H. Guo, Yu-Shun Huang, Chien-Hung Lin, J. Chien, K. Haraikawa, J. Shieh
{"title":"Heart Rate Variability Signal Features for Emotion Recognition by Using Principal Component Analysis and Support Vectors Machine","authors":"H. Guo, Yu-Shun Huang, Chien-Hung Lin, J. Chien, K. Haraikawa, J. Shieh","doi":"10.1109/BIBE.2016.40","DOIUrl":"https://doi.org/10.1109/BIBE.2016.40","url":null,"abstract":"Emotion influences human health significantly. In this pilot study, a movie clips method has been designed to induce 5 kinds of emotion states. 90-sec corresponding ECG signal have been measured in the end of video stimulus. Heart rate variability (HRV) features were extracted from ECG signal by using time-domain, frequency-domain, Poincare, and statistic analysis. Then these HRV features were used to classify different emotion states by support vectors machine (SVM). Also, we used principal component analysis (PCA) to reduce the number of extracted features. Briefly, in the classification for 2 emotion states (positive/negative) and 5 kinds of emotion states, the accuracy of 71.4%, 56.9% are reached, respectively. Compared with other studies of emotion recognition using 2 or more vital signs, the accuracy in this study is lower slightly than other studies (56.9% versus 61.6%). However, using single ECG signal or HRV features is accessible for the daily emotion monitoring. Our results showed the feasibility of daily emotion monitoring by using extracted HRV features and SVM classifier.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132852779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Nozaki, H. Tamagawa, Chihiro Sugiyama, K. Nohara, Takayoshi Sakai, Kohei Hatanaka, Machiko Nakagawa, K. Satoh, M. Kariyasu, T. Yamashiro, M. Kogo
{"title":"Velopharyngeal Closure Function Strategy in Articulation: Mechanical Dynamics Modeling of Air Flow in the Vocal Tract","authors":"K. Nozaki, H. Tamagawa, Chihiro Sugiyama, K. Nohara, Takayoshi Sakai, Kohei Hatanaka, Machiko Nakagawa, K. Satoh, M. Kariyasu, T. Yamashiro, M. Kogo","doi":"10.1109/BIBE.2016.13","DOIUrl":"https://doi.org/10.1109/BIBE.2016.13","url":null,"abstract":"In this study, a numerical simulation of airflow while pronouncing a phrase /usuimisosiru/ with velopharyngeal closure based on cinematic volumetric data was performed. The results indicated that the air stream path was affected by the velopharyngeal closure. Principle morphological factors were selected to achieve articulation of the consonant, which was the constriction ratio of the velopharyngeal region and the narrowing of the oral cavity by the elevation of the tongue. The simplified velopharyngeal model was constructed based on the factors measured by using real morphological data. The results of the simulation using a simplified model indicated that a 20% and 30% constriction ratio of each region supplied the largest airflow magnitude from the nasal cavity and oral cavity.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116448069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Liu, Youbing Zhao, Hui Wei, S. Roumeliotis, E. Kaldoudi
{"title":"Navigating Health Literacy Using Interactive Data Visualisation","authors":"E. Liu, Youbing Zhao, Hui Wei, S. Roumeliotis, E. Kaldoudi","doi":"10.1109/BIBE.2016.56","DOIUrl":"https://doi.org/10.1109/BIBE.2016.56","url":null,"abstract":"It is commonly concluded that health literacy focuses on individual skills to obtain, process and understand health information and services necessary to make appropriate health decisions. To achieve this, an individual first needs to obtain an adequate level of health literacy. However, nowadays, the information that individuals encounter with regards to their health, the amount, credibility and quality of the data make it difficult for one to make judgments on their health and disease progression, let alone make informed decisions on behaviour change. In this paper, we will report our work in providing patients with efficient ways to explore and understand the relevant health literacy. We focus on two data types: 1) harvested medical evidence from PubMed on cardiorenal disease and its comorbidities, 2) data collected from patients including from PHR and wearable sensors. Our work provides ways for patients to visualise this data meaningfully. Our work aims to improve the health literacy for the general public and increase the population's understanding of the medical field, thus helping users to make informed decision with regards to their care.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122069779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Location-Aware Fall Detection System for Dementia Care on Nursing Service in Evergreen Inn of Jianan Hospital","authors":"Ping Wang, Chin-Shan Chen, Chi-Chi Chuan","doi":"10.1109/BIBE.2016.70","DOIUrl":"https://doi.org/10.1109/BIBE.2016.70","url":null,"abstract":"According to the Taiwan Alzheimer's Disease Association data released in April 2012, the domestic population of dementia increased annually. Especially, the estimated aging population increased from 248.6 million in 2010 to 784.4 million in 2060, i.e., approximately four persons in 100 have dementia. Thus the dementia care for the elderly became a problem. Recently several programs and subsidy cases were initiated to develop various telemedicine services and care information systems. Accordingly, the present study provides a safety monitoring platform for nursing care service with a wearable vest incorporating accelerometer-based fall detection and message notification service for the elderly with dementia to assist managers improve the care quality in Jianan Hospital. Especially, it aggregates the RFID real-time locating service (RTLS) with GIS (geographic information system) to enhance the precision of real-time accidental detection based on a body posture angle (BPA) measure approach by replacing the existing CCTV system for security monitoring of living area in Evergreen Inn. After the safety monitoring platform was deployed, experimental results showed it can improve the care safety for dementia patients in which the number of patient fall decreased 81% than that of the conventional CCTV monitoring system.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124361532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CRDT: Correlation Ratio Based Decision Tree Model for Healthcare Data Mining","authors":"Smita Roy, S. Mondal, Asif Ekbal, M. Desarkar","doi":"10.1109/BIBE.2016.21","DOIUrl":"https://doi.org/10.1109/BIBE.2016.21","url":null,"abstract":"The phenomenal growth in the healthcare data has inspired us in investigating robust and scalable models for data mining. For classification problems Information Gain(IG) based Decision Tree is one of the popular choices. However, depending upon the nature of the dataset, IG based Decision Tree may not always perform well as it prefers the attribute with more number of distinct values as the splitting attribute. Healthcare datasets generally have many attributes and each attribute generally has many distinct values. In this paper, we have tried to focus on this characteristics of the datasets while analysing the performance of our proposed approach which is a variant of Decision Tree model and uses the concept of Correlation Ratio(CR). Unlike IG based approach, this CR based approach has no biasness towards the attribute with more number of distinct values. We have applied our model on some benchmark healthcare datasets to show the effectiveness of the proposed technique.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"C-33 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114116560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiscale Meshfree Analysis of the Effects of Thermal Treatments on Deformability of Red Blood Cell Membrane","authors":"A. Ademiloye, Lu-Wen Zhang, K. Liew","doi":"10.1109/BIBE.2016.43","DOIUrl":"https://doi.org/10.1109/BIBE.2016.43","url":null,"abstract":"From temperature conditions in blood storage units to those observed in patients with severe thermal burns, it is obvious that the human blood cells are subjected to various temperature ranges and conditions during their lifespan. It is also known that temperature affects the ability of blood cell to transverse thin microcapillaries, although the extent remains unknown. In this study, we employed a three-dimensional (3D) nonlinear multiscale meshfree approach to investigate the effects of freezing and heating temperatures on the deformability of the human red blood cell (RBC). The optical tweezers experiment was numerically simulated in order to quantify the deformability of red blood cells as a function of the relationship between its deformed axial and transverse diameter. We observe that the deformability of red blood cell membrane decreases as temperature increases. It is concluded that increase in temperature leads to increase in membrane rigidity and decrease in overall membrane deformability, which may be due to the denaturation of RBC membrane underlying cytoskeleton protein.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132159078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}