The flexible and distributed pressure sensor with 64 units for on-line gait recognition analysis

With the rapid development of flexible electronic technology, human gait recognition device is also developing in the direction of flexibility, refinement, and intelligence. In this paper, a gait recognition system with the advantages of being non-invasive and flexible is proposed and prepared to collect complex pressure information of human plantar and identify different gaits accurately. A flexible and distributed pressure sensor with a structure of eight rows and eight columns is designed and fabricated by the screen printing process and micro-nano manufacturing technology. The insole shape can be placed directly into a sneaker for easy wearing, while 64 pressure sensing units allow for more accurate detection of complex plantar pressure information. In addition, based on the voltage mirror principle and the feature threshold analysis method, a distributed pressure acquisition circuit and an online gait recognition software are developed respectively to realize time-sharing decoupling of complex output signals from multiple pressure sensing units and online real-time display of different gaits. Finally, Different human gait recognition experiments have also been carried out. The results show that the test error of the pressure sensing unit is better than 8.28%. The gait recognition system can realize the reliable and accurate online real-time identification of slow walking, fast walking, and different leaning directions, which shows great potential and value in the fields of medical diagnosis, health monitoring, gait correction and artificial intelligence.

Automated summary

With the development of flexible electronic technology, a non-invasive and flexible gait recognition system is proposed in this study. A flexible and distributed pressure sensor is designed and fabricated to collect complex pressure information, and a distributed pressure acquisition circuit and an online gait recognition software are developed to accurately identify different gaits. The system shows great potential and value in fields such as medical diagnosis, health monitoring, gait correction, and artificial intelligence.