Kaur Manvinder, Mathur Shilpi, Bhatia Dinesh, Verma Suresh
Department of Biomedical Engineering, Deenbandhu Chhotu Ram University of Science & Technology , Murthal-131039, Haryana , India .
J Med Eng Technol. 2015 Jan;39(1):19-25. doi: 10.3109/03091902.2014.973615. Epub 2014 Nov 11.
Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.
代表肌肉电活动的肌电图（EMG）信号可用于各种临床和生物医学应用。这些信号复杂且变化很大，取决于肌肉的解剖位置和生理特性。从肌肉获取的EMG信号需要先进的检测、分解和处理方法。本文提出了一种在MATLAB中开发的新型图形用户界面（GUI）siGnum，它将应用高效有效的技术来处理原始EMG信号，并以更简单的方式对其进行分解。通过使用部署工具，它可以独立于MATLAB软件使用。这将使研究人员能够更好地理解EMG信号及其分析程序，以便在不久的将来用于更强大、灵活和高效的应用。
