Performing human-like motions that involve multiple contacts is challenging for robots. In this regard, a researcher has envisioned an interactive cyber-physical human (iCPH) platform with complementary humanoid (physical twin) and simulation (digital twin) elements. iCPH combines human measurement data, musculoskeletal analysis, and machine learning for data collection and augmentation. As a result, iCPH can understand, predict, and synthesize whole-body contact motions.