Key result
A review of various ECG compression techniques and implementations is presented to assist in selecting appropriate algorithms based on storage, power, and communication requirements.
This review provides an overview of ECG compression algorithms and their implementations, aiding in the selection of appropriate techniques based on storage, communication, power, and area requirements.
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Informs ECG device algorithm selection under resource constraints; leaves open standardized clinical validation of optimal techniques.
A duration of century past over to the invention of electrocardiogram (ECG) but even today also electrocardiogram (ECG) monitoring is playing its important role of help to take care of patients having cardiac diseases. Electrocardiogram (ECG) data compression is important for portable solutions, for reducing the storage requirements and low power consumption. Large variety of ECG compression algorithms and their implementation have been proposed in literature till date. Selection of the appropriate ECG compression technique needs important considerations such as storage requirements and communication link utilization. Further power consumption and chip area requirements depend on the computational complexity of ECG compression algorithm. Thus identifying suitable ECG compression technique for the given application requirements remains a big challenge from implementation point of view. Review of the different ECG compression techniques and ECG compression implementations available in literature is presented in this paper, which can be helpful for identifying suitable technique for application specific requirements.
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Kale et al. (2016) conducted a review in Cardiac diseases. ECG compression techniques was evaluated. A review of various ECG compression techniques and implementations is presented to assist in selecting appropriate algorithms based on storage, power, and communication requirements.
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