There is a need to prevent low back pain in various workplaces, such as reducing the burden on workers and reducing fatigue, and the research group is working on "lightening" various tasks. In 2015, in collaboration with Nikon, we developed a sensor-embedded wear "Wearing X-ray" that can easily detect how the burden is placed on the worker. Succeeded in measuring and managing in real time.However, although it was possible to measure the load on the lower back due to its own weight due to changes in posture, it was not able to handle the work load due to external forces such as holding the patient and lifting luggage.
　
　This time, by incorporating a new sensor that measures the activity of the muscles of the back, we have developed a sensing technology that can know in detail the increase or decrease in the load on the lower back without knowing the weight of the luggage to be lifted.In the cargo lifting experiment, we succeeded in improving the measurement accuracy of the load on the lower back by about 3 to 5% on average compared to the conventional method using only the posture sensor.Assist tools such as strength assist suits can visualize the degree of reduction of the load on the lower back even when the waist is assisted.　
　
　In the future, the research group is considering developing products and services that can be used in nursing care facilities and other workplaces.By accumulating waist load data during work and analyzing big data, we plan to proceed with development with a view to providing solutions that lead to business improvement such as reduction of waist load and optimization of staffing.In addition, it can be expected to be used as a sensor for assist tools and for evaluating the assistive effects of assist tools such as muscle strength assist suits.