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  1. Raez MB, Hussain MS, Mohd-Yasin F
    Biol Proced Online, 2006;8:11-35.
    PMID: 16799694
    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications.
  2. Reaz MB, Hussain MS, Mohd-Yasin F
    Biol Proced Online, 2006;8:163.
    PMID: 19565309 DOI: 10.1251/bpo124
    This paper was originally published in Biological Procedures Online (BPO) on March 23, 2006. It was brought to the attention of the journal and authors that reference 74 was incorrect. The original citation for reference 74, "Stanford V. Biosignals offer potential for direct interfaces and health monitoring. Pervasive Computing, IEEE 2004; 3(1):99-103." should read "Costanza E, Inverso SA, Allen R. 'Toward Subtle Intimate Interfaces for Mobile Devices Using an EMG Controller' in Proc CHI2005, April 2005, Portland, OR, USA."
  3. Koh B, Sulaiman N, Ismadi SNSW, Ramli R, Yunus SSM, Idrus RBH, et al.
    Biol Proced Online, 2021 Sep 15;23(1):18.
    PMID: 34521356 DOI: 10.1186/s12575-021-00155-7
    BACKGROUND: In the area of oral and maxillofacial surgery, regenerative endodontics aims to present alternative options to conventional treatment strategies. With continuous advances in regenerative medicine, the source of cells used for pulp tissue regeneration is not only limited to mesenchymal stem cells as the non-mesenchymal stem cells have shown capabilities too. In this review, we are systematically assessing the recent findings on odontoblastic differentiation induction with scaffold and non-scaffold approaches.

    METHODS: A comprehensive search was conducted in Pubmed, and Scopus, and relevant studies published between 2015 and 2020 were selected following the PRISMA guideline. The main inclusion criteria were that articles must be revolving on method for osteoblast differentiation in vitro study. Therefore, in vivo and human or animal clinical studies were excluded. The search outcomes identified all articles containing the word "odontoblast", "differentiation", and "mesenchymal stem cell".

    RESULTS: The literature search identified 99 related studies, but only 11 articles met the inclusion criteria. These include 5 odontoblastic differentiation induction with scaffold, 6 inductions without scaffolds. The data collected were characterised into two main categories: type of cells undergo odontoblastic differentiation, and odontoblastic differentiation techniques using scaffolds or non-scaffold.

    CONCLUSION: Based on the data analysis, the scaffold-based odontoblastic induction method seems to be a better option compared to the non-scaffold method. In addition of that, the combination of growth factors in scaffold-based methods could possibly enhance the differentiation. Thus, further detailed studies are still required to understand the mechanism and the way to enhance odontoblastic differentiation.

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