity (Se) median value of 93.3%, precision PPV median value at 99.6%; HRV RMS correlation (p) of 0.97 and coefficient of determination (R2) of 0.95 with HRV gold standard values measured in the standard Lead-I ECG.

Transcutaneous Pulsed RF Energy Transfer Mitigates Tissue Heating in High Power Demand Implanted Device Applications: In Vivo and In Silico Models Results.

This article presents the development of a power loss emulation (PLE) system device to study and find ways of mitigating skin tissue heating effects in transcutaneous energy transmission systems (TETS) for existing and next generation left ventricular assist devices (LVADs). Skin thermal profile measurements were made using the PLE system prototype and also separately with a TETS in a porcine model. Subsequent data analysis and separate computer modelling studies permit understanding of the contribution of tissue blood perfusion towards cooling of the subcutaneous tissue around the electromagnetic coupling area. A 2-channel PLE system prototype and a 2-channel TETS prototype were implemented for this study. The heating effects resulting from power transmission inefficiency were investigated under varying conditions of power delivery levels for an implanted device. In the part of the study using the PLE setup, the implanted heating element was placed subcutaneously 6-8 mm below the body surface of in vivo porcine model skin. Two operating modes of transmission coupling power losses were emulated: (a) conventional continuous transmission, and (b) using our proposed pulsed transmission waveform protocols. Experimental skin tissue thermal profiles were studied for various levels of LVAD power. The heating coefficient was estimated from the porcine model measurements (an in vivo living model and a euthanised cadaver model without blood circulation at the end of the experiment). An in silico model to support data interpretation provided reliable experimental and numerical methods for effective wireless transdermal LVAD energization advanced solutions. In the separate second part of the study conducted with a separate set of pigs, a two-channel inductively coupled RF driving system implemented wireless power transfer (WPT) to a resistive LVAD model (50 Ω) to explore continuous versus pulsed RF transmission modes. The RF-transmission pulse duration ranged from 30 ms to 480 ms, and the idle time (no-transmission) from 5 s to 120 s. The results revealed that blood perfusion plays an important cooling role in reducing thermal tissue damage from TETS applications. In addition, the results analysis of the in vivo, cadaver (R1Sp2) model, and in silico studies confirmed that the tissue heating effect was significantly lower in the living model versus the cadaver model due to the presence of blood perfusion cooling effects.

Towards Low Energy Atrial Defibrillation.

A wireless powered implantable atrial defibrillator consisting of a battery driven hand-held radio frequency (RF) power transmitter (ex vivo) and a passive (battery free) implantable power receiver (in vivo) that enables measurement of the intracardiac impedance (ICI) during internal atrial defibrillation is reported. The architecture is designed to operate in two modes: Cardiac sense mode (power-up, measure the impedance of the cardiac substrate and communicate data to the ex vivo power transmitter) and cardiac shock mode (delivery of a synchronised very low tilt rectilinear electrical shock waveform). An initial prototype was implemented and tested. In low-power (sense) mode, >5 W was delivered across a 2.5 cm air-skin gap to facilitate measurement of the impedance of the cardiac substrate. In high-power (shock) mode, >180 W (delivered as a 12 ms monophasic very-low-tilt-rectilinear (M-VLTR) or as a 12 ms biphasic very-low-tilt-rectilinear (B-VLTR) chronosymmetric (6ms/6ms) amplitude asymmetric (negative phase at 50% magnitude) shock was reliably and repeatedly delivered across the same interface; with >47% DC-to-DC (direct current to direct current) power transfer efficiency at a switching frequency of 185 kHz achieved. In an initial trial of the RF architecture developed, 30 patients with AF were randomised to therapy with an RF generated M-VLTR or B-VLTR shock using a step-up voltage protocol (50-300 V). Mean energy for successful cardioversion was 8.51 J ± 3.16 J. Subsequent analysis revealed that all patients who cardioverted exhibited a significant decrease in ICI between the first and third shocks (5.00 Ω (SD(σ) = 1.62 Ω), p < 0.01) while spectral analysis across frequency also revealed a significant variation in the impedance-amplitude-spectrum-area (IAMSA) within the same patient group (|∆(IAMSAS1-IAMSAS3)[1 Hz - 20 kHz] = 20.82 Ω-Hz (SD(σ) = 10.77 Ω-Hz), p < 0.01); both trends being absent in all patients that failed to cardiovert. Efficient transcutaneous power transfer and sensing of ICI during cardioversion are evidenced as key to the advancement of low-energy atrial defibrillation.

Waveform optimization for internal cardioversion of atrial fibrillation.

INTRODUCTION: A novel atrial defibrillator was developed at the Royal Victoria Hospital in collaboration with the Nanotechnology and Integrated Bio-Engineering Centre, University of Ulster. This device is powered by an external pulse of radiofrequency energy and designed to cardiovert using low-tilt monophasic waveform (LTMW) and low-tilt biphasic waveform (LTBW), 12 milliseconds pulse width. This study compared the safety and efficacy of LTMW with LTBW for transvenous cardioversion of atrial fibrillation (AF). METHODS: Patients were anticoagulated with warfarin to maintain International Normalized Ratio between 2 and 3 for 4 weeks prior cardioversion. Warfarin international normalized ratio level was maintained in between 2 and 3 for 4 weeks prior cardioversion. St Jude's defibrillating catheter was positioned in the distal coronary sinus and right atrium and connected to the defibrillator via a junction box. After a test shock using a dummy load, the patient was cardioverted in a step-up progression from 50 to 300 V. Shock success was defined as return of sinus rhythm for 30 seconds or more. If cardioversion was unsuccessful at peak voltage, the patient was crossed over to the other arm of the waveform type and cardioverted at peak voltage. RESULTS: Thirty patients were randomized equally to LTBW and LTMW (15 each). Seven out of 15 patients (46%) cardioverted to sinus rhythm with LTBW, and 1 (6%) of 15, with LTMW (P = .035). Including crossover patients, 14 patients (46%) converted to sinus rhythm. After crossover, 4 patients were cardioverted with LTBW and 2 with LTMW. Overall mean voltage, current, and energy used for cardioversion were 270.53 ± 35.96 V, 3.68 ± 0.80 A, and 9.12 ± 3.73 J, respectively, and intracardiac impedance was 70.82 ± 13.46 Ω. For patients who were successfully cardioverted, mean voltage, current, energy, and intracardiac impedance were 268.28 ± 42.41 V, 3.52 ± 0.63 A, 8.51 ± 3.16 J, and 73.92 ± 12.01 Ω. There were no major adverse complications during the study. Cardiac markers measured postcardioversion were unremarkable. CONCLUSION: Low-tilt biphasic waveform was more efficacious for low-energy transvenous cardioversion of AF. A significant proportion of patients were successfully cardioverted to sinus rhythm with low energy. Radiofrequency-powered defibrillation can be safely used for transvenous cardioversion of AF.

A pilot study of a low-tilt biphasic waveform for transvenous cardioversion of atrial fibrillation: improved efficacy compared with conventional capacitor-based waveforms in patients.

BACKGROUND: The optimal waveform tilt for defibrillation is not known. Most modern defibrillators used for the cardioversion of atrial fibrillation (AF) employ high-tilt, capacitor-based biphasic waveforms. METHODS: We have developed a low-tilt biphasic waveform for defibrillation. This low-tilt waveform was compared with a conventional waveform of equivalent duration and voltage in patients with AF. Patients with persistent AF or AF induced during a routine electrophysiology study (EPS) were randomized to receive either the low-tilt waveform or a conventional waveform. Defibrillation electrodes were positioned in the right atrial appendage and distal coronary sinus. Phase 1 peak voltage was increased in a stepwise progression from 50 V to 300V. Shock success was defined as return of sinus rhythm for >/=30 seconds. RESULTS: The low-tilt waveform produced successful termination of persistent AF at a mean voltage of 223 V (8.2 J) versus 270 V (6.7 J) with the conventional waveform (P = 0.002 for voltage, P = ns for energy). In patients with induced AF the mean voltage for the low-tilt waveform was 91V (1.6 J) and for the conventional waveform was 158 V (2.0 J) (P = 0.005 for voltage, P = ns for energy). The waveform was much more successful at very low voltages (less than or equal to 100 V) compared with the conventional waveform (Novel: 82% vs Conventional 22%, P = 0.008). CONCLUSION: The low-tilt biphasic waveform was more successful for the internal cardioversion of both persistent and induced AF in patients (in terms of leading edge voltage).

Performance assessment of dry electrodes for wearable long term cardiac rhythm monitoring: Skin-electrode impedance spectroscopy.

The use of wearable dry sensors for recording long term ECG signals is a requirement for certain studies of heart rhythm. Knowledge of the skin-electrode electrical performance of dry electrodes is necessary when seeking to improve various processing stages for signal quality enhancement. In this paper, methods for the assessment of dry skin-electrode impedance (ZSE) and its modelling are presented. Measurements were carried out on selected electrode materials such as silver, stainless steel, AgCl (dry) and polyurethane. These had ZSE values between 500 kΩ and 1 MΩ within the main ECG frequency range (1 Hz - 100 Hz); in contrast to plain iron material which had a significantly higher impedance. However, in spite of the high ZSE values, open bandwidth ECG traces were of acceptable quality and stability; with dry AgCl material offering the best ECG trace performance.

Improved detection of acute myocardial infarction using a diagnostic algorithm based on calculated epicardial potentials.

BACKGROUND: New methods for detecting myocardial infarction in patients with suspected acute coronary syndromes are needed particularly in an era where the majority of patients with myocardial infarction present with non-diagnostic 12-lead electrocardiograms (ECG). We compared a novel epicardial diagnostic algorithm using epicardial potentials from the 80-lead body surface map with other electrocardiographic techniques in detection of myocardial infarction. METHODS: Between February 1999 and February 2001, consecutive patients (n=427) with ischemic type chest pain had an initial 12-lead ECG and body surface map recorded. Detecting myocardial infarction using an epicardial algorithm was first performed in a training set (n=213) and tested in a validation set of patients (n=214). The results from this epicardial algorithm in myocardial infarction detection were compared with the physician's interpretation of the 12-lead ECG, the body surface map algorithm (PRIME) and physician's interpretation of the body surface map. RESULTS: Myocardial infarction occurred in 205 patients (creatine kinase >or=2x upper limit of normal with creatine kinase-MB >or=7% CK). The physician's interpretation of the 12-lead ECG identified 122 with myocardial infarction (sensitivity 60%, specificity 99%), the body surface map algorithm 137 (sensitivity 67%, specificity 89%), the physician's interpretation of the body surface map 153 (sensitivity 75%, specificity 91%) and the epicardial algorithm 158 (sensitivity 77% specificity 99%). Combining the physician's interpretation of the 12-lead ECG with the epicardial algorithm increased significantly the detection of myocardial infarction (sensitivity 85%, specificity 98%, p<0.001) compared with the 12-lead ECG. CONCLUSIONS: An epicardial algorithm based on epicardial potentials increases significantly the detection of myocardial infarction particularly among those with non-diagnostic 12-lead ECG's.

A support vector machine for predicting defibrillation outcomes from waveform metrics.

BACKGROUND: Algorithms to predict shock success based on VF waveform metrics could significantly enhance resuscitation by optimising the timing of defibrillation. OBJECTIVE: To investigate robust methods of predicting defibrillation success in VF cardiac arrest patients, by using a support vector machine (SVM) optimisation approach. METHODS: Frequency-domain (AMSA, dominant frequency and median frequency) and time-domain (slope and RMS amplitude) VF waveform metrics were calculated in a 4.1Y window prior to defibrillation. Conventional prediction test validity of each waveform parameter was conducted and used AUC>0.6 as the criterion for inclusion as a corroborative attribute processed by the SVM classification model. The latter used a Gaussian radial-basis-function (RBF) kernel and the error penalty factor C was fixed to 1. A two-fold cross-validation resampling technique was employed. RESULTS: A total of 41 patients had 115 defibrillation instances. AMSA, slope and RMS waveform metrics performed test validation with AUC>0.6 for predicting termination of VF and return-to-organised rhythm. Predictive accuracy of the optimised SVM design for termination of VF was 81.9% (± 1.24 SD); positive and negative predictivity were respectively 84.3% (± 1.98 SD) and 77.4% (± 1.24 SD); sensitivity and specificity were 87.6% (± 2.69 SD) and 71.6% (± 9.38 SD) respectively. CONCLUSIONS: AMSA, slope and RMS were the best VF waveform frequency-time parameters predictors of termination of VF according to test validity assessment. This a priori can be used for a simplified SVM optimised design that combines the predictive attributes of these VF waveform metrics for improved prediction accuracy and generalisation performance without requiring the definition of any threshold value on waveform metrics.

Detection of cardiac arrest using a simplified frequency analysis of the impedance cardiogram recorded from defibrillator pads.

An algorithm based only on the impedance cardiogram (ICG) recorded through two defibrillation pads, using the strongest frequency component and amplitude, incorporated into a defibrillator could determine circulatory arrest and reduce delays in starting cardiopulmonary resuscitation (CPR). Frequency analysis of the ICG signal is carried out by integer filters on a sample by sample basis. They are simpler, lighter and more versatile when compared to the FFT. This alternative approach, although less accurate, is preferred due to the limited processing capacity of devices that could compromise real time usability of the FFT. These two techniques were compared across a data set comprising 13 cases of cardiac arrest and 6 normal controls. The best filters were refined on this training set and an algorithm for the detection of cardiac arrest was trained on a wider data set. The algorithm was finally tested on a validation set. The ICG was recorded in 132 cardiac arrest patients (53 training, 79 validation) and 97 controls (47 training, 50 validation): the diagnostic algorithm indicated cardiac arrest with a sensitivity of 81.1% (77.6-84.3) and specificity of 97.1% (96.7-97.4) for the validation set (95% confidence intervals). Automated defibrillators with integrated ICG analysis have the potential to improve emergency care by lay persons enabling more rapid and appropriate initiation of CPR and when combined with ECG analysis they could improve on the detection of cardiac arrest.

Novel rectangular biphasic and monophasic waveforms delivered by a radiofrequency-powered defibrillator compared with conventional capacitor-based waveforms in transvenous cardioversion of atrial fibrillation.

AIMS: To investigate the feasibility and efficacy of novel low-tilt biphasic waveforms in transvenous cardioversion of atrial fibrillation (AF), delivered by a radiofrequency-powered defibrillator. METHODS AND RESULTS: The investigation was performed in three phases in an animal model of AF: a feasibility and efficacy study (in 10 adult Large White Landrace swine), comparison with low-tilt monophasic and standard capacitor-based waveforms, and an assessment of sequential shocks delivered over several pathways (in 15 adult Suffolk sheep). Defibrillation electrodes were positioned transvenously under fluoroscopic control in the high lateral right atrium and distal coronary sinus. When multiple defibrillation pathways were tested, a third electrode was also attached to the lower interatrial septum. The electrodes were then connected to a radiofrequency (RF)-powered defibrillator or a standard defibrillator. After confirmation of successful induction of sustained AF, defibrillation was attempted. Percentage success was calculated from the effects of all shocks delivered to all the animals within each set of experiments. Of the low-tilt (RF) biphasic waveforms delivered during internal atrial cardioversion, 100% success was achieved with a 6/6 ms 100/-50 V waveform (1.45+/-0.01 J). This waveform was similar in efficacy to low-tilt (RF) monophasic waveforms (88 vs. 92% success, 1.58+/-0.01 vs. 2.67+/-0.03 J; P=NS; delivered energy 41% lower) and superior to equivalent voltage standard monophasic (50% success, 0.67+/-0.00 J; P<0.001) and biphasic waveforms (72% success, 0.69+/-0.00 J; P=0.03). Sequential shocks delivered over dual pathways did not improve the efficacy of low-tilt biphasic waveforms. CONCLUSION: A low-tilt biphasic waveform from a RF-powered defibrillator (6/6 ms 100/-50 V) is more efficacious than standard monophasic or biphasic waveforms (equivalent voltage) and is similar in efficacy to low-tilt monophasic waveforms.

The use of calculated epicardial potentials improves significantly the sensitivity of a diagnostic algorithm in the detection of acute myocardial infarction.

Inverse electrocardiography can calculate epicardial potentials (EP) from body surface potentials (BSP) taking into account a thoracic volume conductor model (TVCM). Previous studies have shown that a tailored TVCM is superior to a general TVCM in calculating EP. However, construction of a tailored TVCM for a patient in an acute clinical setting is impractical. In this study we used a general TVCM in our EP calculations to determine whether this improves detection of acute myocardial infarction (AMI) using a diagnostic algorithm. BSP were derived from the 80-lead body surface map (BSM). Consecutive patients (n=379) with ischemic type chest pain were recruited. The BSM and a 12-lead electrocardiogram (ECG) were recorded at initial presentation and creatine kinase (CK) and/or CK-MB were measured initially, 12 and 24 hours postsymptom onset. A physician interpreted the 12-lead electrocardiogram and documented ST elevation if present. AMI was defined by the World Health Organization (WHO) criteria. The diagnostic algorithm result for each patient using BSP and calculated EP were documented. AMI occurred in 171 patients. The diagnostic algorithm using BSP identified 106 of these as ST elevation AMI (STEMI) (sensitivity 62%, specificity 80%). The same algorithm using EP identified 133 as STEMI (sensitivity 78%, specificity 80%). Calculated EP improved the algorithm's diagnostic sensitivity by a factor of 1.25 (P<.001) with no significant difference in specificity. Calculated EP using a general TVCM significantly improves the sensitivity of a diagnostic algorithm based on BSP in detection of AMI with no significant loss in specificity.