Analysis of compression algorithms on ECG signals using an embedded system

• Tarlysson Menezes Universidade Federal De Sergipe (UFS)
• Edward Ordonez Universidade Federal De Sergipe (UFS)

Abstract

Digital systems applied to medicine are increasingly common. Often, you need to decide how best to capture, process, store, and transfer analytical data from such systems. The focus was electrocardiogram devices, specifically the decrease in the size of the data captured by them. In this work, we analyzed which compression algorithm had the best performance using a Raspberry Pi 3 in relation to the memory consumption, time and processing used. In addition, a comparison was made between them and a discussion of which best suits each situation.

References

Holtz, K. and Holtz, E. (2002). Lossless data compression techniques. WESCON/94. Idea/Microelectronics. Conference Record.

Mahoney, M. (2009). Incremental journaling backup utility and archiver.

Mahoney, M. (2010). Data compression explained.

Martin, G. and Chang, H. (2002). System-on-chip design. ASIC, 2001. Proceedings. 4Th International Conference on.

Moody, G. and Mark, R. (2001). The impact of the mit-bih arrhythmia database. IEEE Eng in Med and Biol, pages 45–50.

Salomon, D. and Motta, G. (2009). Handbook of data compression, 5th edition. Springer, pages 16–18.