Jongsook Sanguantrakul, Nattawat Soontreekulpong, T. Trakoolwilaiwan, Y. Wongsawat
{"title":"Analysis of Walking Movement Using EEG for the Lower-Limb Paralysis","authors":"Jongsook Sanguantrakul, Nattawat Soontreekulpong, T. Trakoolwilaiwan, Y. Wongsawat","doi":"10.1109/BMEiCON47515.2019.8990321","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990321","url":null,"abstract":"The relationship between brain activity and lower-limb movement has been investigated for several decades. Due to brain activity, the motor cortex area has been represented for the movement controlled by the brain including pattern generation and adaptation. One of the techniques, Brain-computer Interface (BCI), has been developed which makes people interacted with computers to command devices or their bodies using their thought. This work aims to analyze brain signals of walking movement imagine and to reduce the number of EEG channels for lower-limb activity thinking. Each participant has participated in this work for 2 parts (idle and walking movement imagine part) on the same date. At first, all participants were started with idle part and the next is walking movement imagine part for every day of the experiment. The participants were asked to report their general information and acquired a brief protocol about the experiment. The significant differences indicated that changes in alpha and beta activity in the central region are varied for imagining each activity, which has been related to dominant middle activity in the center on the front region. Especially, the change of absolute power of both alpha and beta power activity in the left central area during imagine turn right. The variation of alpha and beta EEG wave is affecting to imagine walking movement. This work has also reduced the channels of EEG for the lower-limb activity of human beings to 4 channels.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123751183","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":"Controlled Release of Dual Antibacterial Drug from Composite Hydrogels","authors":"Pitirat Pholpabu, Pattira Somharnwong, Nattathida Huaybun, Chanatip Cherdbaramee, Vichapas Boonpasart, Lakkhanabut Komchum, Achiya Phuengsap","doi":"10.1109/BMEiCON47515.2019.8990291","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990291","url":null,"abstract":"Hydrogels with a controlled release of dual antibacterial drug have been developed to effectively prevent bacterial infections for biomedical applications. The synergistic dual drug aims to fight against drug resistant bacteria, which become more commonly found nowadays. In this study, we fabricated composite hydrogels using calcium carbonate microspheres as drug carriers to load a combination of tetracycline and ampicillin into the matrices for controlled drug release. The composite hydrogels were prepared using three different molar ratios between polymers and crosslinkers to investigate the effect of crosslink density on the physical properties and drug release. The drug release profiles were quantitatively analyzed to compare diffusivity and release mechanism. The results revealed that the crosslinker molar ratio influenced not only the physical properties, but also the drug release rate and mechanism. The different release characteristics of the drugs also suggested chemical interactions between the calcium carbonate microspheres and the small molecules. Such insight could assist designing of composite hydrogels for controlled dual drug release in biomedical applications.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"24 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708594","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}
Chanin Lochotinunt, Nattasasi Suwanpathumlert, Nattachai Masawat, S. Airphaiboon, C. Pintavirooj
{"title":"Neurofeedback System","authors":"Chanin Lochotinunt, Nattasasi Suwanpathumlert, Nattachai Masawat, S. Airphaiboon, C. Pintavirooj","doi":"10.1109/BMEiCON47515.2019.8990224","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990224","url":null,"abstract":"Nowadays, reading is one of the essential factors in learning. However, there are problems which make reading ineffective or time-wasting on comprehending the points read. The most efficient method to read is associated with our concentration. Practicing concentration allows us to control this factor. In this study, neurofeedback is applied in this situation together with the Neurosky Mindset measuring Electroencephalogram (EEG) to indicate the concentration level by the lamp which connects to the Arduino board informing the user about their state of concentration from the output. The output illustrates that the light will dim when the concentration level drops below the threshold. Making lamp's light brighter, you need to adjust your concentration level to be higher than a threshold. Moreover, the concentration level output will be demonstrated on the smartphone application.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124716110","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":"Drowsiness Detection for Office-based Workload with Mouse and Keyboard Data","authors":"Sanurak Natnithikarat, Sirakorn Lamyai, Pitshaporn Leelaarporn, Narin Kunaseth, Phairot Autthasan, Thayakorn Wisutthisen, Theerawit Wilaiprasitporn","doi":"10.1109/BMEiCON47515.2019.8990236","DOIUrl":"https://doi.org/10.1109/BMEiCON47515.2019.8990236","url":null,"abstract":"Non-invasive devices involved in the detection of drowsiness generally include infrared camera and Electroencephalography (EEG), of which sometimes are constrained in an actual real-life scenario deployments and implementations such as in the working office environment. This study proposes a combination using the biometric features of keyboard and mouse movements and eye tracking during an office-based tasks to detect and evaluate drowsiness according to the self-report Karolinska sleepiness scale (KSS) questionnaire. Using machine learning models, the results demonstrate a correlation between the predicted KSS from the biometrics and the actual KSS from the user input, indicating the feasibility of evaluating the office workers’ drowsiness level of the proposed approach.","PeriodicalId":213939,"journal":{"name":"2019 12th Biomedical Engineering International Conference (BMEiCON)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123665565","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}