In the analysis of fingertip photoplethysmograms (PPG), the Pulse Decomposition Analysis (PDA) has emerged as a powerful tool for the extraction of physiologically relevant information from the morphology of single digital volume pulse (DVP) cycles. In previously published works on the PDA, many different models are suggested. In this work, we conducted a data driven approach to address the question of which model to choose for the PDA. For this purpose, we compiled an extensive dataset of 7805 single DVP pulses that comprises most expectable pulse morphologies and conducted PDA simulations with four different basis functions types and a meaningful range of model orders. We then performed model selection based on the Corrected Akaike Information Criterion (AICc) with the aim of identifying the PDA models that provided the best fit. As a result, we found that a PDA model based on the linear superposition of three scaled Gamma basis functions was selected as the best fitting model in 28.1% of all pulses. The second highest relative selection frequency of 14.4% was achieved by fitting two Rayleigh functions. Consequently, we recommend to consider the employment of this PDA model in further work on the PDA.
Abstract:In recent years, the analysis of the photoplethysmographic (PPG) pulse waveforms has attracted much research focus. However, the considered signals are primarily recorded at the fingertips, which suffer from reduced peripheral perfusion in situations like hypovolemia or sepsis, rendering waveform analysis infeasible. The ear canal is not affected by cardiovascular centralization and could thus prove to be an ideal alternate measurement site for pulse waveform analysis. Therefore, we developed a novel system that allows for highly accurate photoplethysmographic measurements in the ear canal. We conducted a measurement study in order to assess the signal-to-noise ratio of our developed system Hereby, we achieved a mean SNR of 40.65 dB. Hence, we could show that our system allows for highly accurate PPG recordings in the ear canal facilitating sophisticated pulse waveform analysis. Furthermore, we demonstrated that the pulse decomposition analysis is also applicable to in-ear PPG recordings.
Gold-standards for biosignal acquisition require body-spanning sensor positioning which is contradictory to the high integration of modern wearable medical monitors. In applications where obtrusiveness can decrease accuracy, as in sleep monitoring, compact sensor configurations are not only a matter of convenience. To acquire respiratory signals, most systems rely on nasal cannula pressure sensors or inductance plethysmography. Another well-established method is the impedance pneumography, where we aim to contribute to the field of short distance electrode configurations. Evaluating distances down to 8 cm we report linear correlations above 0.85 with respect to a pneumotachometer reference. We estimate the respiratory rate with an error below 0.2 bpm. Inspiratory and expiratory phase detection is possible with an error below 2.5 %. Using a first order polynomial model we estimated the respiratory flow with a relative error of down to 19 % at 8 cm. We conclude that short distance impedance pneumography is feasible and rough flow and volume estimates are possible using linear models. Further research regarding shorter distances and calibration is of great interest.
Stethoscope auscultation is a diagnostic method widely used by medical professionals. With the introduction of digital stethoscopes, auscultation sound analysis has been objectified, which led to an increased interest in the field. Until today, however, no standard to assess the acoustical properties of stethoscopes is available. Some approaches use phantoms mimicking the properties of human soft tissue. In most cases, however, the properties of the phantoms have not been analyzed with respect to environmental variables. In our work, we propose a stethoscope characterization system for the frequency range between 50 Hz and 2.5 kHz with a small financial footprint. We analyzed its frequency behavior over temperature, time and position on the phantom and derived quantitative recommendations for environmental variables. Finally, the frequency response of a commercial digital stethoscope was characterized at different pressure levels. We conclude that the presented system is capable to stably and reproducibly assess the transfer function of digital stethoscopes. We hope that future stethoscope designs will be characterized with respect to their acoustical properties.
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