Towards a user-specific ergonomics-based approach for an activity assessment tool

Work-related musculoskeletal disorders (WRMSDs) are the most reported work-related health problem in European Union. These are multifactorial disorders, influenced not only by sustained or repeated awkward postures but also by each worker’s individual and psychosocial context. Thus, it becomes crucial to quantify and automatize risk assessment, in an attempt to prevent and reduce WRMSD. This work presents the design of a solution for a user-specific assessment based on ergonomics for posture correction through an intuitive haptic feedback strategy to increase posture self-awareness and guide the user into a more neutral posture. The user’s angular configurations are continuously evaluated with a risk score, based on an ergonomic method, and then associated with the postures where those risks occurred. Posture is intended to be predicted by a deep learning model. Moreover, a joint kinematic wear index is used to carry out a cumulative assessment, taking into account the past postures’ scores. Inertial data from three individuals was collected and analyzed to perform movement analysis and define the ground truth of the recognition model. The resulting kinematic parameters’ ranges are presented. An offline risk assessment was also conducted, showing the potential of the cumulative approach for a more complete and meaningful evaluation.This work was supported in part by the Fundação para a Ciência e Tecnologia (FCT) under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020, and by the FEDER Funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI) and P2020 with the Reference Project SmartOs Grant POCI-01-0247-FEDER-039868. Sara Cerqueira was supported by the doctoral Grant SFRH/BD/151382/2021, financed by the Portuguese Foundation for Science and Technology (FCT), under MIT Portugal Program