The Biomechanics of Bedsharing
Faculty Mentor Information
Dr. Erin Mannen (Mentor), Boise State University
Abstract
Sudden Unexpected Infant Death (SUID) is a critical public health issue, with half of the 3,500 annual cases in the U.S. involving bedsharing. Despite the frequency of these cases, there is a limited understanding how the adult bed's mechanical environment affects infant movement. This research investigates the mechanical environment and movement patterns of caregiver-infant dyads to better understand the associated risk. Three data collection methods—OpenCap markerless motion capture, Vario thermal camera, and GoPro video camera— were tested for feasibility of recording participants overnight in their homes. OpenCap, despite advanced biomechanical analysis capabilities, was hindered by recording limitations and calibration challenges. The thermal camera effectively captured thermal images and provided a visualization of heat patterns but is expensive and requires significant set-up space which may not be feasible in participants’ homes. The GoPro camera emerged as the optimal choice due to its high-resolution video and wide-angle lens, providing clear footage of the entire mattress area. Future steps will include quantifying movement patterns using image analysis. Integrating high-quality video data and advanced computational analysis offers critical insights into bedsharing dynamics, ultimately contributing to the development of safer sleep practices and reducing the incidence of SUID.
The Biomechanics of Bedsharing
Sudden Unexpected Infant Death (SUID) is a critical public health issue, with half of the 3,500 annual cases in the U.S. involving bedsharing. Despite the frequency of these cases, there is a limited understanding how the adult bed's mechanical environment affects infant movement. This research investigates the mechanical environment and movement patterns of caregiver-infant dyads to better understand the associated risk. Three data collection methods—OpenCap markerless motion capture, Vario thermal camera, and GoPro video camera— were tested for feasibility of recording participants overnight in their homes. OpenCap, despite advanced biomechanical analysis capabilities, was hindered by recording limitations and calibration challenges. The thermal camera effectively captured thermal images and provided a visualization of heat patterns but is expensive and requires significant set-up space which may not be feasible in participants’ homes. The GoPro camera emerged as the optimal choice due to its high-resolution video and wide-angle lens, providing clear footage of the entire mattress area. Future steps will include quantifying movement patterns using image analysis. Integrating high-quality video data and advanced computational analysis offers critical insights into bedsharing dynamics, ultimately contributing to the development of safer sleep practices and reducing the incidence of SUID.