No abstract

For good performance, most existing electrocardiogram (ECG) identification methods still need to adopt a denoising process to remove noise interference beforehand. This specific signal preprocessing technique requires great efforts for algorithm engineering and is usually complicated and time-consuming. To more conveniently remove the influence of noise interference and realize accurate identification, a novel temporal-frequency autoencoding based method is proposed. In particular, the raw data is firstly transformed into the wavelet domain, where multi-level time-frequency representation is achieved. Then, a prior knowledge-based feature selection is proposed and applied to the transformed data to discard noise components and retain identity-related information simultaneously. Afterward, the stacked sparse autoencoder is introduced to learn intrinsic discriminative features from the selected data, and Softmax classifier is used to perform the identification task. The effectiveness of the proposed method is evaluated on two public databases, namely, ECG-ID and Massachusetts Institute of Technology-Biotechnology arrhythmia (MIT-BIH-AHA) databases. Experimental results show that our method can achieve high multiple-heartbeat identification accuracies of 98.87%, 92.3%, and 96.82% on raw ECG signals which are from the ECG-ID (Two-recording), ECG-ID (All-recording), and MIT-BIH-AHA database, respectively, indicating that our method can provide an efficient way for ECG biometric identification.

Background Undergraduate dental basic research education (UDBRE) is broadly regarded as an important approach for cultivating scientific research talent. This scoping review aims to summarize the current status of UDBRE in terms of educational goals, teaching program and content, assessment system, training outcomes, barriers, and reflections. Methods The authors performed a systematic literature search in PubMed, Web of Science, and Education Resources Information Center (ERIC) to identify peer-reviewed articles written in English from their inception to January 29, 2021. Articles were reviewed and screened according to the inclusion and exclusion criteria. Related data from the included publications were then collected and summarized. Results The authors searched 646 publications and selected 16 articles to include in the study. The education goals included cultivating five major dental basic research capabilities (n=10, 62.5%) and developing interest in basic research (n=2, 12.5%). As for the teaching program, the mentor-guided student research project was the most popular (n=11, 68.8%), followed by didactic courses (n=5, 31.3%), experimental skills training (n=1, 6.3%), and the combination of the above forms (n=3, 18.8%). However, the assessment system and training outcome diverged. Existing evidence showed that UDBRE reached satisfying education outcomes. Barriers included excessive curriculum burden (n=2, 12.5%), tutor shortage (n=3, 18.8%), lack of financial support (n=5, 31.3%), and inadequate research skills and knowledge (n=5, 31.3%). Conclusions Although efforts were made, the variation between studies revealed the immature status of UDBRE. A practical UDBRE education system paradigm was put forward. Meanwhile, more research is required to optimize a robust UDBRE system with clear education goals, well-designed teaching forms, and convincing assessment systems.