Output Behavior of Fall Detection Sensor Using Brush-Based Triboelectric Nanogenerator Depending on Fiber Characteristics

Abstract

Abstract In Japan, a huge portion of the population is aged people, who are prone to various diseases and injuries on a regular basis. Injuries due to falls are one of the biggest risk factors. Consequently, the demand for fall detection sensors, especially the ones that used a triboelectric nanogenerator (TENG) has recently increased. In a previous study, our group reported the development of a wearable sensor for fall detection with privacy protection using the principle of TENG. Conventional TENGs use polymer films as friction material. However, it is difficult for film-based TENGs to harvest output from various angles of contact separation, as the films have two-dimension structures. Consequently, our previous study focused on developing brush-based TENG (B-TENG), and B-TENG harvested output from various angles of contact-separation. However, the B-TENGs we developed were not sensitive enough to detect signals of lower contact force, and thereby could not be used in fall detection sensors. In this study, we focused on improving the performance of B-TENG by investigating the properties of the brushes and the effect of various external parameters on the harvested output voltage of B-TENGs. Consequently, we have constructed an optimized B-TENG, which harvests almost 18 times higher output voltage than the previous one developed by our group. Thus, this optimized B-TENG has the potential for practical use in fall detection sensors.