Work in demanding postures is a known risk factor for work-related musculoskeletal disorders (MSDs), specifically work with elevated arms may cause neck/shoulder disorders. Such a disorder is a tragedy for the individual, and costly for society. Technical measurements are more precise in estimating the work exposure, than observation and self-reports, and there is a need for uncomplicated methods for risk assessments. The aim of this project was to develop and validate an iOS application for measuring arm elevation angle. Such an application was developed, based on the built-in accelerometer and gyroscope of the iPhone/iPod Touch. The application was designed to be self-exploratory. Directly after a measurement, 10th, 50th and 90th percentiles of angular distribution and median angular velocity, and percentage of time above 30°, 60°, and 90° are presented. The focused user group, ergonomists, was consulted during the user interface design phase. Complete angular datasets may be exported via email as text files for further analyses. The application was validated by comparison to the output of an optical motion capture system for four subjects. The two methods correlated above 0.99, with absolute error below 4.8° in arm flexion and abduction positions. During arm swing movements, the average root-mean-square differences (RMSDs) were 3.7°, 4.6° and 6.5° for slow (0.1 Hz), medium (0.4 Hz) and fast (0.8 Hz) arm swings, respectively. For simulated painting, the mean RMSDs was 5.5°. Since the accuracy was similar to other tested field research methods, this convenient and “low-cost” application should be useful for ergonomists, for risk assessments or educational use. The plan is to publish this iOS application on Apple Store (Apple Inc.) for free. New user feedback may further improve the user interface.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-173361 |
| Date | January 2015 |
| Creators | Yang, Liyun |
| Publisher | KTH, Skolan för teknik och hälsa (STH) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-STH ; 2015: 078 |
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