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Computer Assisted Auscultation System for Phonoangiography of the Carotid Artery

Computer Assisted Auscultation System for Phonoangiography of the Carotid Artery Current Directions in Biomedical Engineering 2019;5(1):175-178 Thomas Sühn*, Naghmeh Mahmoodian, Arathi Sreenivas, Iván Maldonado, Moritz Spiller, Axel Boese, Alfredo Illanes, Michael Bloxton, Michael Friebe Computer Assisted Auscultation System for Phonoangiography of the Carotid Artery and 35% to the informal cost to take care of people with CVD Abstract: Cerebrovascular diseases such as stenosis, [2]. The carotid arteries are crucial for the supply of atherosclerosis or distention of the carotid artery are oxygenated blood to the head and brain. Vascular diseases accountable for about 1 million death per year across Europe. associated to the carotid such as atherosclerosis, distension or Diagnostic tools like ultrasound imaging, angiography or stenosis can cause major complications and in worst case can magnetic resonance-based imaging require specific hardware lead to the event of stroke [3]. Narrowing of the carotid artery evolves when fibrous material such as fat, cholesterol or and highly depend on the experience of the examining calcium deposits on the inner vessel layer. This alters the blood clinician. In contrast auscultation with a stethoscope can be flow in the particular area and potentially reduces supply of used to screen for carotid bruits – audible vascular sounds the associated anatomic area with oxygenated blood. associated with turbulent blood flow – a method called Treatment methods for carotid stenosis (CS) vary between phonoangiography. A reliable auscultation setup is conservative anti-platelet drug therapy or aggressive invasive prerequisite to ensure high signal quality, adequate processing treatment strategies such as carotid endarterectomy or angioplasty and stenting. For the treatment decision it is and the objective evaluation of this audible signal. We propose crucial to distinguish between two manifestations of CS: a computer assisted auscultation system for the acquisition of symptomatic and asymptomatic cases. Both types differ vascular sounds of the carotid. The system comprises of an significantly in the related risk of vascular events, their natural auscultation device, a smartphone-based control application history and with that prognosis for the patient. [4] and cloud-based signal analysis and storage. It is designed to However, there is an ongoing debate about current CS management guidelines or the evidence for certain treatment facilitate the objective assessment, screening and monitoring options [5]. Especially with respect to asymptomatic of long-term changes in the vessel condition based on manifestations, current studies ascertain the need for new and auscultation of the carotid artery. effective prevention strategies, screening tools for high risk patients, along with the implementation of personalised Keywords: Phonoangiography, carotid stenosis, computer management strategies and related monitoring approaches [6]. assisted auscultation, cerebrovascular diseases. State of the art diagnostic tools for CS are based on imaging technology such as US, angiography or MRI and https://doi.org/10.1515/cdbme-2019-0044 require expensive and bulky hardware. In contrast, the auscultation of the flow of blood in vessels e.g. in the carotid arteries using a stethoscope is an affordable and simple diagnostic method. Based on the audible signal, experienced 1 Introduction cardiologists are able to identify tiny blood flow dynamical changes in the vessel. This phonoangiography called method can be used to screen for carotid bruits - audible vascular Cerebrovascular diseases (CVD) are 2nd most common cause sounds associated with turbulent blood flow. Since it is of death across Europe, accounting for 11% and a total number possible to hear these changes, it should also be possible to of 1.0 million death per year according to the WHO [1]. They measure and objectively quantify vascular sounds over a have a major economic and human impact on society and are period of time. Dynamical changes in the flow and the sound estimated to cost the EU €45 billion a year, from which 44% signals can for example be associated with a pathological is related to direct health care costs, 21% to productivity losses narrowing of the vessel and further indicate the need for additional diagnostic investigations [7]. A reliable auscultation setup is considered crucial for ______ signal acquisition with reproducible high quality, to allow *Corresponding author: Thomas Sühn: Chair of Catheter adequate processing and the objective evaluation of a curently Technologies and Image Guided Therapies, Otto-von-Guericke- subjectively assessed audible signal. We propose a computer University, Magdeburg, Germany, e-mail: thomas.suehn@ovgu.de assisted Phonoangiography system for auscultation and Naghmeh Mahmoodian, Arathi Sreeniva,s Iván Maldonado, acquisition of vascular sounds of the carotid, characterisation Moritz Spiller, Axel Boese, Alfredo Illanes, Michael Friebe: of carotid bruits and subsequent assessment of long-term Otto-von-Guericke-University, Magdeburg, Germany. Michael changes in the vessel condition. Bloxton: Bloxton Investment Group, LLC., San Diego, USA. Open Access. © 2019 Thomas Sühn et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 License. T. Sühn et al., Computer Assisted Auscultation System fo r Phonoangiography of the Carotid Artery — 176 (BT) interface for data transmission and communication with 2 Phonoangiography System the smartphone-based control interface. For standalone operation of the device, a printed circuit board (PCB) with The introduced auscultation system comprises of three main button switches and LEDs allows control of the device without components (Figure 1): 1. A handheld and easy-to-use auscultation device, for smartphone. signal acquisition. 2. A control interface implemented as smartphone application, for the visualization and local storage of auscultation signals and additional information. 3. A cloud-based signal analysis and database, for long term storage and organization of auscultation signals, processing and subsequent diagnosis and/or monitoring of individual subjects. Auscultation Device Signal Analysis and Database  Signal quality check Signal Cloud  Feedback to the user processing  Sensor location adjustment Data Position optimization transmission Signal acquisition and local storage Smartphone Application Figure 2: Prototype of the handheld auscultation device consisting of sensing unit with stethoscope-inspired interface to the skin, user Signal preprocessing Visualization interface for standalone operation and Raspberry Pi as host system. Control Data transmission interface Figure 1: Main components of the proposed computer assisted 2.2 Smartphone Application phonoangiography system: auscultation device, smartphone- A smartphone application for android-based operating systems based control interface and cloud-based analysis and storage. (Android 5.0 / API level 21 - 9 / API level 28) was developed to control the auscultation device in a convenient way. The application was implemented with Android Studio (Version 2.1 Auscultation Device 3.4.1, Android SDK: 26.1.1) in Java programming language. Transmission and communication of the data and control To transduce the sound, caused by pulsation of the carotid commands between device and smartphone is implemented artery and the subsequent vibration of the skin, an auscultation wireless via the BT service Advanced Audio Distribution device was designed and is depicted in Figure 2. The sensing Profile (A2DP). A universally unique identifier (UUID) is unit comprises of two audio sensors (SPH0645LM4HB - used to identify the auscultation device and allow to establish Knowles Electronics, LLC, Illinois, USA) based on the a connection to the smartphone. The application comprises condenser microphone principle and implemented in MEMS functionalities such as: technology. The microphone comes with an internal  turning on BT communication of the smartphones amplification and an 18-bit sigma-delta-converter, providing a  discover and connect to the auscultation device digital output via I2S communication protocol and allowing a  start and stop signal acquisition via control commands synchronised recording with two channels. For mechanical  visualize the acquired and transferred audio signals contact to the skin, an interface combining two setups inspired  add patient details and additional information by bell and diaphragm of a stethoscope chest piece is used. The  store and organize the signals in a local database sensing unit is capable to acquire carotid sounds in a  visualize and edit information of signals in the database reproducible manner and of similar quality then signals form expensive digital stethoscopes [8]. In Figure 3, the two views for input of patient details and for A minicomputer (Raspberry Pi 3 Model B - Raspberry Pi the visualization of recorded audio signals are shown Foundation, UK) is used as host system to control the sensor exemplary. via the provided I2S protocol. Further, it provides a Bluetooth Data transmission T. Sühn et al., Computer Assisted Auscultation System for Phonoangiography of the Carotid Arter y— 177 Figure 3: Views from the storyboard of the developed smartphone Figure 4: Steps of the time-varying autoregressive signal analysis. application. Here, the control interface is used for input of subject TV-AR models are computed from the filtered and decomposed related information and visualization of acquired sound signals. signals and subsequently the spectrum and poles are analysed. possible to identify different dynamics associated to both measurement intervals and also to the intervals between the 2.3 Signal Analysis and Database main valves sounds. The computed TV-PSD for both individuals show, that dynamics can be very different from The acquired carotid signals are stored temporary on the one subject to another one for selected modes of the EMD. smartphone. Eventually, the data get transmitted to a server and subsequently processed and analysed. We assume that carotid sounds will change over the human life time due to changes inside the vessel. To detect traces that are invariable in very long-term spaced recordings in the highly short-term nonstationary carotid audio, an Empirical Mode Decomposition (EMD) and time-varying (TV) autoregressive (AR) analysis is proposed. EMD has been proposed as an adaptive time-frequency analysis method for processes involving nonlinear and nonstationary characteristics [9]. Here the method is used to decompose the carotid audio signal in different modes and to identify dynamical changes that indicate vessel characteristic of each subject. The recorded signals were first filtered using a wavelet based (DWT) band- pass filter and decomposed using EMD. Subsequently, TV-AR models were computed for some selected modes and the TV power spectral density (PSD) and poles were computed and analysed [10]. Figure 4 depicts the main steps of the time- varying signal analysis. 3 Results and Discussion Figure 5 depicts 13 seconds of carotid sound signals of two Figure 5: Carotid sound signals (top) of two individuals A and B and different individuals. Two measurements were acquired within two measurement cycles within an interval of 3 weeks are shown. an interval of 3 weeks. The respective TV-AR spectrums and The TV-PSD (middle) and maximal energy pole frequency of TV- the TV maximal energy pole frequency are plotted below. It is AR models (bottom) for selected modes of the EMD are plotted. T. Sühn et al., Computer Assisted Auscultation System for Phonoangiography of the Carotid Arter y— 178 Investigations of Carotid Stenosis to Identify Vulnerable However, for the same subject the spectral properties of the Atherosclerotic Plaque and Determine Individual Stroke Risk. maximal energy pole are more or less invariant from Circulation Journal, CJ-16. measurement cycle to cycle. Preliminary results show, that [4] Touze, E. (2012). Treatment of carotid stenosis. Current TV-AR poles of certain modes of the decomposed carotid vascular pharmacology, 10(6), 734-738. [5] Abbott, A. L., Paraskevas, K. I., Kakkos, S. K., Golledge, J., audio signal are different from subject to subject. The TV-AR Eckstein, H. H., Diaz-Sandoval, L. J., ... & Montero-Baker, M. analysis approach combined with EMD enables the extraction (2015). Systematic review of guidelines for the management of quantitative spectral parameters and appears to allow of asymptomatic and symptomatic carotid stenosis. Stroke, distinction between individuals based on the vascular sounds. 46(11), 3288-3301. [6] De Waard, D. D., Morris, D., De Borst, G. J., Bulbulia, R., & Halliday, A. (2017). Asymptomatic carotid artery stenosis: who should be screened, who should be treated and how should we treat them?. Journal of Cardiovascular Surgery, 58(1). 4 Conclusion [7] Tavel, M. E., & Bates, J. R. (2006). The cervical bruit: sound spectral analysis related to severity of carotid arterial disease. A computer assisted auscultation system for phono- Clinical cardiology, 29(10), 462-465. angiography of the carotid artery was proposed. The system is [8] Sühn, T., Sreenivas, A., Mahmoodian, N., Maldonado, I., Boese, A., Illanes, A., … & Friebe, M. (2019). capable to acquire vascular sound signals of similar quality Phonoangiography for the Monitoring of Carotid Artery then a digital stethoscope and can be controlled via a Diseases – Design Considerations for a Computer Assisted smartphone application in a convenient way. This enables Auscultation System (accepted). In 2019 Proc IEEE Eng Med reproducible and long-term signal acquisition of individuals Biol Soc, Berlin, GermanyCardiology (CinC) (pp. 1-4). IEEE. and the build-up of a database for signal analysis. [9] Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2014). Improved complete ensemble EMD: A suitable tool for The acquired sound data can be used to extract long term biomedical signal processing. Biomedical Signal Processing stable blood flow features, that can be associated to a given and Control, 14, 19-29. subject. The hypothesis is, that extract features represent [10] Thanagasundram, S., Spurgeon, S., & Schlindwein, F. S. physical characteristics of the vessel wall such as stiffness, (2008). A fault detection tool using analysis from an autoregressive model pole trajectory. Journal of Sound and indicate turbulent blood flow or bruits. This will enable the Vibration, 317(3-5), 975-993. creation of personal auscultation profiles which later on can be [11] Maldonado, I., Illanes, A., Boese, A., & Friebe, M. (2017). used for long-term examination of the vessel status. Potential Characterization of a carotid distension waveform from audio applications are the screening for vascular conditions or the signal acquired with a stethoscope. In 2017 Computing in monitoring of diagnosed vascular diseases. Further, carotid Cardiology (CinC) (pp. 1-4). IEEE. sound signals can be deployed to extract diagnostic parameters such as the carotid distension and related blood pressure waveforms, currently acquired via imaging modalities [11]. Author Statement Research funding: This research was financially supported by the Federal Ministry of Education and Research in the context of the INKA Project (Grant Number 03IPT7100X). Conflict of interest: Authors state no conflict of interest. Informed consent: Informed consent has been obtained from all individuals included in this study. References [1] Townsend, N., Wilson, L., Bhatnagar, P., Wickramasinghe, K., Rayner, M., & Nichols, M. (2016). Cardiovascular disease in Europe: epidemiological update 2016. European heart journal, 37(42), 3232-3245. [2] Wilkins, E., Wilson, L., Wickramasinghe, K., Bhatnagar, P., Leal, J., Luengo-Fernandez, R., ... & Townsend, N. (2017). European cardiovascular disease statistics 2017. [3] Liem, M. I., Kennedy, F., Bonati, L. H., van der Lugt, A., Coolen, B. F., Nederveen, A. J., ... & Nederkoorn, P. J. (2017). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Directions in Biomedical Engineering de Gruyter

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Publisher
de Gruyter
Copyright
© 2019 by Walter de Gruyter Berlin/Boston
eISSN
2364-5504
DOI
10.1515/cdbme-2019-0044
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Abstract

Current Directions in Biomedical Engineering 2019;5(1):175-178 Thomas Sühn*, Naghmeh Mahmoodian, Arathi Sreenivas, Iván Maldonado, Moritz Spiller, Axel Boese, Alfredo Illanes, Michael Bloxton, Michael Friebe Computer Assisted Auscultation System for Phonoangiography of the Carotid Artery and 35% to the informal cost to take care of people with CVD Abstract: Cerebrovascular diseases such as stenosis, [2]. The carotid arteries are crucial for the supply of atherosclerosis or distention of the carotid artery are oxygenated blood to the head and brain. Vascular diseases accountable for about 1 million death per year across Europe. associated to the carotid such as atherosclerosis, distension or Diagnostic tools like ultrasound imaging, angiography or stenosis can cause major complications and in worst case can magnetic resonance-based imaging require specific hardware lead to the event of stroke [3]. Narrowing of the carotid artery evolves when fibrous material such as fat, cholesterol or and highly depend on the experience of the examining calcium deposits on the inner vessel layer. This alters the blood clinician. In contrast auscultation with a stethoscope can be flow in the particular area and potentially reduces supply of used to screen for carotid bruits – audible vascular sounds the associated anatomic area with oxygenated blood. associated with turbulent blood flow – a method called Treatment methods for carotid stenosis (CS) vary between phonoangiography. A reliable auscultation setup is conservative anti-platelet drug therapy or aggressive invasive prerequisite to ensure high signal quality, adequate processing treatment strategies such as carotid endarterectomy or angioplasty and stenting. For the treatment decision it is and the objective evaluation of this audible signal. We propose crucial to distinguish between two manifestations of CS: a computer assisted auscultation system for the acquisition of symptomatic and asymptomatic cases. Both types differ vascular sounds of the carotid. The system comprises of an significantly in the related risk of vascular events, their natural auscultation device, a smartphone-based control application history and with that prognosis for the patient. [4] and cloud-based signal analysis and storage. It is designed to However, there is an ongoing debate about current CS management guidelines or the evidence for certain treatment facilitate the objective assessment, screening and monitoring options [5]. Especially with respect to asymptomatic of long-term changes in the vessel condition based on manifestations, current studies ascertain the need for new and auscultation of the carotid artery. effective prevention strategies, screening tools for high risk patients, along with the implementation of personalised Keywords: Phonoangiography, carotid stenosis, computer management strategies and related monitoring approaches [6]. assisted auscultation, cerebrovascular diseases. State of the art diagnostic tools for CS are based on imaging technology such as US, angiography or MRI and https://doi.org/10.1515/cdbme-2019-0044 require expensive and bulky hardware. In contrast, the auscultation of the flow of blood in vessels e.g. in the carotid arteries using a stethoscope is an affordable and simple diagnostic method. Based on the audible signal, experienced 1 Introduction cardiologists are able to identify tiny blood flow dynamical changes in the vessel. This phonoangiography called method can be used to screen for carotid bruits - audible vascular Cerebrovascular diseases (CVD) are 2nd most common cause sounds associated with turbulent blood flow. Since it is of death across Europe, accounting for 11% and a total number possible to hear these changes, it should also be possible to of 1.0 million death per year according to the WHO [1]. They measure and objectively quantify vascular sounds over a have a major economic and human impact on society and are period of time. Dynamical changes in the flow and the sound estimated to cost the EU €45 billion a year, from which 44% signals can for example be associated with a pathological is related to direct health care costs, 21% to productivity losses narrowing of the vessel and further indicate the need for additional diagnostic investigations [7]. A reliable auscultation setup is considered crucial for ______ signal acquisition with reproducible high quality, to allow *Corresponding author: Thomas Sühn: Chair of Catheter adequate processing and the objective evaluation of a curently Technologies and Image Guided Therapies, Otto-von-Guericke- subjectively assessed audible signal. We propose a computer University, Magdeburg, Germany, e-mail: thomas.suehn@ovgu.de assisted Phonoangiography system for auscultation and Naghmeh Mahmoodian, Arathi Sreeniva,s Iván Maldonado, acquisition of vascular sounds of the carotid, characterisation Moritz Spiller, Axel Boese, Alfredo Illanes, Michael Friebe: of carotid bruits and subsequent assessment of long-term Otto-von-Guericke-University, Magdeburg, Germany. Michael changes in the vessel condition. Bloxton: Bloxton Investment Group, LLC., San Diego, USA. Open Access. © 2019 Thomas Sühn et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 License. T. Sühn et al., Computer Assisted Auscultation System fo r Phonoangiography of the Carotid Artery — 176 (BT) interface for data transmission and communication with 2 Phonoangiography System the smartphone-based control interface. For standalone operation of the device, a printed circuit board (PCB) with The introduced auscultation system comprises of three main button switches and LEDs allows control of the device without components (Figure 1): 1. A handheld and easy-to-use auscultation device, for smartphone. signal acquisition. 2. A control interface implemented as smartphone application, for the visualization and local storage of auscultation signals and additional information. 3. A cloud-based signal analysis and database, for long term storage and organization of auscultation signals, processing and subsequent diagnosis and/or monitoring of individual subjects. Auscultation Device Signal Analysis and Database  Signal quality check Signal Cloud  Feedback to the user processing  Sensor location adjustment Data Position optimization transmission Signal acquisition and local storage Smartphone Application Figure 2: Prototype of the handheld auscultation device consisting of sensing unit with stethoscope-inspired interface to the skin, user Signal preprocessing Visualization interface for standalone operation and Raspberry Pi as host system. Control Data transmission interface Figure 1: Main components of the proposed computer assisted 2.2 Smartphone Application phonoangiography system: auscultation device, smartphone- A smartphone application for android-based operating systems based control interface and cloud-based analysis and storage. (Android 5.0 / API level 21 - 9 / API level 28) was developed to control the auscultation device in a convenient way. The application was implemented with Android Studio (Version 2.1 Auscultation Device 3.4.1, Android SDK: 26.1.1) in Java programming language. Transmission and communication of the data and control To transduce the sound, caused by pulsation of the carotid commands between device and smartphone is implemented artery and the subsequent vibration of the skin, an auscultation wireless via the BT service Advanced Audio Distribution device was designed and is depicted in Figure 2. The sensing Profile (A2DP). A universally unique identifier (UUID) is unit comprises of two audio sensors (SPH0645LM4HB - used to identify the auscultation device and allow to establish Knowles Electronics, LLC, Illinois, USA) based on the a connection to the smartphone. The application comprises condenser microphone principle and implemented in MEMS functionalities such as: technology. The microphone comes with an internal  turning on BT communication of the smartphones amplification and an 18-bit sigma-delta-converter, providing a  discover and connect to the auscultation device digital output via I2S communication protocol and allowing a  start and stop signal acquisition via control commands synchronised recording with two channels. For mechanical  visualize the acquired and transferred audio signals contact to the skin, an interface combining two setups inspired  add patient details and additional information by bell and diaphragm of a stethoscope chest piece is used. The  store and organize the signals in a local database sensing unit is capable to acquire carotid sounds in a  visualize and edit information of signals in the database reproducible manner and of similar quality then signals form expensive digital stethoscopes [8]. In Figure 3, the two views for input of patient details and for A minicomputer (Raspberry Pi 3 Model B - Raspberry Pi the visualization of recorded audio signals are shown Foundation, UK) is used as host system to control the sensor exemplary. via the provided I2S protocol. Further, it provides a Bluetooth Data transmission T. Sühn et al., Computer Assisted Auscultation System for Phonoangiography of the Carotid Arter y— 177 Figure 3: Views from the storyboard of the developed smartphone Figure 4: Steps of the time-varying autoregressive signal analysis. application. Here, the control interface is used for input of subject TV-AR models are computed from the filtered and decomposed related information and visualization of acquired sound signals. signals and subsequently the spectrum and poles are analysed. possible to identify different dynamics associated to both measurement intervals and also to the intervals between the 2.3 Signal Analysis and Database main valves sounds. The computed TV-PSD for both individuals show, that dynamics can be very different from The acquired carotid signals are stored temporary on the one subject to another one for selected modes of the EMD. smartphone. Eventually, the data get transmitted to a server and subsequently processed and analysed. We assume that carotid sounds will change over the human life time due to changes inside the vessel. To detect traces that are invariable in very long-term spaced recordings in the highly short-term nonstationary carotid audio, an Empirical Mode Decomposition (EMD) and time-varying (TV) autoregressive (AR) analysis is proposed. EMD has been proposed as an adaptive time-frequency analysis method for processes involving nonlinear and nonstationary characteristics [9]. Here the method is used to decompose the carotid audio signal in different modes and to identify dynamical changes that indicate vessel characteristic of each subject. The recorded signals were first filtered using a wavelet based (DWT) band- pass filter and decomposed using EMD. Subsequently, TV-AR models were computed for some selected modes and the TV power spectral density (PSD) and poles were computed and analysed [10]. Figure 4 depicts the main steps of the time- varying signal analysis. 3 Results and Discussion Figure 5 depicts 13 seconds of carotid sound signals of two Figure 5: Carotid sound signals (top) of two individuals A and B and different individuals. Two measurements were acquired within two measurement cycles within an interval of 3 weeks are shown. an interval of 3 weeks. The respective TV-AR spectrums and The TV-PSD (middle) and maximal energy pole frequency of TV- the TV maximal energy pole frequency are plotted below. It is AR models (bottom) for selected modes of the EMD are plotted. T. Sühn et al., Computer Assisted Auscultation System for Phonoangiography of the Carotid Arter y— 178 Investigations of Carotid Stenosis to Identify Vulnerable However, for the same subject the spectral properties of the Atherosclerotic Plaque and Determine Individual Stroke Risk. maximal energy pole are more or less invariant from Circulation Journal, CJ-16. measurement cycle to cycle. Preliminary results show, that [4] Touze, E. (2012). Treatment of carotid stenosis. Current TV-AR poles of certain modes of the decomposed carotid vascular pharmacology, 10(6), 734-738. [5] Abbott, A. L., Paraskevas, K. I., Kakkos, S. K., Golledge, J., audio signal are different from subject to subject. The TV-AR Eckstein, H. H., Diaz-Sandoval, L. J., ... & Montero-Baker, M. analysis approach combined with EMD enables the extraction (2015). Systematic review of guidelines for the management of quantitative spectral parameters and appears to allow of asymptomatic and symptomatic carotid stenosis. Stroke, distinction between individuals based on the vascular sounds. 46(11), 3288-3301. [6] De Waard, D. D., Morris, D., De Borst, G. J., Bulbulia, R., & Halliday, A. (2017). Asymptomatic carotid artery stenosis: who should be screened, who should be treated and how should we treat them?. Journal of Cardiovascular Surgery, 58(1). 4 Conclusion [7] Tavel, M. E., & Bates, J. R. (2006). The cervical bruit: sound spectral analysis related to severity of carotid arterial disease. A computer assisted auscultation system for phono- Clinical cardiology, 29(10), 462-465. angiography of the carotid artery was proposed. The system is [8] Sühn, T., Sreenivas, A., Mahmoodian, N., Maldonado, I., Boese, A., Illanes, A., … & Friebe, M. (2019). capable to acquire vascular sound signals of similar quality Phonoangiography for the Monitoring of Carotid Artery then a digital stethoscope and can be controlled via a Diseases – Design Considerations for a Computer Assisted smartphone application in a convenient way. This enables Auscultation System (accepted). In 2019 Proc IEEE Eng Med reproducible and long-term signal acquisition of individuals Biol Soc, Berlin, GermanyCardiology (CinC) (pp. 1-4). IEEE. and the build-up of a database for signal analysis. [9] Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2014). Improved complete ensemble EMD: A suitable tool for The acquired sound data can be used to extract long term biomedical signal processing. Biomedical Signal Processing stable blood flow features, that can be associated to a given and Control, 14, 19-29. subject. The hypothesis is, that extract features represent [10] Thanagasundram, S., Spurgeon, S., & Schlindwein, F. S. physical characteristics of the vessel wall such as stiffness, (2008). A fault detection tool using analysis from an autoregressive model pole trajectory. Journal of Sound and indicate turbulent blood flow or bruits. This will enable the Vibration, 317(3-5), 975-993. creation of personal auscultation profiles which later on can be [11] Maldonado, I., Illanes, A., Boese, A., & Friebe, M. (2017). used for long-term examination of the vessel status. Potential Characterization of a carotid distension waveform from audio applications are the screening for vascular conditions or the signal acquired with a stethoscope. In 2017 Computing in monitoring of diagnosed vascular diseases. Further, carotid Cardiology (CinC) (pp. 1-4). IEEE. sound signals can be deployed to extract diagnostic parameters such as the carotid distension and related blood pressure waveforms, currently acquired via imaging modalities [11]. Author Statement Research funding: This research was financially supported by the Federal Ministry of Education and Research in the context of the INKA Project (Grant Number 03IPT7100X). Conflict of interest: Authors state no conflict of interest. Informed consent: Informed consent has been obtained from all individuals included in this study. References [1] Townsend, N., Wilson, L., Bhatnagar, P., Wickramasinghe, K., Rayner, M., & Nichols, M. (2016). Cardiovascular disease in Europe: epidemiological update 2016. European heart journal, 37(42), 3232-3245. [2] Wilkins, E., Wilson, L., Wickramasinghe, K., Bhatnagar, P., Leal, J., Luengo-Fernandez, R., ... & Townsend, N. (2017). European cardiovascular disease statistics 2017. [3] Liem, M. I., Kennedy, F., Bonati, L. H., van der Lugt, A., Coolen, B. F., Nederveen, A. J., ... & Nederkoorn, P. J. (2017).

Journal

Current Directions in Biomedical Engineeringde Gruyter

Published: Sep 1, 2019

Keywords: Phonoangiography; carotid stenosis; computer assisted auscultation; cerebrovascular diseases

There are no references for this article.