{"title":"The Relationship Between Pulse Rate and Mandarin Tone Recognition: A Preliminary Study with CCi-Mobile Cochlear Implant Research Processor","authors":"Yefei Mo, Huali Zhou, Q. Meng, Peina Wu","doi":"10.1145/3543081.3543082","DOIUrl":"https://doi.org/10.1145/3543081.3543082","url":null,"abstract":"The aim of this study is to evaluate the effects of pulse rate (i.e., stimulation rate) on Mandarin tone recognition by cochlear implant users. Mandarin tone recognition was measured by using monosyllabic and disyllabic tone data-bases at three pulse rates in cochlear implant users. The three pulse rates included each participant's clinical default pulse rate (i.e., 900 or 1200 pulses per second (pps) for each electrode), 400 pps, and 200 pps. A real-time research speech processor, CCi-Mobile, was used to implement the signal processing strategies. Although the results are variable among participants, there was a trend that the recognition rates of both monosyllabic and disyllabic databases decreased with lower pulse rates, indicating that low pulse rates degrade acoustic cues, like periodicity, for Mandarin tone perception. This study also provided preliminary data for evaluating the CCi-Mobile research processor for the first time in China. The processor could be used for signal processing algorithm development and psychophysical experiments in the future.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116874465","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}
Lianyi Huo, Xuetao Shi, Xing Wang, Yuchen Yao, Yiwei Liu
{"title":"Development Trend of 3D Printing Bone Tissue Engineering Scaffold Based on Black Phosphorus Nanosheets","authors":"Lianyi Huo, Xuetao Shi, Xing Wang, Yuchen Yao, Yiwei Liu","doi":"10.1145/3543081.3543104","DOIUrl":"https://doi.org/10.1145/3543081.3543104","url":null,"abstract":"∗ With the increasingly serious problem of population aging, the number of patients with bone defects caused by degenerative dis-eases is gradually increasing, which has brought great pressure to the medical system of various countries. Bone tissue engineering scaffolds made of traditional biomaterials are easy to produce problems such as poor fit, wear and corrosion after repairing bone tissue, especially it is difficult to form bone tissue with biological function. In this paper, the research status of 3D printed bone tissue engineering scaffold technology based on black phosphorus nanosheets (BPNs) is deeply analyzed. It is considered that BPNs have unique advantages and development prospects compared with other traditional bone tissue scaffold materials (such as bioceramics and metal materials). The combination of BPNs and 3D-printed bone tissue engineering scaffolds can overcome the defects of traditional scaffold manufacturing methods and achieve a breakthrough in the personalized, accurate, mechanical strength, pore regulation and spatial structure complexity of scaffolds. This study provides a salutary lesson for the design of 3D printed bone tissue engineering scaffolds and the improvement of antibacterial and stability based on BPNs.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123800491","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":"PResearch on Biological Species Improvement Technology Based on Genetic Recombineering","authors":"Xuanting Li, Peize Zhao","doi":"10.1145/3543081.3543095","DOIUrl":"https://doi.org/10.1145/3543081.3543095","url":null,"abstract":"Gene recombination is an essential feature in biological evolution. Genetic recombination is an essential mode of species improvement in microorganisms, plants, and animals. A chromosome consists of a sequence of genes, and a genome is a collection of chromosomes. This paper uses computer signal recognition technology to discover DNA base sequences in gene recombination. Further, the paper uses a filtered deep learning algorithm to locate the starting fragment of gene recombination. In this way, the paper has a predictive model of genetic recombination. Finally, this paper uses the algorithm model to predict the genetic recombination fragments in biological species improvement. The research found that the algorithm's accuracy proposed in this paper is 98.5%.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134018950","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":"SVEM: A Signal Variation Elimination Model for EEG Emotion Recognition","authors":"Zhaohong Sun, Haomin Li, H. Duan","doi":"10.1145/3543081.3543085","DOIUrl":"https://doi.org/10.1145/3543081.3543085","url":null,"abstract":"Motivated by the non-stationarity characteristics of electroencephalograph (EEG) signals, we propose a signal variation elimination model (SVEM) for emotion recognition. The proposed SVEM enables to capture the topological structures of different EEG channels due to the utilized graph neural network (GNN). Two tricks are proposed to reduce signal variations and improve the model generalization. Firstly, the proposed SVEM is pre-trained by a mask-generation supervised learning where we randomly mask several signal channels in GNN and then generate them. Secondly, the proposed SVEM is fine-tuned by incorporating a domain classifier to reduce the distribution shift between the training and testing sets. To further reduce the subject signal variations of the training set, a subject classifier is incorporated in the fine-tuning process of SVEM. The performance of SVEM is evaluated on the real-world dataset SEED. Experiment results demonstrate that the accuracy of SVEM achieves 87% and 71%, on subject-dependent and subject-independent tasks, respectively.","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128876314","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":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","authors":"","doi":"10.1145/3543081","DOIUrl":"https://doi.org/10.1145/3543081","url":null,"abstract":"","PeriodicalId":432056,"journal":{"name":"Proceedings of the 6th International Conference on Biomedical Engineering and Applications","volume":"10 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":"128444949","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}