Smart clothing and measurement methods in ergonomics
Physical workload is an important risk factor for work-related injuries, which lead to costs to both the individual and society. There are different assessment methods today for evaluating a work task, including self-reports, observational methods and technical measurements using sensors. These assessments are shown to improve work environments while also have positive economic effects to the companies. While there are limitations in these methods, that it requires lots of resources in time, money and personnel. That is part of the reason why they are not widely used, especially for small and medium companies.
The aim of this project is to develop a practical system of clothes with integration of sensors, which can measure, analyze, evaluate and visualize the risks of the physiologic load at work, and in the long term, prevent occupational injuries and promote healthy work environment.
The project begins with a convenient and low-cost measurement method using an iOS application – ErgoArmMeter to measure arm elevation at work. It is validated to have similar accuracy compared to former validated accelerometers, and higher accuracy when measuring fast movements because of the integration of gyroscopes.
The next step is to deal with physical activities in combination with heart rate to evaluate and visualize the risk of physiologic workload, which is planed to conduct in collaboration with a project team from Medical sensors, signals and systems.
Project period: 2015 – 2019
Funding: AFA Insurance & China Scholarship Council
Project Leader: Jörgen Eklund
PhD Student: Liyun Yang