Doppler ultrasound dataset for the development of automatic emboli detection algorithms

Abstract

The article describes a dataset of doppler ultrasound audio tracks taken on a sample of 30 divers according to the acquisition protocol defined by the Divers Alert Network. The audio tracks are accompanied by a medical evaluation for the decompression sickness risk according to the Spencer's scale levels. During the acquisition campaign, each diver in the post-dive phase was subjected to a double doppler ultrasound examination of approximately 45 seconds each one in the precordial area using a Huntleigh FD1 Fetal doppler probe. The two measurements were separated by a time of 8-10 seconds necessary for carrying out specific physical exercises designed to free the bubbles trapped in the tissues. The audio tracks were stored without compression via the TASCAM DP-004 recorder and processed in order to eliminate the noise generated by the positioning of the probe and the time interval between the two measurements. The audio tracks recorded during the acquisition campaign have been evaluated by experts belonging to three independent blind teams in order to provide an assessment of the decompression sickness risk according to Extended Spencer's scale. The specific typology of doppler ultrasound audio tracks and the associated medical evaluation according to the Spencer's scale levels make this dataset useful for the development, testing, and performance evaluation of new audio processing algorithms capable of automatically detecting bubbles in the blood vessels.

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Doppler ultrasound dataset for the development of automatic emboli detection
algorithms
Paola Pierleoni, Marco Mercuri, Alberto Belli, Massimo Pieri, Alessandro Marroni,
Lorenzo Palma
PII: S2352-3409(19)31094-7
DOI: https://doi.org/10.1016/j.dib.2019.104739
Reference: DIB 104739
To appear in: Data in Brief
Received Date: 5 September 2019
Revised Date: 7 October 2019
Accepted Date: 28 October 2019
Please cite this article as: P. Pierleoni, M. Mercuri, A. Belli, M. Pieri, A. Marroni, L. Palma, Doppler
ultrasound dataset for the development of automatic emboli detection algorithms, Data in Brief, https://
doi.org/10.1016/j.dib.2019.104739.
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Article Title
Doppler ultrasound dataset for the development of automatic emboli detection algorithms
Authors
Paola Pierleoni
1
, Marco Mercuri
1
, Alberto Belli
1
, Massimo Pieri
2
, Alessandro Marroni
2
, Lorenzo Palma
1
Affiliations
1. Department of Information Engineering, Università Politecnica delle Marche, Via Brecce Bianche
12, 60131 Ancona, Italy;
2. DAN Europe Foundation Research Division, Sir Ugo Mifsud Street, XBX 1431 Ta’ Xbiex, Malta.
Corresponding author(s)
Lorenzo Palma: l.palma@univpm.it; Tel.: +39-071-220-4847;
Marco Mercuri: mrc.mercuri@gmail.com .
Abstract
The article describes a dataset of doppler ultrasound audio tracks taken on a sample of 30 divers
according to the acquisition protocol defined by the Divers Alert Network. The audio tracks are
accompanied by a medical evaluation for the decompression sickness risk according to the Spencer's
scale levels.
During the acquisition campaign, each diver in the post-dive phase was subjected to a double doppler
ultrasound examination of approximately 45 seconds each one in the precordial area using a Huntleigh
FD1 Fetal doppler probe. The two measurements were separated by a time of 8-10 seconds necessary
for carrying out specific physical exercises designed to free the bubbles trapped in the tissues. The audio
tracks were stored without compression via the TASCAM DP-004 recorder and processed in order to
eliminate the noise generated by the positioning of the probe and the time interval between the two
measurements.
The audio tracks recorded during the acquisition campaign have been evaluated by experts belonging to
three independent blind teams in order to provide an assessment of the decompression sickness risk
according to Extended Spencer’s scale. The specific typology of doppler ultrasound audio tracks and the
associated medical evaluation according to the Spencer’s scale levels make this dataset useful for the
development, testing, and performance evaluation of new audio processing algorithms capable of
automatically detecting bubbles in the blood vessels.
Keywords
Embolic detection, decompression sickness, bubble detection, doppler ultrasound automatic analysis.

Specifications Table
Subject
Electrical
and
Electronic
Engineering
Specific
subject
area
Audio
signal
processing
for
embolic
detection
Type
of
data
Audio
wave
(.WAV)
files
Text file
How
data
were
acquired
Doppler
probe
(FD1
2
-
MHz,
Huntleigh
Ltd,
Cardiff,
UK)
Digital recorder (Tascam DP-004; TEAC America Inc., Montebello, CA,
USA)
Data
format
Raw
,
Filtered
and
analyzed
Parameters
for
data
collection
The
subjects
involved
in
the
dataset
were
30
professionals
and
amateurs
scuba divers (18 males and 12 women), aged between 25 and 65 years.
Doppler ultrasound acquisitions were performed in the divers about 35
minutes after surfacing. Diving activities were carried out in the Maldives
and Madagascar area. All participants who volunteered gave their
informed consent before each acquisition.
Description
of
data
collection
The
ultrasound
doppler
signals
were
acquired
in
the
precordial
area
with
two consecutive measurements of about 45 seconds each interspersed
with about 10 seconds of motor activity to free the bubbles trapped in
the tissues. The audio tracks once acquired have been filtered eliminating
a few seconds at the beginning and at the end of the entire recording and
the interval between the two measurements in order to reduce the
unwanted noise due to doppler probe positioning. For each acquisition an
assessment of the circulating bubbles according to the extended Spencer
scale has been provided by experts.
Data
source
location
Department
of
Information
Eng
i
neering,
Università
Politecnica
delle
Marche, Ancona, Italy

Data
accessibility
With
the
article
Related
research
article
Paola Pierleoni, Lorenzo Palma, Alberto Belli, Massimo Pieri, Lorenzo
Maurizi, Marco Pellegrini and Alessandro Marroni
“An EMD-Based Algorithm for Emboli Detection in Echo Doppler Audio
Signals”
Electronics
https://doi.org/10.3390/electronics8080824 [1]
Value of the Data
• Data are useful to develop and test new audio processing algorithms for emboli events
detection and evaluation of the decompression sickness risk level.
• Researchers and developers who want to implement systems for emboli detection using doppler
ultrasound acquisition;
• Data can be used as a benchmark for performance evaluations of different algorithms able to
automatically detect gas bubbles in blood vessels;
• In addition to the previously introduced values, this dataset is the only one that provides
doppler ultrasound acquisitions accompanied by medical evaluation for sickness risk according
to the Spencer’s scale;
• Dataset could be exploited for teaching to operators on how to evaluate a doppler ultrasound
track accordingly to Spencer's scale levels.

Data
The proposed dataset provides a complete set of Doppler Ultrasound (DU) audio tracks acquired
from scuba divers after the emersion. Each DU audio track was evaluated by experts in order to assess
the decompression sickness risk according to the Extended Spencer’s scale (ESS) [2].
The dataset is contained in Dataset_DU.zip file accessible as a supplementary file of this article.
Within Dataset_DU.zip, data are organized in one main directory, Dataset_DU, containing the DU audio
tracks and a file Eval.txt. The Eval.txt file contains a table which provides the level of the ESS associated
with each DU audio track. In Eval.txt file the first column indicates the file number (X) of the DU audio
track and the second indicates the relative level of the Extended Spencer’s scale. The analysis and the
subsequent evaluation according to the ESS was conducted by DAN medical staff.
Each DU audio track is a WAVEform audio file format called DU_X.wav, where X=1, 2, …, 30
indicates the file number. Table 1 shows the number of DU audio tracks contained in the dataset for
each Spencer
level:
Table 1
ESS
Level
0
0,5
1
1,5
2,5
Number of
tracks
9 6 10 3 2
Experimental Design, Materials, and Methods
The data of the proposed dataset were acquired based on the guidelines defined in the acquisition
protocol set by the Divers Alert Network (DAN) [3] which defines the precordial region as the optimal
zone of the human body for the detection of bubbles in the blood vessels [4]. In fact, numerous studies
have shown that this region, although affected by cardiac noise that can be eliminated through signal
processing algorithms [5,6,7], allows to obtain a complete evaluation of all the bubbles present in the
blood vessel.
The protocol also defines the exact acquisition procedure to follow in order to obtain an overall
analysis of the bubble situation of each diver. The protocol provides for alternating measurements in the
precordial zone with a series of exercises to free the bubbles entrapped in the tissues. The exercises
defined by the DAN medical team, are 2/3 folds on the legs, repeated a few times and performed freely
according to the scuba divers' abilities and physical conditions, all to avoid endangering the person's
health.
The acquisition procedure of the protocol starts approximately 35 minutes after scuba diver
emersion in order to allow the formation of bubbles. In fact, according to some studies [8], the peak
time for release of the bubbles is between 30 min and 60 min after surfacing. It consists of three
consecutive phases:

• 45 seconds during which a measurement of the doppler signal of blood vessels in the precordial
is performed;
• 8 - 10 seconds in where the scuba diver performs the series of exercises;
• 45 seconds during which a measurement of the doppler signal of blood vessels in the precordial
is performed;
According to the previous protocol DU audio tracks were collected in a specific acquisition
campaign which was conducted on 30 scuba divers (60% male and 40% female) between professionals
and amateurs, aged between 25 and 65 years during the diving activities in the Maldives and
Madagascar. The audio tracks presented were collected through a Huntleigh FD1 Fetal Doppler with 2
MHz probe (FD1, Huntleigh Ltd., Cardiff, UK) and a digital recorder (Tascam DP-004, TEAC America Inc.,
Santa Fe Springs, California, USA) which does not compress audio files and uses a linear pulse code
modulation (LPCM) format for data storage. Moreover, great care has been taken in adjusting the input
signal of the recorder to a level that avoids audio saturation because it could irreparably compromise
the recorded file. It was decided to process the audio tracks in order to eliminate any unwanted noise
generated by the doppler probe positioning during the initial and final phase of the measurement, as
well as in the interval between the two acquisitions. For this reason, at the beginning and at the end of
the recording 1-2 seconds of acquisition were cut, but also the whole interval between the two
measurements.
The dataset provided also presents an evaluation of the decompression sickness risk which was
performed by experts belonging to three independent blind teams. The DU audio tracks of the proposed
dataset were evaluated by each blind team that provide file’s annotations report containing the number
of embolic event and the corresponding Extended Spencer’s scale level. The level of the ESS indicated in
this dataset was derived from a subsequent analysis of the file’s annotations reports carried out by DAN
medical staff.
Acknowledgments
The authors would like to thank the Divers Alert Network Europe Foundation for their contribution in
data acquisition and research activities.
References
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Based Algorithm for Emboli Detection in Echo Doppler Audio Signals. Electronics 2019, 8, 824.
https://doi.org/10.3390/electronics8080824
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