Acoustic Detection of Coronary Occlusions

Acoustic Detection of Coronary Occlusions before and after Stent Placement Using an

Electronic Stethoscope

Andrei Dragomir 1, Allison Post 1, Yasemin M. Akay 1, Hani Jneid 2,3, David Paniagua 2,3,Ali Denktas 2,3, Biykem Bozkurt 2,3 and Metin Akay 1,*1 Department of Biomedical Engineering, University of Houston, Houston, TX 77204, USA;

Andrei.Drag@gmail.com (A.D.); Allison.Post@central.uh.edu (A.P.); ymakay@uh.edu (Y.M.A.)2 Winters Center for Heart Failure Research, The Michael E. DeBakey VA Medical Center, Houston, TX 77030,USA; jneid@bcm.edu (H.J.); dpaniagua@bcm.edu (D.P.); ali.denktas@bcm.edu (A.D.);bbozkurt@bcm.edu (B.B.)

3 Cardiovascular Research Institute, Baylor College of Medicine, Houston, TX 77030, USA

* Correspondence: makay@uh.edu; Tel.: +1-832-842-8860

Academic Editors: Raúl Alcaraz Martínez and Kevin H. Knuth

Received: 27 April 2016; Accepted: 23 July 2016; Published: 29 July 2016

Abstract: More than 370,000 Americans die every year from coronary artery disease (CAD).Early detection and treatment are crucial to reducing this number. Current diagnostic and disease-monitoring methods are invasive, costly, and time-consuming. Using an electronic stethoscope and spectral and nonlinear dynamics analysis of the recorded heart sound, we investigated the acoustic signature of CAD in subjects with only a single coronary occlusion before and after stent placement, as well as subjects with clinically normal coronary arteries. The CAD signature was evaluated by estimating power ratios of the total power above 150 Hz over the total power below 150 Hz of the FFT of the acoustic signal. Additionally, approximate entropy values were

estimated to assess the differences induced by the stent placement procedure to the acoustic signature of the signals in the time domain. The groups were identified with this method with 82% sensitivity and 64% specificity (using the power ratio method) and 82% sensitivity and 55% specificity (using the approximate entropy). Power ratios and approximate entropy values after stent placement are not statistically different from those estimated from subjects with no coronary occlusions. Our approach

demonstrates that the effect of stent placement on coronary occlusions can be monitored using an electronic stethoscope.


Shimmer Sensing

A wearable chemical–electrophysiological hybrid biosensing system for real-time health and fitness monitoring

Somayeh Imani

, Amay J. Bandodkar , A. M. Vinu Mohan , Rajan Kumar , Shengfei Yu

, Joseph Wang  & Patrick P. Mercie


Flexible, wearable sensing devices can yield important information about the underlying physiology of a human subject for applications in real-time health and fitness monitoring. Despite significant progress in the fabrication of flexible biosensors that naturally comply with the epidermis, most designs measure only a small number of physical or electrophysiological parameters, and neglect the rich chemical information available from biomarkers. Here, we introduce a skin-worn wearable hybrid sensing system that offers simultaneous real-time monitoring of a biochemical (lactate) and an electrophysiological signal (electrocardiogram), for more comprehensive fitness monitoring than from physical or electrophysiological sensors alone. The two sensing modalities, comprising a three-electrode amperometric lactate biosensor and a bipolar electrocardiogram sensor, are co-fabricated on a flexible substrate and mounted on the skin. Human experiments reveal that physiochemistry and electrophysiology can be measured simultaneously with negligible cross-talk, enabling a new class of hybrid sensing devices.


Wearable sensors present an exciting opportunity to measure human physiology in a continuous, real-time and non-invasive manner1,2. Recent advances in hybrid fabrication techniques have enabled the design of wearable sensing devices in thin, conformal form factors that naturally comply with the smooth curvilinear geometry of human skin, thereby enabling intimate contact necessary for robust physiological measurements1,3,4. Development of such epidermal electronic sensors has enabled devices that can monitor respiration rate5,6,7, heart rate8,9, electrocardiograms4,10,11,12, blood oxygenation13, skin temperature14,15, bodily motion16,17,18,19,20, brain activity21,22,23 and blood pressure24,25. To date, most systems have targeted only a single measurement at a time, and most such sensors measure only physical and electrophysiological parameters, significantly limiting monitoring and diagnostic opportunities. For example, the human body undergoes complex physiological changes during physical activities such as exercise26,27, and monitoring the physiologic effect of physical activity can be important for a wide variety of subjects ranging from athletes to the elderly28,29,30. However, current wearable devices that only measure heart rate, motion and electrocardiogram provide an incomplete picture of the complex physiological changes taking place. As a result, further progress in the area of wearable sensors must include new, relevant sensing modalities, and must integrate these different modalities into a single platform for continuous, simultaneous sensing of multiple parameters relevant to a wide range of conditions, diseases, health and performance states.

Inclusion of chemical measurements can provide extremely useful insights not available from physical or electrophysiological sensors31. Chemical information can be conventionally acquired via clinical labs or point-of-care devices32,33,34; unfortunately, such approaches do not support continuous, real-time measurements, therefore limiting their utility to applications where stationary, infrequent tests are sufficient. While recent work, including our own, has demonstrated that chemicals such as electrolytes and metabolites can be measured continuously using epidermal electronics on the skin35,36,37,38, or through non-invasive monitoring of other body fluids38,39,40, these devices measure only a single parameter at once, and are not integrated with other sensing modalities. Recently, Gao et al.41 demonstrated a wearable patch that can simultaneously track levels of metabolites and electrolytes in human sweat. However, electrophysiology sensors were not included, and such multimodal sensor fusion is crucial to obtain a more comprehensive knowledge about a wearer’s well-being.

Here, we introduce a wearable device that can simultaneously measure chemical and electrophysiological parameters in the form factor of a single epidermal patch. The hybrid wearable, termed here as a Chem–Phys patch, comprises a screen-printed three-electrode amperometric lactate biosensor and two electrocardiogram electrodes, enabling concurrent real-time measurements of lactate and electrocardiogram. When used in physical-exertion monitoring, electrocardiogram measurements can help monitor heart health and function, while sweat lactate can be used to track an individual’s performance and exertion level, and is also an important biomarker for tissue oxygenation and pressure ischaemia42,43,44,45,46,47. Although prior work has demonstrated separate wearable electrocardiogram and lactate sensors, these devices were fabricated on separate platforms and thus mandate applying multiple patches on the human body, which is inconvenient and can deter long-term use. By combining a lactate biosensor and an electrocardiogram sensor, the new Chem–Phys hybrid wearable patch represents a powerful platform capable of simultaneously tracking both physicochemical and electrophysiological attributes, thus providing a more comprehensive view of a person’s health status than current wearable fitness monitors.

The Chem–Phys hybrid patch was fabricated by leveraging screen-printing technology on a thin, highly flexible polyester sheet that conforms well with the complex three-dimensional (3D) morphology of human skin to provide a low-noise signal. The working electrode of the lactate biosensor was functionalized and coated with a biocompatible biocatalytic layer (lactate oxidase (LOx)-modified prussian blue). The three amperometric electrodes were separated from the Ag/AgCl electrocardiogram electrodes via a printed hydrophobic layer to maximize sensor stability and signal-to-noise ratio even in the presence of significant perspiration. The dimensions of the electrodes and the inter-electrode distances have been optimized based on the human trials to acquire a clean electrocardiogram signal and lactate response with minimal interference between the two sensors. The two sensors were interfaced to a custom-printed circuit board (PCB) featuring a potentiostat, an electrocardiogram analogue front-end (AFE), and a bluetooth low-energy (BLE) radio for wireless telemetry of the results to a mobile platform, such as a smartphone or laptop. The hybrid sensing system was tested on three human subjects during exercise on a stationary bicycle, showing that lactate and electrocardiogram can be measured simultaneously with negligible co-interference. Electrocardiogram data was found to be similar to the data collected from standard electrode types, and extracted heart rate correlated well to commercial heart rate detectors. A control experiment, where an enzyme-free amperometric sensor was applied to a perspiring human subject, corroborated the lactate sensor’s sensitivity and selectivity towards on-body detection of physiologic lactate levels. The promising data obtained in this work thus supports the possibility of developing more advanced hybrid wearable sensors that involve complex integration of several physical and chemical sensors on the same platform for monitoring many relevant modalities.

Shimmer Sensing

Knitted Strain Sensor Textiles of Highly Conductive All-Polymeric Fibers
Shayan Seyedin†‡, Joselito M. Razal*†‡, Peter C. Innis†, Ali Jeiranikhameneh†, Stephen Beirne†, and Gordon G. Wallace*†
Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, Innovation Campus, University of Wollongong, Wollongong, New South Wales 2522, Australia
Institute for Frontier Materials, Deakin University, Geelong, Victoria 3216, Australia
ACS Appl. Mater. Interfaces, 2015, 7 (38), pp 21150–21158
A scaled-up fiber wet-spinning production of electrically conductive and highly stretchable PU/PEDOT:PSS fibers is demonstrated for the first time. The PU/PEDOT:PSS fibers possess the mechanical properties appropriate for knitting various textile structures. The knitted textiles exhibit strain sensing properties that were dependent upon the number of PU/PEDOT:PSS fibers used in knitting. The knitted textiles show sensitivity (as measured by the gauge factor) that increases with the number of PU/PEDOT:PSS fibers deployed. A highly stable sensor response was observed when four PU/PEDOT:PSS fibers were co-knitted with a commercial Spandex yarn. The knitted textile sensor can distinguish different magnitudes of applied strain with cyclically repeatable sensor responses at applied strains of up to 160%. When used in conjunction with a commercial wireless transmitter, the knitted textile responded well to the magnitude of bending deformations, demonstrating potential for remote strain sensing applications. The feasibility of an all-polymeric knitted textile wearable strain sensor was demonstrated in a knee sleeve prototype with application in personal training and rehabilitation following injury.

Shimmer Sensing


DUBLIN, 13 June 2016 - Shimmer Sensing, a leading provider of medical grade wearable wireless sensors, announced today a partnership with the Wyss Institute for Biologically Inspired Engineering at Harvard University in support of ongoing research focused on remote patient monitoring using wearable sensing technology. The research is led by Paolo Bonato, Ph.D., who is an Associate Faculty Member at the Wyss Institute and an Associate Professor in the Department of Physical Medicine and Rehabilitation at Harvard Medical School.

"Partnering with Shimmer Sensing will allow us to further develop our remote patient monitoring platform called MercuryLive," said Bonato.

MercuryLive is a platform designed to support clinicians’ remote monitoring of patients – who, for example, could have Parkinson’s disease or be stroke survivors, traumatic brain injury survivors, or children with cerebral palsy – via live streaming of wearable sensor data and an interactive video feed. Bonato’s team at the Wyss Institute is developing the latest version of the MercuryLive platform, which enables the integration of a variety of wireless devices.Shimmer’s financial support of the research and its technical expertise in wireless medical sensors will accelerate the development of MercuryLive towards applications in remote patient monitoring. Among other clinical applications, the platform being developed will allow clinicians to remotely monitor patients with knee osteoarthritis using a knee sleeve with embedded wireless sensors and observe older adults in their home using wearable sensors and a mobile robot designed to navigate the environment and reach the subject in case of an emergency.

The Wyss Institute is renowned for taking academic innovation to the next level, and partnering with physicians and the industry to bring new technologies to the bedside. We are very enthusiastic about the opportunity to support Prof. Bonato's research team and their work toward the development of the next generation of remote clinical monitoring systems,” commented Patrick White, the CEO of Shimmer Sensing.

Wearable patient monitoring systems represent the future of ambulatory medicine, and we are excited to help catalyze collaborations between engineers, clinicians and industrial partners to make this a reality,” said Wyss Institute Founding Director Donald Ingber, M.D., Ph.D., who is also the Judah Folkman Professor of Vascular Biology at Boston Children's Hospital and Harvard Medical School and Professor of Bioengineering at the Harvard John A. Paulson School of Engineering and Applied Science.

Labtech Cardiospy

Abstract of PhD Thesis Intelligent Data Processing and Its Applications

Aniko Szilvia Vanger

1 Introduction

Nowadays the rapidly increasing performance of hardware and the efficient

intelligent scientific algorithms enable us to store and process big data. This

tendency will cover more opportunities to get more and more information from

the large amount of data. My thesis is only a precursor of this topic, because

I did not have sufficient hardware and I had only a little data to be processed.

However, all the topics of my thesis belong to the intelligent data processing.

In Chapter 2 of my thesis I introduce a new clustering algorithm named

GridOPTICS, whose goal is to accelerate the well-known OPTICS density

clustering technique. The density-based clustering techniques are capable of

recognizing arbitrary-shaped clusters in a point set. The DBSCAN results in

only one cluster set, but the OPTICS generates a reachability plot from which

a lot of cluster sets can be read as a result without having to execute the whole

algorithm again. I experienced that it is very slow for large data sets, so I wanted

to nd a solution to accelerate it. I wanted to see that the speed of the GridOptics

is better than OPTICS, so I executed both the algorithms on several point sets.

In Chapter 3 of my thesis I introduce two new modules of the Cardiospy system of

Labtech Ltd. On these two projects I worked together with Istvan Juhasz, Laszlo

Farkas, Peter Toth, and 4 students of the university, Jozsef Kuk, Adam Balazs,Bela Vamosi, and David Angyal.Bela Kincs, who was the executive of the Labtech Ltd., wanted the Cardiospy system to be improved. He and his team surveyed what the demand of the users are in this area and how their software could be better. The Labtech Ltd. And the University of Debrecen worked together in two projects. In both cases theLabtech had early solutions for the algorithms, but they were insufficient and slow, the results could not be validated, or they gave insufficient results. Moreover,

there were no visualization tools for either problems. The tasks of the team of the

University of Debrecen were to give a quick algorithm and to create an interactive

visualization interface for each problem.

The goal of the first module of Cardiospy is to cluster and visualize the long (up

to 24-hours) recordings of ECG signals, because the manual evaluation of long

recordings is a lengthy and tedious task. During this project I recognized that it

is a very interesting topic to find out how the OPTICS can be accelerated with a

grid clustering method independently, without any ECG signals.

The goal of the second module of Cardiospy is to calculate and visualize the

steps of the blood pressure measurement and the values of blood pressure. The

recordings (which can contain a sequence of measurements) are collected by a

microcontroller, but this module runs on a PC. With the help of the application

the physicians can recognize the types of errors on the measurements and they

can also find the noisy measurements.

In Chapter 4 I introduce how I applied an active learning method in a subject

whose topic is database programming. I taught Oracle SQL and PL/SQL in

the Advanced DBMS 1 subject, and I saw that the students do not practice at

home. The prerequirements of this subject are the Programming language and

the Database systems courses, so they are not absolute beginners in the field. I

wanted to force the students to try out the programming tools independently, but

with the help of the teacher.

To support the active learning method, an application had to be built. The

application helps the teacher organize and monitor the tasks and their solutions

of the students. Moreover the application can verify the syntax of the solutions

before the students upload them. If the syntax is wrong, the student cannot

upload it. This feature makes the task of the teacher easier.

To demonstrate whether the active learning method is good or not, I gathered and

examined the results of the students during the 3 years when I used this method.

New results

The abstract of the thesis presents new results grouped into four main statements.

The first statement deals with a clustering method, the second one demonstrates

an application of this clustering method, namely clustering of ECG signals, which

can be considered as an application of the GridOPTICS clustering method. The

third statement introduces the visualization of the steps of the blood pressure

measurement, whereas the last statement demonstrates how the solutions of the

students can easily be managed during an active learning method for database


2.1 A clustering algorithm

Cluster analysis is an important research field of data mining, which is applied

on many other disciplines, such as pattern recognition, image processing, machine

learning, bioinformatics, information retrieval, artificial intelligence, marketing,

psychology, etc. The density-based clustering approach is capable of finding

arbitrarily shaped clusters, but they have a disadvantage, namely it is hard to

choose parameter values in order that the algorithm gives an appropriate result

(Gan et al., 2007). The OPTICS (Ankerst et al., 1999) clustering algorithm gives

not only one result but a set of the results. It builds a reachability plot, namely it

orders the input points, and it assigns a reachability distance to an input point.

Based on the reachability plot, the algorithm can produce a lot of clustering

results. Building the reachability plot is slow, but reading the clusters from the

reachability plot is fast.

The OPTICS has a limitation, namely it has high complexity, which means that

it is very slow for large datasets. (Yue et al., 2007) (Schneider and Vlachos, 2013)

Statement A - The GridOPTICS clustering algorithm: I introduced a

new clustering algorithm named GridOPTICS which is a combination of a grid

clustering technique and the OPTICS algorithm. For a large input point sets the

GridOPTICS algorithm works with insignificant information loss and provides

even one or more order of magnitude faster than the OPTICS algorithm. (Vagner,

in press)

The main idea of the GridOPTICS algorithm is to reduce the number of input

points with a grid technique and then to execute the OPTICS algorithm on the

grid structure. Based on the reachability plot, the clusters of the grid structure

can be determined. In the end, the input points can be assigned to the clusters.

The experimental results show that the execution time can be faster with more

orders of magnitude than OPTICS, which is very useful for large data sets.

However, they also show that the GridOPTICS algorithm is less accurate than


2.2 Cardiology information system for ECG signals

The big data problem also appears in the medical area. Without intelligent

information systems, the physicians cannot eOne of its modules is the ECG clustering module.

Statement B - Clustering and visualization of ECG signals: We

developed the ECG clustering and visualization module of Cardiospy software. The

goal of the module is to cluster and visualize the long (up to 24-hours) recordings

of ECG signals. In this way the cardiologists can easier find the heart beats which

morphologically differ from the normal beats. (Vagner et al., 2011 A)

On this project I worked together with Laszlo Farkas (Labtech Ltd.), Istvan

Juhasz (Faculty of Informatics, University of Debrecen), and two students from

the Faculty of Informatics, University of Debrecen, Jozsef Kuk and Adam Balazs.

My contribution to this project was to implement the clustering algorithm and

make it fast. The clustering algorithm is a special simpler version of the

GridOPTICS algorithm. I also contributed to

 2.3 Cardiology information system for blood pressure measurement

In the public health care it is very common that a microcontroller calculates the

result of oscillometric blood pressure measurements. It has only limited resources,

such as memory and processor, moreover it can give only a little feedback about

the measurement. This means that the result can be imprecise; it does not inform

the patient and the physician appropriately. (Sorvoja, 2006)

Cardiospy software has another module, the blood pressure measurement module.

It receives the recordings collected by the microcontroller. The recording can

contain only one measurement or sequence of measurements created during 24

hours. Cardiospy runs on a PC, in this way the algorithm can use more

resources (memory and processor), which means that it is faster and more precise.

Additionally, it can visualize the whole process of the measurement.

Statement C { Visualization of o-line processing of blood pressure

measurements: We developed the blood pressure measurement module of

Cardiospy software. The goal of the blood pressure measurement module is to

calculate and visualize the values of blood pressure. (Vagner et al., 2014)

The module determines the values of the blood pressure based on an oscillometric

blood pressure measurement algorithm. The application visualizes the result of

each step of the algorithm. The algorithm decides whether the result is acceptable

and authentic based on the characteristic of the measurement.

The other part of the application helps in the validation process. It executes

the blood pressure measurement algorithm on mass of the measurements each of

which has reference blood pressure values. The application shows the differences

between the results of the algorithm and the values of reference and it helps to

qualify the algorithm according to the international standards.

On this project I worked together with Peter Toth (Labtech Ltd.), Istvan Juhasz

(Faculty of Informatics, University of Debrecen), and two students from the

Faculty of Informatics, University of Debrecen, Bela Vamosi and David Angyal.

My contribution to this project was to construct and implement a signal processing

algorithm which produces the blood pressure values and the pulse values of a

2.4 Education of database programming
finding out how we can characterize the m


CareTaker のMRI下利用文献

Neural Control of Vascular Reactions: Impact of Emotion and Attention

Hadas Okon-Singer, Jan Mehnert, Jana Hoyer, Lydia Hellrung, Herma Lina Schaare, Juergen Dukart and Arno Villringer

Journal of Neuroscience 19 March 2014, 34 (12) 4251-4259; DOI: https://doi.org/10.1523/JNEUROSCI.0747-13.2014



This study investigated the neural regions involved in blood pressure reactions to negative stimuli and their possible modulation by attention. Twenty-four healthy human subjects (11 females; age = 24.75 ± 2.49 years) participated in an affective perceptual load task that manipulated attention to negative/neutral distractor pictures. fMRI data were collected simultaneously with continuous recording of peripheral arterial blood pressureCareTaker Emperical Technologies;. A parametric modulation analysis examined the impact of attention and emotion on the relation between neural activation and blood pressure reactivity during the task. When attention was available for processing the distractor pictures, negative pictures resulted in behavioral interference, neural activation in brain regions previously related to emotion, a transient decrease of blood pressure, and a positive correlation between blood pressure response and activation in a network including prefrontal and parietal regions, the amygdala, caudate, and mid-brain. These effects were modulated by attention; behavioral and neural responses to highly negative distractor pictures (compared with neutral pictures) were smaller or diminished, as was the negative blood pressure response when the central task involved high perceptual load. Furthermore, comparing high and low load revealed enhanced activation in frontoparietal regions implicated in attention control. Our results fit theories emphasizing the role of attention in the control of behavioral and neural reactions to irrelevant emotional distracting information. Our findings furthermore extend the function of attention to the control of autonomous reactions associated with negative emotions by showing altered blood pressure reactions to emotional stimuli, the latter being of potential clinical relevance.


Comparisons of microvascular and macrovascular changes in aldosteronism-related hypertension and essential hypertension

Monica Varano, Pierluigi Iacono,  Massimiliano M. Tedeschi,  Claudio Letizia,

Mario Curione,  Claudio Savoriti,  Erika Baiocco,  Laura Zinnamosca,

Cristiano Marinelli,  Barbara Boccassini  Mariacristina Parravano


Case-control observational study to evaluate the microvascular and macrovascular changes in patients with hypertension secondary to primary aldosteronism (PA), essential hypertension (EH) and healthy subjects. Measurements of arterial stiffness including augmentation index (AIx) and pulse wave velocity (PWV) were assessed using a TensioClinic arteriograph system. Retinal microcirculation was imaged by a Retinal Vessel Analyzer (RVA) and a non-midriatic camera (Topcon-TRC-NV2000). IMEDOS software analyzed the retinal artery diameter (RAD), retinal vein diameters (RVD) and arteriole-to-venule ratio (AVR) of the vessels coming off the optic disc. Thirty, 39 and 35 patients were included in the PA, EH and control group, respectively. The PA group showed higher PWV values compared only with the control group. The mean brachial and aortic AIx values did not show significant difference between groups. In the PA group, the mean RVD and AVR values were significantly lower than in the EH and control groups, whereas the parameters did not differ between the EH and control groups. In conclusion, AVR appears significantly modified in the PA group compared with the EH group and could represent an early and more reliable indicator of microvascular remodeling.


Abstract Case-control observational study to evaluate the microvascular and macrovascular changes in patients with hypertension secondary to primary aldosteronism (PA), essential hypertension (EH) and healthy subjects. Measurements of arterial stiffness including augmentation index (AIx) and pulse wave velocity (PWV) were assessed using a TensioClinic arteriograph system. Retinal microcirculation was imaged by a Retinal Vessel Analyzer (RVA) and a non-midriatic camera (Topcon-TRC-NV2000). IMEDOS software analyzed the retinal artery diameter (RAD), retinal vein diameters (RVD) and arteriole-to-venule ratio (AVR) of the vessels coming off the optic disc. Thirty, 39 and 35 patients were included in the PA, EH and control group, respectively. The PA group showed higher PWV values compared only with the control group. The mean brachial and aortic AIx values did not show significant difference between groups. In the PA group, the mean RVD and AVR values were significantly lower than in the EH and control groups, whereas the parameters did not differ between the EH and control groups. In conclusion, AVR appears significantly modified in the PA group compared with the EH group and could represent an early and more reliable indicator of microvascular remodeling.