The risk of distal upper limb disorder in cleaners: A modified application of the Strain Index method

Abstract

This paper presents a modified application of the Strain Index (SI) method, in evaluation of effort-related variables in cleaning activities ( n=40). EMG data were analyzed in the wrist flexor and extensor muscles. Effort-related variables were calculated to each record in four trigger levels (effort values were considered when the amplitude of the signal is above the trigger level for at least 0.5 s). Differences in effort time, intensity, frequency of efforts and in the resulting SI score were observed in the same activity when these variables are calculated with different trigger levels. Vacuuming, cleaning walls, floor scrapping, dusting offices and dusting horizontal surfaces were the most critical cleaning activities in terms of distal upper extremity (DUE) risk disorders; operating mono-disc and scrubber drier floor machines, dry and wet mopping and floor sweeping are among the cleaning activities with comparatively lower risk to DUE disorders. Global values of the cleaning activities ( n=40) were calculated: Mean effort-intensity of 59.5% MVE; mean effort duration of 52.6% effort time; mean effort frequency of 7.8 peaks min −1; mean SI score of 8.7 (for a task duration <1 h). The use of EMG data to evaluate effort related variables was found to be an useful alternative to observational methods, when efforts are not clearly associated to hand/wrist movements and when non-cyclical high-frequency activities makes virtually impossible the evaluation of effort variables (intensity, frequency and duration). However, the application of this method requires the definition of an appropriate trigger level and of an activation time. Relevance to industry Job Strain Index (SI) has been widely applied in industry, but not to cleaning activities. Difficulties may occur when observational or self-report methods are applied to activities where hand/wrist efforts are not associated to clear hand/wrist movements and when non-cyclical high-frequency activities make evaluation of effort variables difficult. This study presents a modified application of the original method to calculate wrist exertion variables and it is based on the analysis of EMG data.