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Automatic Ballistocardiogram (BCG) Beat Detection
Using a Template Matching Approach
30th Annual International IEEE EMBS Conference
Vancouver, British Columbia, Canada, August 20-24, 2008
J. H. Shin, B. H. Choi, Y. G. Lim, D. U. Jeong and K. S. Park
Adviser: Ji-Jer Huang
Presenter: Zhe-Lin Cai
Date:2014/12/24
Outline
 Introduction
 Method
 Result
 Discussion
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Introduction
Ballistocardiography (BCG)
―Cardiac and respiratory evaluation
―Non-invasive method
―Strength of myocardial contraction
―Condition of the heart
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Introduction
Ventricle contraction
―ECG Q-R-S complex
―BCG I-J-K complex
ECG, BCG principles
―ECG records the heart in nerve conduction arising from potential
changes graphics
―BCG defined as a method by which body vibrations caused by heart
activity are recorded
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Introduction
BCG:
―Advantages:
• Non-contact
• Non-conscious
• Security
―Disadvantages:
• Motion artifact signal
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Introduction
This paper suggests a beat detection method for
ballistocardiogram (BCG) from an unconstrained
cardiac signal monitoring devices
―The goal of the method is extraction of J peak without ECG
synchronization
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Photo Source : http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6421181
Introduction
The analyzed systems were Chee et al (2005) method using balancing
tube and air-mattress for unconstrained measurement system loadcell
type BCG measurement system and EMFi-film measurement system
were chosen
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Introduction
We applied template matching approach for BCG beat detection
algorithm to the three different types of BCG measurement system
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Method
The detection method is based on a “template matching” rule
evaluated using a correlation function in a local moving-window
procedure
Beat detection algorithm operates in two stages
― BCG template modeling
― Beat detection by Template Matching
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Method
BCG template modeling
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Method
BCG template modeling
―Bandpass filter
The bandpass filter which has 0.5~20Hz cutoff frequency was
applied to remove a respiration signal from raw signal
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Method
BCG template modeling
―The template bases were selected by the following criteria
 Clear to identify the I-J-K complexes
 Includes at least 10 BCG cycles
 Free from respiration effort signal and motion artifact signal
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Method
BCG template modeling
―Segmentation & verification
In the segmentation step, the selected template bases were split to
several BCG cycles and each cycle was verified by the expert
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Method
BCG template modeling
―Ensemble Average
And the cycles were normalized between -1 to 1. Finally, BCG
template was constructed by an ensemble averaging of the valid
BCG cycles centered at J peak points
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Method
Constructed BCG templates :
(a) Air-mattress system
(b) Loadcell system
(c) EMFi-film system
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Template matching illustration
Method
Beat detection by Template
Matching
―Template matching was
performed by local moving
window function which generates
correlation coefficient between the
constructed template in previous
modeling procedure and BCG
signal
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Method
𝑟𝑓,𝑔
𝑐𝑜𝑣(𝑓, 𝑔)
=
𝜎𝑓 𝜎𝑔
𝜎𝑓 =
𝑐𝑜𝑣(𝑓, 𝑓)
𝑇
𝑐𝑜𝑣(𝑓, 𝑔)
𝑓 𝑡 𝑔 𝑡 + 𝜏 𝑑𝜏
0
Photo Source : http://en.wikipedia.org/wiki/Convolution
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Result
Synchronized ECG was measured simultaneously for a
convenience of expert’s manual scoring of BCG J peaks
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Result
Sampling rate:
―Loadcell type BCG system: 200Hz
―Air-mattress type BCG systems:1KHz
―EMFi-film type BCG systems:1KHz
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Result
The template matching approach was
exercised in BCG signals to detect the
J-peak events
Detected J peaks marking with reversed
triangle in three BCG systems
―Air-mattress (upper)
―Loadcell
(middle)
―EMFi-film (lower)
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Result
The sensitivity is the detection screening probability of the
method
The positive predictivity value determines the capacity to
identify a true event
𝑻𝑷
𝑺ensitivity =
(𝑻𝑷 + 𝑭𝑵)
𝑻𝑷
Positive predictivity value =
(𝑻𝑷 + 𝑭𝑷)
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Result
We analyzed 10 subjects recorded during
resting and sleep. All subjects have
normal health condition and signal was
acquired in supine position with normal
breath. The subjects were recorded for 30
seconds and 5 records were analyzed in
each system
Result from air-mattress system and the
loadcell system shows a high
sensitivities and positive predictivity
values.
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Discussion
The template matching has an advantage with a simple and fast
algorithm, and be able a real-time process
Various template types can be useful in different measurement systems
and it is possible to register and classify multi-templates with patient
disease condition
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Discussion
Fixed template is not a universal set with wide variation of BCG shape
according to the change of measurement situations
In the further studies, we will apply the template matching approach to
classification of the beats with a cardiac disease and an automatic
template updating method to overcome the limitation of the fixed
template
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Thanks for your attention
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