فشرده‌سازی سیگنال‌های الکترومایوگرام مبتنی بر تقریب به کمک تجزیه حالت تجربی و هموارسازی به کمک تبدیل DCT

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی برق و رباتیک، دانشگاه صنعتی شاهرود، شاهرود، ایران

چکیده

سیگنال‌های الکترومایوگرام (EMG) ابزار مفیدی در ارزیابی رفتار ماهیچه بوده و کاربردهای کلینیکی بسیاری دارند. امروزه تمایل زیادی به انتقال و ذخیره طولانی‌مدت این سیگنال‌ها وجود دارد. این مطلب اهمیت ذخیره‌سازی مؤثر این سیگنال‌ها را نشان می‌دهد. در این مقاله یک روش فشرده‌سازی سیگنال‌های الکترومایوگرام مبتنی بر تقریب به کمک تجزیه حالت تجربی (EMD)، هموارسازی به کمک تبدیل DCT، دوبعدی‌سازی، تبدیل موجک و کدگذاری SPIHT پیشنهاد شده است. نقش روش EMD، تقریب و هموارسازی نسبی سیگنال و نیز فراهم‌آوردن قابلیت کنترل کیفیت سیگنال فشرده‌شده است. تبدیل DCT نیز به‌منظور هموارسازی سیگنال EMG و افزایش کارایی فشرده‌سازی استفاده‌شده است. سیگنال هموارشده، پس از دوبعدی‌سازی، به‌کمک تبدیل موجک و کدگذاری SPIHT فشرده می‌شود. روش پیشنهادی به‌کمک برخی معیارهای قدرت فشرده‌سازی (PRD و CF) و معیارهای قدرت حفظ اطلاعات کلینیکی (شامل چهار پارامتر طیفی) ارزیابی شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Electromyogram Signal Compression Based on Empirical-Mode-Decomposition-Based Approximation and DCT-Based Smoothing

نویسندگان [English]

  • M. Magari
  • H. Grailu
Faculty of Electrical and Robotics Engineering, Shahrood University of Technology, Shahrood, Iran
چکیده [English]

Electromyogram (EMG) signals are useful in muscle behavior assessment and have some clinical applications. Today, there is a great tendency to transmit and store long-term EMG recordings which implies the importance of EMG signal compression. In this paper, we have proposed an EMG signal compression approach based on Empirical-Mode-Decomposition-based signal approximation, Discrete-Cosine-Transform-based signal smoothing, two-dimensional signal processing, wavelet transform, and SPIHT coding. We have evaluated the compression performance of the proposed approach by two sets of measures: The compression throughput and clinical-information-preserving measures. The former include two measures of PRD and CF while the latter uses four spectral parameters as the appropriate measures.

کلیدواژه‌ها [English]

  • Compression
  • empirical mode decomposition (EMD)
  • signal smoothing
  • discrete cosine transform (DCT)
  • two-dimensional signal processing
  • wavelet transform
  • set partitioning in hierarchical trees (SPIHT) coding

مراجع

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