The electrocardiogram (ECG) is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, these signals are highly subjective, and the symptoms may appear at random in the time scale. It is very taxing and time-consuming to decipher cardiac abnormalities based on these ECG signals. The Vectorcardiogram (VCG) is the vector loop in the 2-D frontal plane, indicating the magnitude and direction of the instantaneous heart electrical activity vector (HAV), which represents the sum of the dipole vectors located along the instantaneous depolarization wavefront. The HAV is constructed from the monitored 3-lead ECG signals, placed at the three vertices of the modified Einthoven triangle formed by the 3-lead system in the frontal plane of the torso. The VCG examines the electrical activities within the heart, using the ECG signals along the three sides of the modified Einthoven triangle, and displays electrical events in the 2-dimensional frontal plane. This study demonstrates the development of the heart-depolarisation vector-locus cardiogram (using modified Einthoven's triangle), as a diagnostic measure of the left ventricular depolarisation strength. Our work involves the reconstruction of the "equivalent heart vector" for the QRS complex from limb lead voltages of a sample ECG, and plotting the progression of the cardiac vector during the QRS complex. We have demonstrated the construction of the frontal plane heart-depolarization vector cardiogram (HDVC), as the path of the locus of the tip of the heart electrical activity vector, with initial and terminal points at the origin. In this work, we have shown characteristic patterns of HDVC for cardiac states namely, normal, bundle branch block, ventricular hypertrophy and myocardial infarction. We have demonstrated how HDVC can be diagnostically employed to characterize cardiac disorders, such as ventricular hypertrophy bundle branch block and inferior myocardial infarction.