| Musculoskeletal disorders are one of the occupational health issues of global concern.In recent years,against the background of the rapid development of the Internet industry,the number of office workers with sedentary office hours is getting longer and longer,and the number of patients with musculoskeletal disorders in the office population has shown exponential growth in recent years,with the main symptoms being lower back pain,shoulder and neck syndrome and carpal tunnel syndrome.Musculoskeletal disorders lead to a chronic state of spinal overload and muscle fatigue in staff,resulting in increased psychological stress,discomfort and pain in body parts,reduced work efficiency,and a host of other problems.How to identify and intervene in musculoskeletal disease risks earlier in the office environment and guiding office workers in posture correction and office rhythm regulation is a problem worth studying and solving.This study is divided into three main sections:(1)The first part uses literature analysis and AHP analysis to specify the weight ranking of office musculoskeletal risk factors and design a mapping functional model of a multimodalaware system and musculoskeletal risk factors.A literature analysis method was used to review studies related to office musculoskeletal risk between 1990 and 2022,from which five categories of musculoskeletal risk based on the office task type,office hours and breaks,ergonomic performance of office tools,office postural performance,and psychological performance of office workers were extracted,and an AHP hierarchical analysis method was used to rank the weights of musculoskeletal risk in the office process.A mapping model between functional indicators-musculoskeletal disease weighting factors of the multimodal perception system was generated.(2)The second part completes the design and construction of the multimodal-aware intervention system through the functional index mapping hierarchical model,user acceptance product form research and perception technology route analysis.A multimodal data sensing and processing approach is proposed for office musculoskeletal risk.The sensing system mainly consists of three parts:the data layer,mechanism layer,and intervention layer.The data layer detects the behavioral performance and various indicators of office workers by collecting physiological data based on blood oxygen,pressure,and electromyography,posture data based on pressure cushion and ear acceleration sensors,and situational data based on mouse and keyboard behavior;The mechanism layer identifies significant changes in user physiological indicators,emotional changes and adverse posture occurrence by cleaning,processing and fusion analysis of different modal data using significance ANOVA;the intervention layer identifies different weighted musculoskeletal risk factors through data results and generates intervention pattern designs based on different weighted risk levels.(3)The third part of this study focuses on the experimental testing of the system’s index detection function and the investigation of musculoskeletal discomfort duration thresholds and physiological thresholds.Experiment I tested and experimented the multimodal data fusion analysis method to validate the system’s behavioral feature identification and indicator significant difference identification functions,and explored the correlation between EMG and blood oxygen finger pressure measurement data.Experiment 2 focused on exploring various threshold indicators of musculoskeletal risk and clarifying the reference range of intervention thresholds based on office hours and physiological indicators.Through the above three parts of the study,combined with user research and product design element analysis,Chapter 5 of this paper focuses on the completion of a multimodal data-aware musculoskeletal risk intervention product design practice for the office population. |
