Data generated and analyzed of our work titled "A computational model of rabbit geometry and ECG: Optimizing ventricular activation sequence and APD distribution". Please see the respective publication for more context. BSPM_filtered.dat Contains the filtered ECG Data BSPM_original.bdf Contains the originally recorded signal. Information on the file format itself can be found here: https://www.biosemi.com/faq/file_format.htm Links to various toolboxes to open the file can be found here: https://www.biosemi.com/download.htm CT_DataDCM.zip Contains the recorded CT images of heart and torso in DCM file format ECG_NodeIndices.txt Contains the the node IDs of the torso mesh corresponding to the electrode positions of the ECG Vest Endocardial_Surface_Papillary.stl Segmented endocardial surface including papillary muscles Mat_LeadField.dat Contains the calculated lead field matrix to be used in combination with the provided Mesh_Ven.vtu. Make sure to keep the node order # Python example of usage # Define a read_vm_vec function which reads your calculated data beforehand import numpy as np t_begin = 0 t_end = 400 LF_mat = np.loadtxt('Mat_LeadField.dat') times = np.linspace(t_begin, t_end, t_end-t_begin) result = np.zeros((len(times), 31)) for i,t in enumerate(times): vm_vec = read_vm_vec(t) result[i, :] = LF_mat.dot(vm_vec)[0:31] result = np.insert(result, 0, times, axis=1) np.savetxt('BSPM.dat', result) Mesh_PurkinjeTree.vtp The resulting optimized Purkinje Node tree. We recommend using ParaView for visualization Mesh_StimPoints.vtp The resulting points of stimulation. Stim_IndexTime.dat Contains the stimulation pattern in terms the node index of Mesh_Ven.vtu and the respective stimulation time Mesh_Ven.vtu Contains the ventricular mesh as well as the repective lead field matrix values for each surface node. Material: Right Ventricle 30 Left Ventricle 31 Mesh_Torso.vtu Contains the whole torso mesh. Material: Fat 2 Bones 3 Blood 9 Cartilage 14 Liver 20 Lungs 17 Right Ventricle 30 Left Ventricle 31 Right Atrium 32 Left Atrium 33 Aorta 60 Pulmonary artery 61 Left Vena Jugularis 62 Right Vena Jugularis 62 Post Vena Cava 62

RM, GS and KEO gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG #394630089). EMW and GS gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG #183027722). RM, EMW, and GS are members of the Collaborative Research Centre SFB 1425 (DFG #422681845).