Abstarct: Invasive blood pressure signals have high importance in the diagnosis of diseases, as well as the continuous treatment and control of the patient. Nowadays, devices that are responsible for recording these signals are facing memory space problems. Therefore, our goal is to compress and store invasive blood pressure signals while retaining the main features. Two proposed hybrid algorithms are presented as compact blocks. In this thesis IBP signals include three different types of measured ABP, PAP and CVP from the databaxse (MGH/MF) from the physionet site with proposed compression methods. Different methods are available for compression of various types of bio-electric signals, after which it was decided to use the combination of EMD and DCT or wavelet transform with Run length encoding method and MQ coding. The proposed method is represented because of the absence of error by RLE, the reversibility of the wavelet transform and the DCT, and the ability to make an appropriate approximation by EMD. To analyze the results, the most important criterion is the compression ratio. The RMS error and Percent Root mean-square Difference, which are among the known criteria in this field, are used for analysis. Numerical results showed that the compression ratio of the proposed method with DCT versus the proposed method with DWT, the two-dimensional method and proposed method without EMD block is 3.4, 21.1 and 1.05 times respectively. In the end, the recommendations of this thesis are presented to improve compression of Invasive blood pressure signals and, in general, biometric signals.