Omer T. Inan

Robust Neural-Network-Based Classification of Premature Ventricular Contractions Using Wavelet Transform and Timing Interval Features

Automatic electrocardiogram (ECG) beat classification is essential to timely diagnosis of dangerous heart conditions. Specifically, accurate detection of premature ventricular contractions (PVCs) is imperative to prepare for the possible onset of life-threatening arrhythmias. Although many groups have developed highly accurate algorithms for detecting PVC beats, results have generally been limited to relatively small data sets. Additionally, many of the highest classification accuracies (>90%) have been achieved in experiments where training and testing sets overlapped significantly. Expanding the overall data set greatly reduces overall accuracy due to significant variation in ECG morphology among different patients. As a result, we believe that morphological information must be coupled with timing information, which is more constant among patients, in order to achieve high classification accuracy for larger data sets. With this approach, we combined wavelet-transformed ECG waves with timing information as our feature set for classification. We used select waveforms of 18 files of the MIT/BIH arrhythmia database, which provides an annotated collection of normal and arrhythmic beats, for training our neural-network classifier. We then tested the classifier on these 18 training files as well as 22 other files from the database. The accuracy was 95.16% over 93,281 beats from all 40 files, and 96.82% over the 22 files outside the training set in differentiating normal, PVC, and other beats

Robust ballistocardiogram acquisition for home monitoring

The ballistocardiogram (BCG) measures the reaction of the body to cardiac ejection forces, and is an effective, non-invasive means of evaluating cardiovascular function. A simple, robust method is presented for acquiring high-quality, repeatable BCG signals from a modified, commercially available scale. The measured BCG waveforms for all subjects qualitatively matched values in the existing literature and physiologic expectations in terms of timing and IJ amplitude. Additionally, the BCG IJ amplitude was shown to be correlated with diastolic filling time for a subject with premature atrial contractions, demonstrating the sensitivity of the apparatus to beat-by-beat hemodynamic changes. The signal-to-noise ratio (SNR) of the BCG was estimated using two methods, and the average SNR over all subjects was greater than 12 for both estimates. The BCG measurement was shown to be repeatable over 50 recordings taken from the same subject over a three week period. This approach could allow patients at home to monitor trends in cardiovascular health.

Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice

Ubiquitous blood pressure (BP) monitoring is needed to improve hypertension detection and control and is becoming feasible due to recent technological advances such as in wearable sensing. Pulse transit time (PTT) represents a well-known potential approach for ubiquitous BP monitoring. The goal of this review is to facilitate the achievement of reliable ubiquitous BP monitoring via PTT. We explain the conventional BP measurement methods and their limitations; present models to summarize the theory of the PTT-BP relationship; outline the approach while pinpointing the key challenges; overview the previous work toward putting the theory to practice; make suggestions for best practice and future research; and discuss realistic expectations for the approach.

Ballistocardiography and Seismocardiography: A Review of Recent Advances

In the past decade, there has been a resurgence in the field of unobtrusive cardiomechanical assessment, through advancing methods for measuring and interpreting ballistocardiogram (BCG) and seismocardiogram (SCG) signals. Novel instrumentation solutions have enabled BCG and SCG measurement outside of clinical settings, in the home, in the field, and even in microgravity. Customized signal processing algorithms have led to reduced measurement noise, clinically relevant feature extraction, and signal modeling. Finally, human subjects physiology studies have been conducted using these novel instruments and signal processing tools with promising results. This paper reviews the recent advances in these areas of modern BCG and SCG research.

Non-invasive cardiac output trending during exercise recovery on a bathroom-scale-based ballistocardiograph.

Cardiac ejection of blood into the aorta generates a reaction force on the body that can be measured externally via the ballistocardiogram (BCG). In this study, a commercial bathroom scale was modified to measure the BCGs of nine healthy subjects recovering from treadmill exercise. During the recovery, Doppler echocardiogram signals were obtained simultaneously from the left ventricular outflow tract of the heart. The percentage changes in root-mean-square (RMS) power of the BCG were strongly correlated with the percentage changes in cardiac output measured by Doppler echocardiography (R(2) = 0.85, n = 275 data points). The correlation coefficients for individually analyzed data ranged from 0.79 to 0.96. Using Bland-Altman methods for assessing agreement, the mean bias was found to be -0.5% (+/-24%) in estimating the percentage changes in cardiac output. In contrast to other non-invasive methods for trending cardiac output, the unobtrusive procedure presented here uses inexpensive equipment and could be performed without the aid of a medical professional.

Rapid Assessment of Cardiac Contractility on a Home Bathroom Scale

Analyzing systolic time intervals-specifically the preejection-period (PEP)-is widely accepted as one of the few methods for the noninvasive assessment of cardiac contractility. In this paper, we investigated the ballistocardiogram (BCG) as a way to noninvasively measure myocardial contractility when combined with the ECG. Specifically, we derived a parameter from the BCG and ECG that we hypothesized would be highly correlated to PEP. This is the time delay between the J-wave peak of the BCG and the R-wave of the ECG, which we refer to as the RJ interval. The RJ interval was correlated to PEP (r2 = 0.86) for 2126 heart beats across ten subjects, with a y-intercept of 138 ms and slope of 1.05. This suggests that the RJ interval can be reliably used as a noninvasive assessment of cardiac contractility.

Novel methods for estimating the ballistocardiogram signal using a simultaneously acquired electrocardiogram

The ballistocardiogram (BCG) signal represents the movements of the body in response to cardiac ejection of blood. Recently, many groups have developed low-cost instrumentation for facilitating BCG measurement in the home. The standard method used in the literature for estimating the BCG pulse response has generally been ensemble averaging over several beats. Unfortunately, since the BCG pulse response is likely longer than a typical heartbeat interval, this standard approach does not yield a full-length estimate of the response. This paper describes a simple, novel algorithm for estimating the full-length BCG pulse response using the R-wave timing of a simultaneously acquired electrocardiogram (ECG). With this pulse response, the full signal can be reconstructed, enabling the analysis of slow transient effects in the BCG signal, and of the measurement noise. Additionally, while this paper focuses only on the BCG signal, the same algorithm could be applied to other biomedical signals such as the phonocardiogram or impedance cardiogram, particularly when the heartbeat interval is shorter than the duration of the cpulse response.

Ballistocardiogram as Proximal Timing Reference for Pulse Transit Time Measurement: Potential for Cuffless Blood Pressure Monitoring

Goal: We tested the hypothesis that the ballistocardiogram (BCG) waveform could yield a viable proximal timing reference for measuring pulse transit time (PTT). Methods: From 15 healthy volunteers, we measured PTT as the time interval between BCG and a noninvasively measured finger blood pressure (BP) waveform. To evaluate the efficacy of the BCG-based PTT in estimating BP, we likewise measured pulse arrival time (PAT) using the electrocardiogram (ECG) as proximal timing reference and compared their correlations to BP. Results: BCG-based PTT was correlated with BP reasonably well: the mean correlation coefficient (r ) was 0.62 for diastolic (DP), 0.65 for mean (MP), and 0.66 for systolic (SP) pressures when the intersecting tangent method was used as distal timing reference. Comparing four distal timing references (intersecting tangent, maximum second derivative, diastolic minimum, and systolic maximum), PTT exhibited the best correlation with BP when the systolic maximum method was used (mean r value was 0.66 for DP, 0.67 for MP, and 0.70 for SP). PTT was more strongly correlated with DP than PAT regardless of the distal timing reference: mean r value was 0.62 versus 0.51 (p = 0.07) for intersecting tangent, 0.54 versus 0.49 (p = 0.17) for maximum second derivative, 0.58 versus 0.52 (p = 0.37) for diastolic minimum, and 0.66 versus 0.60 (p = 0.10) for systolic maximum methods. The difference between PTT and PAT in estimating DP was significant (p = 0.01) when the r values associated with all the distal timing references were compared altogether. However, PAT appeared to outperform PTT in estimating SP ( p = 0.31 when the r values associated with all the distal timing references were compared altogether). Conclusion: We conclude that BCG is an adequate proximal timing reference in deriving PTT, and that BCG-based PTT may be superior to ECG-based PAT in estimating DP. Significance: PTT with BCG as proximal timing reference has potential to enable convenient and ubiquitous cuffless BP monitoring.

Toward Continuous, Noninvasive Assessment of Ventricular Function and Hemodynamics: Wearable Ballistocardiography

Ballistocardiography, the measurement of the reaction forces of the body to cardiac ejection of blood, is one of the few techniques available for unobtrusively assessing the mechanical aspects of cardiovascular health outside clinical settings. Recently, multiple experimental studies involving healthy subjects and subjects with various cardiovascular diseases have demonstrated that the ballistocardiogram (BCG) signal can be used to trend cardiac output, contractility, and beat-by-beat ventricular function for arrhythmias. The majority of these studies has been performed with “fixed” BCG instrumentation-such as weighing scales or chairs-rather than wearable measurements. Enabling wearable, and thus continuous, recording of BCG signals would greatly expand the capabilities of the technique; however, BCG signals measured using wearable devices are morphologically dissimilar to measurements from “fixed” instruments, precluding the analysis and interpretation techniques from one domain to be applied to the other. In particular, the time intervals between the electrocardiogram (ECG) and BCG-namely, the R-J interval, a surrogate for measuring contractility changes-are significantly different for the accelerometer compared to a “fixed” BCG measurement. This paper addresses this need for quantitatively normalizing wearable BCG measurement to “fixed” measurements with a systematic experimental approach. With these methods, the same analysis and interpretation techniques developed over the past decade for “fixed” BCG measurement can be successfully translated to wearable measurements.

Adaptive Cancellation of Floor Vibrations in Standing Ballistocardiogram Measurements Using a Seismic Sensor as a Noise Reference

An adaptive noise canceller was used to reduce the effect of floor vibrations on ballistocardiogram (BCG) measurements from a modified electronic bathroom scale. A seismic sensor was placed next to the scale on the floor and used as the noise reference input to the noise canceller. BCG recordings were acquired from a healthy subject while another person stomped around the scale, thus causing increased floor vibrations. The noise canceller substantially eliminated the artifacts in the BCG signal due to these vibrations without distorting the morphology of the measured BCG. Additionally, recordings were obtained from another subject standing inside a parked bus while the engine was running. The artifacts due to the vibrations of the engine, and the other vehicles moving on the road next to the bus, were also effectively eliminated by the noise canceller. The system with automatic floor vibration cancellation could be used to increase BCG measurement robustness in home monitoring applications. Additionally, the noise cancellation approach may enable BCG recording in ambulances-or other transport vehicles-where noninvasive hemodynamic monitoring may otherwise not be feasible.