Cardiac signal (also known as ECG signal) attracted researchers for using it in generating cryptographic keys due to its availability and its intrinsic nature of every individual. However, the intra-individual variance of ECG signal decreases the possibility of getting a time-invariant key for each individual and increases decryption errors in case of using it in symmetric cryptography. In this paper, we propose a time-invariant cryptographic key generation approach (TICK) that uses a novel method for reducing the intra-individual variance in the real-valued ECG features of multiple sessions. Also, it uses a quantization method for converting the improved ECG features to binary sequences with high randomness. We have tested the approach on a multi-session database. Experimental results show its viability to improve the reliability of keys up to 96.80% using across-sessions data and up to 98.69% using within-session data. We verified the randomness using five of U.S. National Institute of Standards and Technology statistical tests and the generated keys passed all tests. Also, we verified the randomness using min-entropy, and the generated keys offer entropy of ~1.