Scientific Challenge

 

ICBHI 2019

Taipei, Taiwan, 17-20 April 2019

Welcome to the second edition of the Scientific Challenge Competition of the Int. Conf. on Biomedical and Health Informatics (ICBHI).

In this edition of the ICBHI Scientific Challenge, participants are asked to identify the main cardiac systolic time intervals, i.e., the pre-ejection period (PEP) and the left ventricle ejection time (LVET) using ECG and phonocardiogram (PCG) collected in a controlled clinical setting. The pre-ejection period is defined as the time interval between the ECG R-peak and the onset of the opening of the aortic valve (part of the S1 heart sound). The LVET is defined by the time span between the aortic valve opening and closing events. The latter usually corresponds to the onset of the S2 heart sound (see figure 1).

Figure 1. Cardiac time intervals in (left) normal heart and (right) heart with systolic heart failure. Legend: Ao – Aorta; LA – Left Atrium; LV – Left Ventricle; PEP – Pre-ejection period; LVET – Left ventricle ejection time (adapted from (Ross et al., 2006))

The relevance of the main systolic time intervals is related to the fact that myocardial relaxation and contraction are governed by intracellular recycling of calcium ions. The timings of these basic cardiac events are directly related to the health of the cardiac cells and determine the ability of the myocardium to achieve blood delivery according to the metabolic requirements of the organs. Of major importance are the systolic and diastolic timings of the left ventricle, since it is this ventricle’s function to insure the blood flow in the systemic circulation. In the mid 20th century PEP was studied extensively as a measure of cardiac systolic function, whereas LVET was applied as a surrogate of left ventricle stroke volume. A healthy heart exhibits a short PEP and a long ejection time, while myocardial dysfunction prolongs PEP and shortens LVET. This has led to the introduction of the PEP/LVET index to assess the systolic function of the heart. Indeed, a good and significant correlation between PEP/LVET and the left ventricle ejection fraction determined using angiography has been observed among patients with a wide variety of cardiovascular diseases. Furthermore, it was found that in patients with coronary artery disease, the PEP/LVET ratio is a highly reproducible measure that is equivalent in accuracy to the determination of the left ventricle ejection fraction. Despite the introduction of powerful and complete assessment tools of cardiac function such as the echocardiography, a significant interest in STI as a non-invasive tool for left ventricle function assessment persists in several contexts where portable, low intrusive and cheap solutions are imperative, such as in pHealth.

In order to develop solutions for the challenge, participants will have access to an annotated heart sound database containing snippets of about 30-120s of synchronously acquired heart sounds and ECG in clinical settings collected from healthy and patients with different cardiovascular disorders. Each test data set entry has information regarding beat-to-beat aortic valve events. The goal of this edition’s challenge is to develop a resilient and accurate solution to measure beat-to-beat PEP and LVET timings from heart sounds and ECG (see figure below).

Figure 2: Example of synchronously acquired ECG, PCG and echocardiography.

In order to participate as an individual or a collective team you should first register in order to be able to access the public annotated database of heart sounds and ECG made available for the challenge and to submit your entries to the challenge.

All official entries must be received no later than 12:00 GMT on the 20^th of February 2019. In the interest of fairness to all participants, late entries will not be accepted or scored.

To be eligible you must do all of the following:

1. Register: you should include the full name, email, and affiliation.
    
2. Submit at least one entry that can be scored during Phase I until the defined deadline (12:00 GMT, December 15, 2018). All submissions must be in Matlab and be self-contained (e.g. if some special open-source and non-standard toolbox is needed, then it has to be provided; all commercially available toolboxes from Mathworks for MATLAB R2015a are included). Please follow the detailed information on data formats, input and output formats provided in the sample files.
    
3. Submit an abstract (up to 1 page) describing your approach on the Scientific Challenge to ICBHI’ 19 no later than December 15, 2018.      

    

4. Submit a full paper describing your work for the Scientific Challenge following the ICBHI' 19 rules no later than February 1, 2019, using the regular submission system. Include the overall score for at least one Phase I or Phase II entry in your paper. You will be notified if your paper has been accepted by email from ICBHI’19 until February 10, 2019.
    
5. Paper final submission (4 pages) must be received no later than February 20, 2019.
    
6. Attend ICBHI'19 (April 17-20, 2019) and present your work there (at least one team member must be registered and attend ICBHI).

Lower score is better.

a) Challenge Data

The database was collected using synchronized phonocardiogram (PCG), photoplethysmogram (PPG) and electrocardiogram (ECG) as well as echocardiography (Doppler mode). The study was carried out with 68 volunteers in the “Centro Hospitalar da Universidade de Coimbra”, Coimbra, Portugal, which are divided into two distinct groups: one containing 33 healthy subjects and another with 35 subjects suffering from various cardiovascular diseases (CVDs), such as hypertension, arrhythmia, acute infarction, AV blocks (pacemaker), angina pectoris, heart failure, ischemia, aortic insufficiency, coronary artery disease and aortic stenosis.

During this study, the volunteers were requested to stay at the supine position, at rest and after exercise (the healthy subjects), while the ECG (MLII lead configuration), PPG (right hand index finger), PCG (LSB – left sternum border, and apex) and echocardiography (Doppler mode) were collected by an authorized medical specialist. The measurement protocol consisted on the acquisition of echocardiographic data during several runs (at least 4 consecutive runs of 8 seconds), during which the remaining bio-signals were synchronously recorded.

Using the echocardiographic measurements, a clinical technician manually annotated several cardiac parameters, such as the pre-ejection period and the left ventricular ejection time. The population was not balanced for gender (51 male and 17 female). The biometric characteristics of the population are (mean ± std):

Age: 29,72 ± 8,54 (Healthy subjects) and 58,97 ± 17,22 (CVD subjects) years

BMI: 24,48 ± 2,41 (Healthy subjects) and 25,38 ± 3,10 (CVD subjects) Kg/m2

Parameters

The parameters available in the data set, collected in a daily basis, are:

Time series:

• ECG – runs between ap. 8s (from ECHO) and 400s (from HP monitor)
• PPG – runs of ap. 400s
• PCG – runs of ap. 30s-120s
• Echocardiography – ap. 4-8 runs of 8 secs

b) Input/ouput formats

To enter the ICBHI challenge, the participants have to develop an algorithm that is able to read both the biosignals signals and the annotation files, providing as output the PEP and LVET measurements for each cardiac cycle, without any user interaction. The algorithm must be implemented in MATLAB. Each team must send the whole files in a compressed format (*.rar, *.zip, *.7z, or *.tar.gz) from your registered email account to icbhi2019.sc@gmail.com. The archive should contain the following files::

1. AUTHORS.txt, a plain text file listing the members of your team who contributed to your code, and their affiliations.
2. All the required code that is used for the analysis. This set of files must include a file with the name challenge.m, which is the entry file of the code and has one input: the name of the record.
3. Your code should output the file results_RecordName.txt, where RecordName is the name of the recording from training data set that was used for the analysis. Each text file should contain a N*2 vector, where N is the number of cardiac cycles in the recording. Row number i should correspond to the pair PEP_i and LVET_i measured in ms (mili-seconds).

We will run your code on the testing set and compare the contents of the results_RecordName.txt files that are generated with the ground-truth annotations of the health professionals. If everything runs as expected, you will get an email with the score of your submission.

In Phase I (Unofficial) your submissions will be tested on a subset of the testing set, while in Phase II (Official) they will be tested on the whole testing set. Thus, the grade for a specific algorithm may be different in each phase.

You can download the public set and the expected submission files as zip files.