Conference Program of WCICA 2012

Conference Program WCICA 2012
Automatic Sleep Stage Classification Based on ECG and EEG Features
for Day Time Short Nap Evaluation, pp.4974–4977
Yu, Shanshan
Chen, Xi
Wang, Bei
Wang, Xing-yu
East China Univ. of Sci. & Tech.
East China Univ. of Sci. & Tech.
East China Univ. of Sci. & Tech.
East China Univ. of Sci. & Tech.
In this study, the Electrocardiogram (ECG) and Electroencephalogram
(EEG) data recorded during day time short nap were analyzed. The ultimate
purpose is to find out effective ECG features combined with usual
EEG features for sleep stage determination during day time nap. Firstly,
the ECG data was pre-processed in order to eliminate artifacts. After
preprocessing, the second-order derivative of the ECG signal was calculated
and clustered into two classes by K-means method. The peak
positions of R wave were detected. Secondly, the Heart Rate Variability
(HRV) was calculated according to the RR intervals (RRIs). Features
of HRV of ECG were extracted in time-domain and frequency-domain.
The redundant features were removed by the rough set method. Finally,
the extracted features from the HRV of ECG were combined with the
usual EEG features for sleep stage determination. The sleep stages including
stage awake, stage 1 and stage 2 were distinguished by using
Support Vector Machine (SVM). The obtained result indicated that the
extracted ECG features improved the sleep stage classification accuracy.
◮ SuB05-2 16:10–16:30
Optimal Control in Molecular-level Gene Manipulation, pp.4978–4983
Yu, Juanyi
Li, Jr-Shin
Washington Univ. in St. Louis
Washington Univ. in St. Louis
The sequential information stored in DNA determines the appearance
and inheritance of different life forms and individuals. Precision control
of DNA sequences at the molecular level is crucial to maintain the fidelity
of genes and to ensure the accuracy of gene expression. In this
paper, we propose state-space control models at the molecular level
by converting character-based DNA sequences into state vectors and
incorporating on/off controls for mutagens into DNA replication systems
in different scales. Subsequently, we compute the optimal control
sequence for minimizing the risk of applying mutagens and the offtrajectory
penalty using dynamic programming algorithm. By the brute
force method and simulation results, we conclude that the global optimum
can always be achieved within a finite number of steps of deterministic
DNA replication systems. The upper limit of steps to reach the
global optimum depends on the length of the DNA sequence.
◮ SuB05-3 16:30–16:50
Multivariate Statistical Analysis Methods to Investigate Interindividual
Glucose Dynamics for Subjects with Type 1 Diabetes Mellitus, pp.4989–
4994
Zhao, Chunhui
Sun, Youxian
Gao, Furong
Zhejiang Univ.
Zhejiang Univ.
Hong Kong Univ. of Sci. & Tech.
This paper investigates the interindividual variability of underlying glucose
dynamics using multivariate statistical analysis methods for subjects
with type 1 diabetes mellitus. Here two types of glucose dynamics
are defined, the general dynamics and the output-relevant predictive
dynamics. The concerned important issues are whether the underlying
glucose dynamics change from subject to subject? Can a global
(or universal) empirical model be developed from glucose data for a s-
ingle subject and then used to explain the glucose dynamics for other
subjects? These and related issues are investigated using multivariate
statistical analysis methods based on clinical data for two groups
of subjects. Together, these findings provide insights into more efficient
development of data-driven models to understand and capture the glucose
information in diabetes subjects.
◮ SuB05-4 16:50–17:10
Dynamic Feature Extraction of Epileptic EEG Using Recurrence Quantification
Analysis, pp.5019–5022
Chen, Lanlan
East China Univ. of Sci. & Tech.
Zhang, Jian
Zou, Junzhong
East China Univ. of Sci. & Tech.
East China Univ. of Sci. & Tech.
Detecting the reliable transition point embedded in the electroencephalograms
(EEGs) is a challenge in the field of epileptic research.
In this research, a recurrence quantification analysis (RQA) is proposed
to help medical doctors to reveal dynamical characteristics in EEGs of
patients suffering from epilepsy. In contrast with traditional chaos methods,
the merits of RQA method is that it can measure the complexity
of a short and non-stationary signal without any assumptions such as
linear, stationary and noiseless noise. In this study, EEGs with generalized
epilepsy were collected in Epilepsy Center of Renji Hospital. The
test results show that three RQA measurements, i.e. recurrence rate,
determinism and entropy can track the complexity changes of brain
electrical activity. RQA variables show a large fluctuation in pre-ictal
stage, which reflects a transitional state leading to seizure activity. On
the contrary, RQA variables fluctuate in relatively small bounds in ictal
stage, which is due to organized and self-sustained rhythmic discharge.
Therefore, RQA could be a promising approach in prediction and diagnosis
for epileptic seizures.
◮ SuB05-5 17:10–17:30
Key-frame Selection in WCE Video Based on Shot Detection, pp.5030–
5034
Fu, Yanan
Liu, Haiying
Cheng, Yu
Yan, Tingfang
Li, Teng
Meng, Max, Q.-H.
shandong Univ.
Shandong Unversity
Shandong Univ.
Shandong Univ.
Shandong Univ.
The Chinese Univ. of Hong Kong
Wireless Capsule Endoscopy (WCE) is an imaging technology that enables
close examination of the interior of the entire small intestine. A
major problem associated with this new technology is that a large number
of images need to be manually examined by clinicians. It is therefore
useful to automatically reduce the number of frames that need direct
interpretation by a clinician. In this paper a technique based on
shot detection method is presented for automatic key-frame selection
in WCE videos. The frames in the small intestine zone containing relevant
features are extracted from the video sequence as the key-frames.
Experimental results show that the proposed key-frame selection techniques
significantly reduce the number of frames that need to
be directly viewed by clinicians, and speed up the diagnosis procedures.
◮ SuB05-6 17:30–17:50
Patient Data Tracking in a Collaborative Healthcare, pp.5045–5050
Memon, Qurban
Khoja, Shakeel
UAE Univ.
IBA, Pakistan
It has been found that patients do suffer from queuing at reception,
pharmacy, appointments, and services departments of the hospitals.
In this paper, patient tracking is presented such that it enables not only
presence of the patient within each service area of the hospital but
helps in retrieving relevant medical records of the patient from another
hospital within a collaborative health care domain. The architectural
challenges are investigated, and a framework for such a collaborative
region is presented. The patient record database is developed, technologies
are chosen and role based access for purpose of privacy is
exemplified for a typical environment. The issues related to its deployment
are also discussed.
SuB06 16:10–17:50 Room 302
Invited Session: Robot Sensing and Control
Chair: Liu, Yun-Hui
The Chinese Univ. of Hong Kong
◮ SuB06-1 16:10–16:30
Design of an Optimal Flight Control System with Integral Augmented
Compensator for a Nonlinear UAV Helicopter, pp.3927–3932
Tang, Yirui
Li, Yangmin
Univ. of Macau
Univ. of Macau
This paper presents the development of an optimal flight control system
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