Human-to-human touch conveys rich, meaningful social and emotional sentiment. At present, however, we understand neither the physical attributes that underlie such touch, nor how the attributes evoke responses in unique types of peripheral afferents. Indeed, nearly all electrophysiological studies use well-controlled but non-ecological stimuli. Here, we develop motion tracking and algorithms to quantify physical attributes – indentation depth, shear velocity, contact area, and distance to the cutaneous sensory space (receptive field) of the afferent – underlying human-to-human touch. In particular, 2-D video of the scene is combined with 3-D stereo infrared video of the toucher’s hand to measure contact interactions local to the receptive field of the receiver’s afferent. The combined and algorithmically corrected measurements improve accuracy, especially of occluded and misidentified fingers. Human subjects experiments track a toucher performing four gestures – single finger tapping, multi-finger tapping, multi-finger stroking and whole hand holding – while action potentials are recorded from a first-order afferent of the receiver. A case study with one rapidly-adapting (Pacinian) and one C-tactile afferent examines temporal ties between gestures and elicited action potentials. The results indicate this method holds promise in determining the roles of unique afferent types in encoding social and emotional touch attributes in their naturalistic delivery.