Bio-signals compression using auto-encoder
| Autor: | K N Sunilkumar, Keshavamurthy Keshavamurthy, Shivashankar Shivashankar |
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| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
business.industry Computer science Real-time computing Bio-medical signals 020302 automobile design & engineering 020206 networking & telecommunications Feature selection 02 engineering and technology Auto-encoder Autoencoder Task (computing) 0203 mechanical engineering Frequency domain 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Wearable technology Energy (signal processing) |
| Popis: | Latest developments in wearable devices permits un-damageable and cheapest way for gathering of medical data such as bio-signals like ECG, Respiration, Blood pressure etc. Gathering and analysis of various biomarkers are considered to provide anticipatory healthcare through customized applications for medical purpose. Wearable devices will rely on size, resources and battery capacity; we need a novel algorithm to robustly control memory and the energy of the device. The rapid growth of the technology has led to numerous auto encoders that guarantee the results by extracting feature selection from time and frequency domain in an efficient way. The main aim is to train the hidden layer to reconstruct the data similar to that of input. In the previous works, to accomplish the compression all features were needed but in our proposed framework bio-signals compression using auto-encoder (BCAE) will perform task by taking only important features and compress it. By doing this it can reduce power consumption at the source end and hence increases battery life. The performance of the result comparison is done for the 3 parameters compression ratio, reconstruction error and power consumption. Our proposed work outperforms with respect to the SURF method. |
| Databáze: | OpenAIRE |
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