Assessing motion induced interruptions using a motion platform

Abstract

Human performance contributes to total system performance. As human performance decreases, total system performance decreases while lifecycle costs increase. In a fiscally constrained environment, Human Systems Integration (HSI) seeks to assure human performance to reduce operating costs. This thesis seeks to develop a model for ship design in relation to Motion Induced Interruptions (MII). The model is based on the premise that MIIs affect specific domains of HSI in an adverse way. Future ship design considerations that mitigate MII occurrences can save the Navy money spent on human injury and system degradation. The thesis begins with an historical overview of MII theory and development and its interactions with domains of HSI. A MII prediction model was developed using data acquired from an experiment using a motion-based platform that emulates ship motion. Quantitative data were analyzed from 21 subjects who underwent 32 trials. Multiple regression analysis consisted of two independent variables as period and lateral acceleration and the response variable as a MII incident. Logistic regression considered two more independent variables that addressed individual differences. Data analysis revealed that acceleration, period, and human balance were statistically significant. The proposed multiple regression model accounted for 77% of the variance of MII forecasting. This thesis lays the foundation for future quantitative analysis of interactions between MIIs and accelerations or periods in different axes. Additionally, it provides an initial model that predicts conditions of high MII incident environments that can ultimately lead to a viable design tool for HSI practitioners and ship designers.