An electrocardiogram (ECG) is a recording of the heart's activity, represented by a series of voltage data. The ECG data can be used for various medical purposes, such as monitoring heart rate, detecting arrhythmias, and diagnosing heart conditions. The ECG signal contains sensitive patient data and is bandwidth-intensive, which can pose challenges for storage and transmission.

The Proposed Technique

A hybrid technique for compression and encryption is proposed and analyzed. The proposed technique uses a compress-then-encrypt approach involving 3 main phases:

  1. Preprocessing
  2. Compression
  3. Encryption

Preprocessing

The ECG signal is preprocessed to reduce noise and artifacts to make the data suitable for compression. This involves the following steps:

  1. Peak Detection and Segmentation
  2. Period Normalization
  3. DC Equalization
  4. Sample Entropy Based Sorting

Compression

The preprocessed ECG signal is compressed using AV1 Image File Format (AVIF). The side infromation is compressed using Lempel–Ziv–Markov chain algorithm (LZMA).

Encryption

The compressed ECG data and the side information are encrypted using Chaotic Maps. It involves the following steps:

  1. Sine Map Generation
  2. Generation of Sorting Indices
  3. 8-bit Quantization
  4. Encryption using the quantized map, and s-box

The final output is a compressed and encrypted ECG signal that can be stored and transmitted efficiently.

The research work was presented at the 3rd National Conference on Emerging Trends on Law and Technology (ETLT-2024).