Figure 2. General Overview of the Proposed Method.
(a) The SCG signals (three-axes [dorso-ventral, DV, head-to-foot, HF, and lateral, LAT]) of heart are measured using the custom, wearable patch. Filtering is applied and SCG3D (a point-by-point average of the three axes) is calculated. Then, SCG3D of rest and recovery segments are windowed and generate NRES and NREC. (b) The L frequency domain feature sets (X and Y) are computed from NRES and NREC. (c) Two kNNG graphs (GX and GY) are constructed from frequency feature vectors X and Y and GSS is calculated to measure similarity in between rest and recovery states. (d) An example of GSS calculation between two illustrative graphs.