Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments
Journal of Ambient Intelligence and Smart Environments
Comparison of different approaches for removal of baseline wander from ECG signal
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Fast ECG baseline wander removal preserving the ST segment
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments
Journal of Ambient Intelligence and Smart Environments
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Baseline drift in ECG signal is the biggest hurdle in visualization of correct waveform and computerized detection of wave complexes based on threshold decision. The baseline drift may be linear, static, non-linear or wavering. Reducing the baseline drift to a near zero value greatly helps in visually inspecting the morphology of the wave components as well as in computerized detection and delineation of the wave complexes. The algorithm is developed for computer implementation using MATLAB. It deploys least squares error correction and correction based on overall median of individual single lead data, to reduce baseline drift. QRS complexes are then detected to find RR intervals of the waveform. Finally, median based correction is implemented in the RR interval and a drift free signal is achieved. This can help cardiologists significantly.