Mother-Infant Interaction Kinect Analysis (MIIKA): An automatic kinematic-based methodology for the investigation of interpersonal distance during early exchanges

Interpersonal distance is a core aspect of mother-child interaction. While conventional measures based on human coders do not fully capture the dynamics of this feature, computational methods provide automatic measures which can detect even small changes and more accurate estimates both spatially and temporally. Using RGB-D sensors (Microsoft Kinect V2), the present study describes a setup to automatically examine interpersonal distance during mother-child interactions, termed Mother-Infant Interaction Kinect Analysis (MIIKA). First, the laboratory setting and the data extraction method are described. By using an ad-hoc algorithm for kinematic data extraction, MIIKA returns three metrics: barycenter position (distance and velocity of approach and separation), movements (number of small, medium and large approaches and separations) and contributions (proportional contributions of mother and child to approaches and separations). Secondly, preliminary MIIKA metrics are described for a non-clinical mother-child dyad as an exemplification of the protocol. As interpersonal distance can be affected by contingent situations, we detected mother-infant full skeleton during three interactional contexts characterized by different kinds of dyadic exchanges: a free play session, a task-oriented activity and an emotionally arousing condition. Results highlighted similarities and differences between the three interactional contexts. MIIKA appears to be a promising setup to automatically examine interpersonal distance in early mother-child interactions.     

Sensing everyday activity: Parent perceptions and feasibility

Mobile and wearable sensors provide a unique opportunity to capture the daily activities and interactions that shape developmental trajectories, with potential to revolutionize the study of development (de Barbaro, 2019). However, developmental research employing sensors is still in its infancy, and parents’ comfort using these devices is uncertain. This exploratory report assesses parent willingness to participate in sensor studies via a nationally representative survey (N = 210) and live recruitment of a low-income, minority population for an ongoing study (N = 359). The survey allowed us to assess how protocol design influences acceptability, including various options for devices and datastream resolution, conditions of data sharing, and feedback. By contrast, our recruitment data provided insight into parents’ true willingness to participate in a sensor study, with a protocol including 72 h of continuous audio, motion, and physiological data. Our results indicate that parents are relatively conservative when considering participation in sensing studies. However, nearly 41 % of surveyed parents reported that they would be at least somewhat willing to participate in studies with audio or video recordings, 26 % were willing or extremely willing, and 14 % reported being extremely willing. These results roughly paralleled our recruitment results, where 58 % of parents indicated interest, 29 % of parents scheduled to participate, and 10 % ultimately participated. Additionally, 70 % of caregivers stated their reason for not participating in the study was due to barriers unrelated to sensing while about 25 % noted barriers due to either privacy concerns or the physical sensors themselves. Parents’ willingness to collect sensitive datastreams increased if data stayed within the household for individual use only, are shared anonymously with researchers, or if parents receive feedback from devices. Overall, our findings suggest that given the correct circumstances, mobile sensors are a feasible and promising tool for characterizing children’s daily interactions and their role in development.