On the wavelet-based compressibility of continuous-time sampled ECG signal for e-health applications.

This paper presents a compression study of electrocardiogram (ECG) signals for e-Health cardiac online diagnostic systems. The study uses 75 real electrocardiogram records sampled with continuous-time level-crossing (LC) analog-to-digital converter (ADC). This signal-dependent LC-ADC compresses signals compared to conventional ADC but further compression is needed especially for long-time monitoring applications. The orthogonal matching pursuit algorithm is simulated to evaluate ECG compression with 54 orthogonal and biorthogonal wavelets. For LC-ADC amplitude output compression, Biorthogonal3.1 (bior3.1) wavelet achieves optimal performances in terms of compression ratio (CR) while ensuring 2-% percentage root-mean-square difference (PRD). The PRD must be limited to this value to ensure a very good quality signals after decompression. For circuit implementation purposes, bior3.1 wavelet is proposed as a multiplier-free decomposition step and a noncomplex global and hard thresholding process is achieved. The average CR is 63% and PRD varies between 0.1 and 2.1% leading to a very good diagnostic quality.

Event-Driven ECG Sensor in Healthcare Devices for Data Transfer Optimization.

The long-term monitoring of cardiovascular signs requires a wearable and connected electrocardiogram (ECG) healthcare device. It increases user's comfort and diagnosis quality of chronic cardiac and/or high-risk patients. This paper covers the enormous data to be transmitted from the ECG device to the physician's, namely the cardiologist's, control unit. Existent ECG devices uniformly sample analog signals and convert them to digital samples which are compressed before data transmission. However, event-driven sampling simultaneously compresses and samples. Therefore, this paper quantitatively compares successive approximation register analog-to-digital converter (SAR ADC) with discrete wavelet transform (DWT) compression and level-crossing analog-to-digital converter (LC-ADC). Evaluation metrics are the percent root-mean-square difference ( PRD ), bit compression ratio ( BCR ) and data length in bits. When a 12-bit reconstruction is operated on the outputs of an 8-bit LC-ADC with 12-bit and 10-kHz reference counter, the BCR is equal to 80% for 75% of test ECG signals. That is better than the 71.87% BCR of the 12-bit 1-kHz SAR ADC with DWT compression. The modeled LC-ADC guarantees a signal quality in terms of PRD comparable to the PRD of the SAR ADC with DWT compression. The data length in bits of the LC-ADC is lower than the data length in bits of the SAR ADC with more than 14-bit resolution with DWT compression for 82% of the test ECG signals. However, for lower resolutions, to obtain lower power consumption for radiofrequency transmission, a better alternative remains the SAR ADC with DWT compression.