scholarly journals Biosignal Compression Toolbox for Digital Biomarker Discovery

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 516
Author(s):  
Brinnae Bent ◽  
Baiying Lu ◽  
Juseong Kim ◽  
Jessilyn P. Dunn

A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization challenges and costs. Data aggregation, sampling rate minimization, and effective data compression are all methods for consolidating wearable sensor data to reduce data volumes. There has been limited research on appropriate, effective, and efficient data compression methods for biosignal data. Here, we examine the application of different data compression pipelines built using combinations of algorithmic- and encoding-based methods to biosignal data from wearable sensors and explore how these implementations affect data recoverability and storage footprint. Algorithmic methods tested include singular value decomposition, the discrete cosine transform, and the biorthogonal discrete wavelet transform. Encoding methods tested include run-length encoding and Huffman encoding. We apply these methods to common wearable sensor data, including electrocardiogram (ECG), photoplethysmography (PPG), accelerometry, electrodermal activity (EDA), and skin temperature measurements. Of the methods examined in this study and in line with the characteristics of the different data types, we recommend direct data compression with Huffman encoding for ECG, and PPG, singular value decomposition with Huffman encoding for EDA and accelerometry, and the biorthogonal discrete wavelet transform with Huffman encoding for skin temperature to maximize data recoverability after compression. We also report the best methods for maximizing the compression ratio. Finally, we develop and document open-source code and data for each compression method tested here, which can be accessed through the Digital Biomarker Discovery Pipeline as the “Biosignal Data Compression Toolbox,” an open-source, accessible software platform for compressing biosignal data.

2021 ◽  
Vol 14 (2) ◽  
pp. 125
Author(s):  
Verryna Adzillatul Fathiha

Watermarking merupakan teknik penyembunyian data/informasi kedalam suatu citra digital yang tidak kasat mata atau tidak dapat diketahui secara visual. Penyembunyian data/informasi kedalam citra tersebut bersifat rahasia. Karena tahan terhadap proses digitalisasi, teknik watermarking dapat digunakan untuk melindungi kepemilikan suatu citra digital. Ada tiga kriteria yang harus diperhatikan dalam watermarking pada citra digital, diantaranya adalah security, impreceptibily, dan robustness. Pada tugas Penulisan Karya Ilmiah (PI) ini dibuat suatu program watermarking menggunakan metode Discrete Wavelet Transform (DWT) dan Singular Value Decomposition (SVD) yang kemudian juga akan dipaparkan bagaimana cara menggunakan program watermarking yang telah dibuat. Keunggulan dari program ini citra yang digunakan dalam program watermarking ini dapat berupa citra berwarna maupun citra grayscale. Program watermarking ini dibuat menggunakan bahasa pemrograman C++ melalui aplikasi Matlab Kata Kunci            : Wateramarking , Singular Value Decomposition (SVD), Discrete Wavelet Transform (DWT), Matlab, Bahasa Pemrograman C++.


Author(s):  
Divya Chadar ◽  
Shailja Shukla

An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same. 


Author(s):  
Om Narayan Mishra ◽  
Shailja Shukla

Watermarking is a method to hide the image efficiently into any covering object (image in our case) so no intruder can interpret it by any means. Proposed work is a new design of image watermarking which include pre-processing of cover image with Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). Proposed work using an alphanumeric key which initially modifies the watermark using simple ‘XOR’ operation, and at the receiver end this key must be there so that receiver can extract the watermark.  Proposed work is also using torus Automorphism which initially changes the watermark into a scramble format which cannot be recognised as original watermark.


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