ECS Sensors Plus最新文献

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Challenges and Opportunities for Developing Electrochemical Biosensors with Commercialization Potential in the Point-of-Care Diagnostics Market 开发具有商业化潜力的医疗点诊断市场电化学生物传感器的挑战与机遇
ECS Sensors Plus Pub Date : 2024-03-05 DOI: 10.1149/2754-2726/ad304a
Amir Ali Akhlaghi, Harmanjit Kaur, Bal-Ram Adhikari, L. Soleymani
{"title":"Challenges and Opportunities for Developing Electrochemical Biosensors with Commercialization Potential in the Point-of-Care Diagnostics Market","authors":"Amir Ali Akhlaghi, Harmanjit Kaur, Bal-Ram Adhikari, L. Soleymani","doi":"10.1149/2754-2726/ad304a","DOIUrl":"https://doi.org/10.1149/2754-2726/ad304a","url":null,"abstract":"\u0000 There is a plethora of electrochemical biosensors developed for ultrasensitive detection of clinically-relevant biomarkers. However, many of these systems lose their performance in heterogeneous clinical samples and are too complex to be operated by end users at the point-of-care (POC), prohibiting their commercial success. Integration of biosensors with sample processing technology addresses both of these challenges; however, it adds to the manufacturing complexity and the overall cost of these systems. Herein, we review the different components of a biosensor and avenues for creating fully-integrated systems. In the context of integration, we focus on discussing the trade-offs between sensing performance, cost, and scalable manufacturing to guide the readers toward designing new electrochemical biosensors with commercialization potential.","PeriodicalId":505590,"journal":{"name":"ECS Sensors Plus","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140263755","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}
引用次数: 0
HGSSA-bi LSTM: A Secure Multimodal Biometric Sensing Using Optimized Bi-Directional Long Short-Term Memory with Self-Attention HGSSA-bi LSTM:使用具有自注意功能的优化双向长短时记忆的安全多模态生物识别传感技术
ECS Sensors Plus Pub Date : 2024-01-04 DOI: 10.1149/2754-2726/ad1b3a
Juhi Priyani, Pankaj Nanglia, Paramjit Singh, Vikrant Shokeen, Anshu Sharma
{"title":"HGSSA-bi LSTM: A Secure Multimodal Biometric Sensing Using Optimized Bi-Directional Long Short-Term Memory with Self-Attention","authors":"Juhi Priyani, Pankaj Nanglia, Paramjit Singh, Vikrant Shokeen, Anshu Sharma","doi":"10.1149/2754-2726/ad1b3a","DOIUrl":"https://doi.org/10.1149/2754-2726/ad1b3a","url":null,"abstract":"\u0000 Biometric sensing technology has become a frequent element of everyday life as a result of the global demand for information security and safety legislation. In recent years, multimodal biometrics technology has become increasingly popular due to its ability to overcome the shortcomings of unimodal biometric systems. A hunger game search self-attention based Bi-LSTM model (HGSSA-Bi LSTM, Bi-directional long short-term memory) modal is presented in this paper for multimodal biometric identification. For removal of noise (unwanted) the pre-processing stage is used in the initial stage. An extended cascaded filter (ECF) is used with a combination of median and wiener filter in the pre-processing stage. Then, using the CNN model, feature extraction is utilized to extract features from the processed images. After feature extraction, fusing of feature is used with the aid of discriminant correlation analysis (DCA). Finally, the recognition process is performed by using the novel optimized HGSSA-Bi LSTM. The obtained outcome for the developed model is finally compared with other previous approaches such as CNN, RNN, DNN, and autoencoder models and the calculated performance based on accuracy 98.5%, precision 98%, F1-score 97.5%, sensitivity 98.5%, and specificity 99% accordingly.","PeriodicalId":505590,"journal":{"name":"ECS Sensors Plus","volume":"59 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139384873","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}
引用次数: 0
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