Keya R. Pandia

Motion artifact cancellation to obtain heart sounds from a single chest-worn accelerometer

This paper presents a method of extracting primary heart sound signals from chest-worn accelerometer data in the presence of motion artifacts. The proposed method outperforms noise removal techniques such as wavelet denoising and adaptive filtering. Results from six subjects show a primary heart signal detection rate of 99.36% with a false positive rate of 1.3%.

A preliminary study investigating the quantification of beat-to-beat in seismocardiogram signals

Ballistocardiography and seismocardiography are both non-invasive mechanical measurements of the vibrations of the body in response to the heartbeat. The ballistocardiogram (BCG) signal represents the movements of the whole body in response to cardiac ejection of blood into the vasculature; the seismocardiogram (SCG) corresponds to local vibrations of the chest wall associated with sub-audible tissue and blood movement and audio frequency heart-valve closure dynamics. This paper focuses on methods for quantifying “signal consistency”-a quantitative measure of how morphologically similar each heartbeat in a patients recording is compared to the ensemble average taken over the recording. Before comparing each beat to the average, known physiological sources of inconsistency-such as respiratory amplitude and timing variability-are removed, then the remaining inconsistency is quantified. Previously described methods for BCG signals are expanded to fit the high-frequency (> 20 Hz) components of the SCG. The use of this method in future work could help enable proactive management of heart disease in extra-clinical settings.

Chest-accelerometry for hemodynamic trending during valsalva-recovery

Chest-worn accelerometers have been shown to detect acoustic and mechanical signals corresponding to cardiovascular activity. This paper aims at investigating and characterizing two different components of chest acceleration (seismocardiogram) along two orthogonal axes: firstly, the sub-10 Hz ballistic signal components dominant in the vertical axis and secondly, the 10–50 Hz acoustic signal components more dominantly expressed in the radial axis. Acceleration signals from five subjects in response to a valsalva maneuver were measured. Correlations of features from the two above acceleration components were computed with respect to reference measurements of stroke volume and pulse pressure obtained with a Finapres continuous blood pressure system. The peak amplitude of the vertical ballistic and radial acoustic signal components were found to correlate well with stroke volume (R=0.78 and 0.83, for vertical ballistic and radial acoustic, respectively). Comparable correlations were found between beat RMS power (R=0.77 and 0.83) and stroke volume. Similarly, correlations were also observed between pulse pressure and peak amplitude (R=0.74 and 0.86) and the beat RMS power (R=0.74 and 0.86).

A frequency domain analysis of respiratory variations in the seismocardiogram signal

The seismocardiogram (SCG) signal traditionally measured using a chest-mounted accelerometer contains low-frequency (0-100 Hz) cardiac vibrations that can be used to derive diagnostically relevant information about cardiovascular and cardiopulmonary health. This work is aimed at investigating the effects of respiration on the frequency domain characteristics of SCG signals measured from 18 healthy subjects. Toward this end, the 0-100 Hz SCG signal bandwidth of interest was sub-divided into 5 Hz and 10 Hz frequency bins to compare the spectral energy in corresponding frequency bins of the SCG signal measured during three key conditions of respiration-inspiration, expiration, and apnea. Statistically significant differences were observed between the power in ensemble averaged inspiratory and expiratory SCG beats and between ensemble averaged inspiratory and apneaic beats across the 18 subjects for multiple frequency bins in the 10-40 Hz frequency range. Accordingly, the spectral analysis methods described in this paper could provide complementary and improved classification of respiratory modulations in the SCG signal over and above time-domain SCG analysis methods.

Physical modeling of low-frequency sound propagation through human thoracic tissue

This work aims at modeling, in the presence of simplifying physical and geometrical assumptions, acoustic wave propagation through human thoracic tissue. Presented here are preliminary modeling results that are indicative of dominant lung resonances at specific frequencies. These resonant modes strongly impact pressure distribution in the tissue as well as the pressure and acceleration at the tissue-air interface. Under the modeling conditions, the effect of these lung resonant modes outweighs that of bones on acoustic waves at these frequencies.