Validation of a Smart shirt for tracking work postures of the trunk

Sammanfattning: Abstract Background Ergonomists are interested in measuring the work postures and movements workers perform during their workday. The most common evaluation method to date, is observational studies, where the ergonomist visits the workplace and performs an evaluation. This is time consuming and different ergonomists tend to have low correlation between their evaluations. To make objective evaluations and speed up the process, a system to capture the work postures and movements would be helpful. Optical motion capture (OMC) systems have shown to have high accuracy and precision for capturing work postures and movements, but OMC systems are quite costly and often need a whole laboratory to be set up. This is not feasible in most workplaces. Inertial sensors on the other hand, enable sufficient capturing of the motions but still have the convenience of being mobile and easy to set up. The purpose of this thesis is to contribute to the development of a motion capture system, based on inertial sensors. Methods An existing Android application was modified for measuring the working postures of the trunk. To evaluate the construct validity, measurements of the inertial sensors were compared to an OMC system, which was used as a gold standard. Three different sensor-placements of the inertial sensors for the trunk was tested. The positions were above the C7, T4 and L1/S5 vertebrates and at the Sternum. The relative angle between L5/S1 and the Sternum, called SaSt, was calculated. Twelve participants performed a validation experiment, following a protocol for motions in a pace set by a metronome to 20 BPM. Four of the participants repeated the validation experiment wearing a Smart shirt. The participants performed a “Posture test”, where the participants were instructed to perform the uniaxially movements flexion/extension, lateral bending and rotation. Also, the participants performed two “Work-task tests”, called symmetrical- and asymmetrical lifting. Results In the Posture test’s result showed that the mean Root Mean Square Difference (RMSD) of all inertial sensors for all types of movements performed, was 4.1˚ and the inter-system correlation was generally high (≥0.782), compared to the OMC system. Symmetrical lifting, showed in the same manner, a mean RMSD of 13˚. The correlation was high (≥0.990) in flexion/extension (over the axis where movement occurred). Asymmetrical lifting, showed a mean RMSD of 26˚. The correlation was high (≥0.732) for all types of movements. Discussions and Conclusions For the Posture test, the sensor-placements T4 and C7 had the lowest RMSD for flexion/extension and lateral bending, compared to the OMC system, but SaSt had the least RMSD when the participants were performing rotation. For the symmetrical lifting task, T4 and C7 showed much lower RMSD than SaSt for flexion/extension. The same applies for asymmetrical lifting, but this time both for flexion/extension and lateral bending. To place the inertial sensors in a Smart shirt instead of on the skin, did not affect the accuracy for the movements flexion/extension and rotation. Only lateral bending was affected, probably because the shirt does not fit tight when lateral bending is performed. The tested inertial sensor-based motion capture system is comparable to an OMC system for uniaxially movements. The inertial sensors had high correlation and low RMSD compared to the OMC system, which is impaired when the participants combined movements over two or more planes.