automatic ballistocardiogram (bcg) beat detection using a template matching approach adviser: ji-jer...
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Automatic Ballistocardiogram (BCG) Beat DetectionUsing a Template Matching Approach
Adviser: Ji-Jer Huang
Presenter: Zhe-Lin Cai
Date:2014/12/24
30th Annual International IEEE EMBS ConferenceVancouver, British Columbia, Canada, August 20-24, 2008
J. H. Shin, B. H. Choi, Y. G. Lim, D. U. Jeong and K. S. Park
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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
Photo Source : http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6421181
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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
Photo Source : http://abrc.snu.ac.kr/korean/viewforum.php?f=172
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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
Photo Source : http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=6421181
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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 filterThe 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 & verificationIn 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 AverageAnd 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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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
Template matching illustration
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Method
𝑟 𝑓 ,𝑔=𝑐𝑜𝑣 ( 𝑓 ,𝑔)𝜎 𝑓 𝜎𝑔
𝑐𝑜𝑣 ( 𝑓 ,𝑔)❑⇒∫0
𝑇
𝑓 (𝑡 )𝑔 (𝑡+𝜏 )𝑑𝜏
𝜎 𝑓=√𝑐𝑜𝑣( 𝑓 , 𝑓 )
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
𝑺ensitivity = 𝑻𝑷
(𝑻𝑷+𝑭𝑵 )
P ositive predictivity value = 𝑻𝑷
(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