Bio-Medical Materials and Engineering - Volume 26, issue s1

Authors: Xia, Yong | Han, Junze | Wang, Kuanquan

Article Type: Research Article

Abstract: Based on the idea of telemedicine, 24-hour uninterrupted monitoring on electrocardiograms (ECG) has started to be implemented. To create an intelligent ECG monitoring system, an efficient and quick detection algorithm for the characteristic waveforms is needed. This paper aims to give a quick and effective method for detecting QRS-complexes and R-waves in ECGs. The real ECG signal from the MIT-BIH Arrhythmia Database is used for the performance evaluation. The method proposed combined a wavelet transform and the K-means clustering algorithm. A wavelet transform is adopted in the data analysis and preprocessing. Then, based on the slope information of the filtered …data, a segmented K-means clustering method is adopted to detect the QRS region. Detection of the R-peak is based on comparing the local amplitudes in each QRS region, which is different from other approaches, and the time cost of R-wave detection is reduced. Of the tested 8 records (total 18201 beats) from the MIT-BIH Arrhythmia Database, an average R-peak detection sensitivity of 99.72 and a positive predictive value of 99.80% are gained; the average time consumed detecting a 30-min original signal is 5.78s, which is competitive with other methods. Show more

Keywords: ECG, detection of QRS-complex and R-wave, wavelet transform, k-means clustering

DOI: 10.3233/BME-151402

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1059-S1065, 2015

Authors: Li, Yifeng | Zhang, Lihui | Li, Baohui | Wei, Xiaoyang | Yan, Guiding | Geng, Xichen | Jin, Zhao | Xu, Yan | Wang, Haixia | Liu, Xiaoyan | Lin, Rong | Wang, Quan

Article Type: Research Article

Abstract: This paper briefly describes the basic principle of wavelet packet analysis, and on this basis introduces the general principle of wavelet packet transformation for signal den-noising. The dynamic EEG data under +Gz acceleration is made a de-noising treatment by using wavelet packet transformation, and the de-noising effects with different thresholds are made a comparison. The study verifies the validity and application value of wavelet packet threshold method for the de-noising of dynamic EEG data under +Gz acceleration.

Keywords: Wavelet packet, EEG, threshold, de-noising

DOI: 10.3233/BME-151403

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1067-S1075, 2015

Authors: Moreno-Alsasua, L. | Garcia-Zapirain, B. | Mendez-Zorrilla, A.

Article Type: Research Article

Abstract: This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the …level of a person’s rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient. Show more

Keywords: EOG, GSR, AS, body temperature, sleep quality, processing

DOI: 10.3233/BME-151404

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1077-S1085, 2015

Authors: Shin, Seung-Won | Kim, Kyeong-Seop | Song, Chul-Gyu | Lee, Jeong-Whan | Kim, Jeong-Hwan | Jeung, Gyeo-Wun

Article Type: Research Article

Abstract: The very first step to process electrocardiogram (ECG) signal is to eliminate baseline wandering interference that is usually caused by electrode-skin impedance mismatch, motion artifacts due to a patient’s body moment or respiratory breathing. A new method is thus suggested to remove baseline wandering in ECG by improving the detrending method that was originally proposed for eliminating slow non-stationary trends from heart rate variability (HRV). In our proposed method, a global trend is estimated in terms of baseline wandering by merging the local trend based on an ECG segment that represents a part of the ECG signal. The experimental results …show that the improved detrending method can efficiently resolve baseline wandering without distorting any morphological characteristic embedded in the ECG signal in no time delay manner. Show more

Keywords: Electrocardiogram (ECG), baseline wandering, detrending, heart rate variability (HRV), high-pass filter

DOI: 10.3233/BME-151405

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1087-S1093, 2015

Authors: Yin, Hong | Zhu, Xiaoqian | Ma, Shaodong | Yang, Shuqiang | Chen, Liqian

Article Type: Research Article

Abstract: The heart sound signal is a reflection of heart and vascular system motion. Long-term continuous electrocardiogram (ECG) contains important information which can be helpful to prevent heart failure. A single piece of a long-term ECG recording usually consists of more than one hundred thousand data points in length, making it difficult to derive hidden features that may be reflected through dynamic ECG monitoring, which is also very time-consuming to analyze. In this paper, a Dynamic Time Warping based on MapReduce (MRDTW) is proposed to make prognoses of possible lesions in patients. Through comparison of a real-time ECG of a patient …with the reference sets of normal and problematic cardiac waveforms, the experimental results reveal that our approach not only retains high accuracy, but also greatly improves the efficiency of the similarity measure in dynamic ECG series. Show more

Keywords: Similarity, DTW, ECG series, MapReduce, parallel

DOI: 10.3233/BME-151406

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1095-S1105, 2015

Authors: Wang, Niannian | Zhang, Li | Liu, Guozhong

Article Type: Research Article

Abstract: Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest …path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders. Show more

Keywords: EEG, brain function network, small-word property, cognitive memory

DOI: 10.3233/BME-151407

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1107-S1114, 2015

Authors: Li, Yan | Chen, Yuanyuan | Lv, Xiaoning | Yang, Yang | Li, Jing | Hao, Chenru | Li, Minggao | Pu, Fang

Article Type: Research Article

Abstract: Unrecognized spatial disorientation (SD) which is intimately linked with brain cognitive function is always a fatal issue for the safety of pilots. To explore its effects on human brain cognitive functions, electroencephalography (EEG) functional network analysis methods were adopted to examine topological changes in the connection of cognitive regions when experiencing unrecognized SD. Twelve male pilots participated in the study. They were subjected to a SD scene, namely visual rotation, which evoked unrecognized SD. For the main EEG frequency intervals, the phase lag index (PLI) and normalized mutual information (NMI) were calculated to quantify the EEG data. Then weighted connectivity …networks were constructed and their properties were characterized in terms of an average clustering coefficient and global efficiency. A T-test was performed to compare PLI, NMI and network measures under unrecognized SD and non-SD conditions. It indicated a weak functional connectivity level in the theta band under unrecognized SD based on the significant decrease of mean values of PLI and NMI (p<0.05). Meanwhile, both the average clustering coefficient and global efficiency in the theta band reduced under the unrecognized SD condition. The decrease of the average clustering coefficient and global efficiency demonstrates a lack of small-world characteristics and a decline in processing efficiency of brain cognitive regions. All the experimental results show that unrecognized SD may have a negative effect on brain functional networks in the theta band. Show more

Keywords: Unrecognized spatial disorientation, cognitive function, EEG, network

DOI: 10.3233/BME-151408

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1115-S1124, 2015

Authors: Yu, Weiwei | Feng, Huashan | Feng, Yangyang | Madani, Kurosh | Sabourin, Christophe

Article Type: Research Article

Abstract: Motor imagery EEG-based BCI has advantages in the assistance of human control of peripheral devices, such as the mobile robot or wheelchair, because the subject is not exposed to any stimulation and suffers no risk of fatigue. However, the intensive training necessary to recognize the numerous classes of data makes it hard to control these nonholonomic mobile systems accurately and effectively. This paper proposes a new approach which combines motor imagery EEG with the Adaptive Neural Fuzzy Inference System. This approach fuses the intelligence of humans based on motor imagery EEG with the precise capabilities of a mobile system based …on ANFIS. This approach realizes a multi-level control, which makes the nonholonomic mobile system highly controllably without stopping or relying on sensor information. Also, because the ANFIS controller can be trained while performing the control task, control accuracy and efficiency is increased for the user. Experimental results of the nonholonomic mobile robot verify the effectiveness of this approach. Show more

Keywords: BCI, motor imagery EEG, ANFIS, nonholonomic mobile system

DOI: 10.3233/BME-151409

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1125-S1133, 2015

Authors: Wang, Gang | Shepherd, Simon J. | Beggs, Clive B. | Rao, Nini | Zhang, Ying

Article Type: Research Article

Abstract: The use of electroencephalograms (EEGs) to diagnose and analyses Alzheimer’s disease (AD) has received much attention in recent years. The sample entropy (SE) has been widely applied to the diagnosis of AD. In our study, nine EEGs from 21 scalp electrodes in 3 AD patients and 9 EEGs from 3 age-matched controls are recorded. The calculations show that the kurtoses of the AD patients’ EEG are positive and much higher than that of the controls. This finding encourages us to introduce a kurtosis-based de-noising method. The 21-electrode EEG is first decomposed using independent component analysis (ICA), and second sort them …using their kurtoses in ascending order. Finally, the subspace of EEG signal using back projection of only the last five components is reconstructed. SE will be calculated after the above de-noising preprocess. The classifications show that this method can significantly improve the accuracy of SE-based diagnosis. The kurtosis analysis of EEG may contribute to increasing the understanding of brain dysfunction in AD in a statistical way. Show more

Keywords: Electroencephalogram (EEG), Alzheimer’s disease (AD), kurtosis, sample entropy (SE)

DOI: 10.3233/BME-151410

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1135-S1148, 2015

Authors: Li, Hui | Peng, Cheng | Ye, Datian

Article Type: Research Article

Abstract: In this paper we report a detection method for different sleep stages and it is based on a single-channel electroencephalogram (EEG) system. The system is simple and can be easily setup in homes to perform sleep EEG recording, overnight sleep EEG automatic staging, and sleep quality evaluation. EEG data of 14 sleeping subjects were recorded through the entire night. All subjects were within the age group of 20-30 years and having no significant sleep disorders. To analyze the EEG data, it is segmented into equal time intervals. This is followed by calculation of Sample Entropy (SampEn) for each section, and …the SampEn’s statistical characteristics, such as the median, upper quartile, lower quartile and inter-quartile range. The sleep data were divided into training group (7 cases) and test group (7 cases). Sleep stages’ quantitative ranges of training group referring to ZEO results were extracted and the quantization range used to sleep staging EEG data. Both the training group and test group results were close to ZEO results. It suggested that the statistical characteristics of Sample Entropy could be used as a criterion for sleep staging and evaluation. Show more

Keywords: Electroencephalogram (EEG), sleep staging, sample entropy (SampEn), median, inter-quartile range (IQR)

DOI: 10.3233/BME-151411

Citation: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1149-S1156, 2015