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Abstract

Advancement in medical technology creates some issues related to data transmission as well as storage. In real-time processing, it is too tedious to limit the flow of data as it may reduce the meaningful information too. So, an efficient technique is required to compress the data. This problem arises in Magnetic Resonance Imaging (MRI), Electrocardiogram (ECG), Electroencephalogram (EEG), and other medical signal processing domains. In this paper, we demonstrate Block Sparse Bayesian Learning (BSBL) based compressive sensing technique on an Electroencephalogram (EEG) signal. The efficiency of the algorithm is described using the Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM) value. Apart from this analysis we also use different combinations of sensing matrices too, to demonstrate the effect of sensing matrices on MSE and SSIM value. And here we got that the exponential and chi-square random matrices as a sensing matrix are showing a significant change in the value of MSE and SSIM. So, in real-time body sensor networks, this scheme will contribute a significant reduction in power requirement due to its data compression ability as well as it will reduce the cost and the size of the device used for real-time monitoring.
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Bibliography

[1] Zou, Xiuming, Lei Feng, and Huaijiang Sun. "Compressive Sensing of Multichannel EEG Signals Based on Graph Fourier Transform and Cosparsity." Neural Processing Letters (2019): 1-10.
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[5] Amezquita-Sanchez, Juan P., Nadia Mammone, Francesco C. Morabito, Silvia Marino, and Hojjat Adeli. "A novel methodology for automated differential diagnosis of mild cognitive impairment and the Alzheimer’s disease using EEG signals." Journal of Neuroscience Methods 322 (2019): 88-95.
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[17] Zhang, Zhilin, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao. "Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning." IEEE Transactions on Biomedical Engineering 60, no. 2 (2012): 300-309.
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[21] Nibheriya, Khushboo, Vivek Upadhyaya, Ashok Kumar Kajla. "To Analysis the Effects of Compressive Sensing on Music Signal with variation in Basis & Sensing Matrix." In 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA), pp. 1121-1126. IEEE, 2018.
[22] Zhang, Zhilin, Tzyy-Ping Jung, Scott Makeig, and Bhaskar D. Rao. "Compressed sensing of EEG for wireless telemonitoring with low energy consumption and inexpensive hardware." IEEE Transactions on Biomedical Engineering 60, no. 1 (2012): 221-224.
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Authors and Affiliations

Vivek Upadhyaya
1
ORCID: ORCID
Mohammad Salim
1

  1. Malaviya National Institute of Technology, India
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Abstract

The influence of glucosinolates isolated from oilseed rape seeds on the growth of pathogenic fungi infecting oilseed rape was studied. The activity of those compounds against 3 fungal species was tested in vitro. It was stated that glucosinolates present in the medium did not totally inhibit the growth of the fungi, but considerably confined the area of colonies of 2 out of 3 fungal species studied.
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Authors and Affiliations

Danuta Waligóra
Dorota Remlein-Starosta
Marek Korbas

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