Background In manufacturing industries, tasks requiring poor posture, high repetition, and long duration commonly induce fatigue and lead to an increased risk of work-related musculoskeletal disorders. Smart devices assessing biomechanics and providing feedback to the worker for correction may be a successful way to increase postural awareness, reducing fatigue, and work-related musculoskeletal disorders. However, evidence in industrial settings is lacking. Objective This study protocol aims to explore the efficacy of a set of smart devices to detect malposture and increase postural awareness, reducing fatigue, and musculoskeletal disorders. Methods A longitudinal single-subject experimental design following the ABAB sequence will be developed in a manufacturing industry real context with 5 workers. A repetitive task of screw tightening of 5 screws in a standing position into a piece placed horizontally was selected. Workers will be assessed in 4 moments per shift (10 minutes after the beginning of the shift, 10 minutes before and after the break, and 10 minutes before the end of the shift) in 5 nonconsecutive days. The primary outcomes are fatigue, assessed by electromyography, and musculoskeletal symptoms assessed by the Nordic Musculoskeletal Questionnaire. Secondary outcomes include perceived effort (Borg perceived exertion scale); range of motion of the main joints in the upper body, speed, acceleration, and deceleration assessed by motion analysis; risk stratification of range of motion; and cycle duration in minutes. Structured visual analysis techniques will be conducted to observe the effects of the intervention. Results for each variable of interest will be compared among the different time points of the work shift and longitudinally considering each assessment day as a time point. Results Enrollment for the study will start in April 2023. Results are expected to be available still in the first semester of 2023. It is expected that the use of the smart system will reduce malposture, fatigue, and consequently, work-related musculoskeletal pain and disorders. Conclusions This proposed study will explore a strategy to increase postural awareness in industrial manufacturing workers who do repetitive tasks, using smart wearables that provide real-time feedback about biomechanics. Results would showcase a novel approach for improving self-awareness of risk for work-related musculoskeletal disorders for these workers providing an evidence base support for the use of such devices. International Registered Report Identifier (IRRID) PRR1-10.2196/43637

BACKGROUND In the manufacturing industries, tasks requiring poor posture, high repetition, and long duration commonly induce fatigue and lead to an increased risk of musculoskeletal disorders. Smart devices assessing biomechanics and providing feedback to the worker for correction may be a successful way to increase postural awareness, reducing fatigue and musculoskeletal disorders. However, evidence in industrial settings is lacking. OBJECTIVE This study protocol aims to explore a set of smart devices to increase postural awareness, reducing fatigue and musculoskeletal disorders METHODS A longitudinal single-subject experimental design following the ABAB sequence will be developed in a manufacturing industrial factory's real context with 5 workers. A repetitive task of screw tightening of five screws in a standing position into a piece placed horizontally was selected. Workers will be assessed in four moments per shift, in 6 nonconsecutive days. The primary outcomes are fatigue, assessed by electromyography and musculoskeletal symptoms assessed by the Nordic Musculoskeletal Questionnaire. Secondary outcomes include perceived effort, range of motion of the main joints in the upper body, speed, acceleration, and deceleration assessed by motion analysis, and cycle duration in minutes. Structured visual analysis techniques will be conducted to observe the effects of the intervention. Results for each variable of interest will be compared in-between the different time points of the work shift and longitudinally considering each assessment day as a time point. RESULTS Enrollment for the study will start in January 2023. Results are expected to be available still in the first semester of 2023. CONCLUSIONS This proposed study will explore a strategy to increase postural awareness in industrial workers, using smart wearables that provide real-time feedback about biomechanics. Results would showcase a novel approach for improving self-awareness of risk for WMSD for these workers providing an evidence base support for the use of such devices.