Active Deep Tissue Massage (ADTM) is a manual therapy technique that combines therapist-applied pressure with active participant movement. To better understand the mechanics of this interaction, I collected motion capture and force plate data and developed biomechanical, physics-based, and machine learning models to estimate therapist-applied forces during treatment. My research quantified therapist forces, measured synchronization between therapist and participant movement, and analyzed differences across multiple muscle groups, providing one of the first quantitative characterizations of force application during ADTM.