فشرده‌سازی سیگنال‌های الکترومایوگرام مبتنی بر هموارسازی به کمک تکنیک پیش‌تاکید-واتاکید

نوع مقاله : علمی-پژوهشی

نویسندگان

1 دانشکده برق و رباتیک - دانشگاه صنعتی شاهرود

2 دانشکده مهندسی برق و کامپیوتر - دانشگاه صنعتی شاهرود

چکیده

امروزه تمایل زیادی به ذخیره طولانی مدت سیگنال‌های الکترومایوگرام (EMG) و بنابراین فشرده سازی مؤثر آنها وجود دارد. در این مقاله، با توجه به تغییرات زمانی نسبتاً سریع سیگنالهای الکترومایوگرام، یک نسخه هموار متناظر با سیگنال الکترومایوگرام مورد نظر تولید می‌شود تا کارایی فشرده‌سازی بهبود یابد. برای هموارسازی سیگنال، برای اولین بار در این مقاله، از تکنیک پیش‌تاکید-واتاکید در حوزه تبدیل فوریه استفاده شده است. سیگنال هموار شده، به منظور افزایش تزاید مکانی، به کمک تکنیک دوبعدی‌سازی به تصویر معادل خود تبدیل و سپس به کمک تبدیل موجک و کدگذاری SPIHT فشرده‌سازی می‌شود. روش پیشنهادی به کمک دو دسته از معیارها، معیارهای قدرت فشرده‌سازی (شامل PRD و CF) و معیارهای قدرت حفظ اطلاعات کلینیکی (شامل چهار پارامتر طیفی) ارزیابی شده است. نتایج، همگی نشان‌دهنده توانمندی و برتری روش پیشنهادی در مقایسه با مهمترین روش‌های امروزی بوده‌اند.

کلیدواژه‌ها

عنوان مقاله [English]

Electromyogram Signal Compression Using Pre/De-emphasis- Based Smoothing Technique

نویسندگان [English]

  • M. Magari 1
  • H. Grailu 2
1 Faculty of Electrical and Robotics Engineering, Shahrood University of Technology, Shahrood, Iran
2 Faculty of Electrical and Robotics Engineering, Shahrood University of Technology, Shahrood, Iran
چکیده [English]

Today, there is a great tendency to store long-term recordings of electromyogram (EMG) signals; thus, showing the importance and necessity of effective compression of this type of biomedical signals. In this paper, regarding to the relatively rapid variation of EMG instantaneous amplitudes and thus having rather high frequency components, we have proposed a compression approach in which a smooth and reversible version of the input EMG signal is generated to be compressed instead of the original one; thus, improving the compression efficiency. We have used the pre/de-emphasis technique in the Fourier domain to produce a smooth signal from the input EMG signal. The smoothed signal is then simply converted to the corresponding 2D image and finally, compressed by the Wavelet transform and Set Partitioning In Hierarchical Trees (SPIHT) codec. The proposed method is evaluated by two sets of criteria, measuring the compression efficiency (including the PRD and CF measures) and capability of preserving the clinical information (including four spectral parameters). The results show the superiority of the proposed method compared to most of existing approaches.

کلیدواژه‌ها [English]

  • Electromyogram Signal Compression
  • Signal Smoothing
  • Pre/De-emphasis Technique
  • Fourier Transform
  • Wavelet Transform
  • SPIHT codec

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