Piezoelectric flexible sensing device

Abstract

The invention belongs to the technical field of sensor manufacturing, in particular to a piezoelectric flexible sensing device. The piezoelectric flexible sensing device mainly consists of a piezoelectric flexible sensor, an electromyographic signal preprocessing module, a Bluetooth wireless transmission module, a Bluetooth wireless receiving module, an electromyographic signal analysis processingmodule, a prosthesis motion control module and the like. The piezoelectric flexible sensor collects muscular tension signals and transmits the signals to the electromyographic signal preprocessing module, the electromyographic signal preprocessing module transmits preprocessed electromyographic signals to the electromyographic signal analysis processing module, and the prosthesis motion control module controls the motions of prostheses according to the electromyographic signals processed by the electromyographic signal analysis processing module. The device is reasonable in structure, scientific and reliable in principle, great in product stability, high in sensitivity and capable of greatly improving the life of the disable. By adopting built-in sensors, epidermal tissue can be avoided to directly apply the electromyographic signals, the signals can be more effectively and accurately collected to help manipulation of the prostheses, and therefore the movement functions of the prostheses can be more equivalent to those of original limbs.

Description

Technical field: [0001] The invention belongs to the technical field of sensor production, and specifically relates to a piezoelectric flexible sensing device, which uses a piezoelectric flexible sensor that is 3D printed to seamlessly fit the remaining limb muscles and adjacent tissue shapes to collect muscle tension signals. Working near the optimal working point of the tension state, the sensitivity is higher, relying on the ARM 9 architecture S3C2440 as the core processor of the prosthetic control terminal, through the software intelligent behavior mode to carry out feature recognition and analysis, and separate the control signal of the residual limb from the signal of the missing limb , using the signal of the missing limb to control the movement of the prosthesis through the ARM microcontroller, so that the function of the movement of the prosthesis is close to that of the original limb. Background technique: [0002] There are various types of sensors and their prepa...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the existing commercial 3D printing raw materials are powder or filament materials, and the waste of raw materials is serious. However, the price of P(VDF-TrFE) sold in the market is relatively high, so it is necessary to reduce the loss of preparation. Through the transformation of the printing head feeding method Using liquid raw materials as printing materials can save raw materials; (Titterington Don[US]; Wang Patricia[US]; WuBo[US] Inks comprising gallants for 3D printing.US20171564083020170703; French Xavier Boddaert research group reported inkjet printing in 2016 PVDF-TrFE sensor (Haque RI, Vie R, Germainy M, Valbin L, Benaben P, Boddaert X. Inkjet printing of high molecularweight PVDF-TrFE for flexible electronics. Flex Print Electron. 2016; 1(1): 12)), etc.

In terms of analyzing nerve signals, Wang Hong analyzed the whole brain wave to obtain residual limb control information (Human brain-manipulator interface system in micro-power wireless communication mode invented by Wang Hong, Li Chunsheng, Liu Chong, and Zhao Haibin in 2009[P] , the patent number is CN101569569;), but the signal components are complex and the accuracy is affected; we intend to use the signal of the clear residual limb nerve, drawing on the US patent of Hargrove et al. (Hargrove LJ, Simon AM, Young AJ, Lipschutz RD, Finucane SB, Smith DG, et al. Robotic leg control with EMG decoding in anamputee with nerve transfers. N Engl J Med. 2013; 369(13): 1237-42), found that body movements have their own Behavioral patterns, such as the bending of the knee joint, in order to find the signals that control the prosthetics, Hargrove et al. analyzed the EMG signals, and removed the useful signals from the original muscle signals to control the prosthetics (Hargrove LJ, Simon AM, Young AJ, Lipschutz RD, Finucane SB, Smith DG, etal. Robotic leg control with EMG decoding in an amputee with nerve transfers. NEngl J Med.2013; 369(13):1237-42); amputee patients due to their own mobility, lodging and other disabilities There are many certainties, and the method of connecting multiple wires of multiple nerves to the control terminal of the prosthesis is not suitable, so Bluetooth technology is used to wirelessly transmit the myoelectric signals collected in the body to the control terminal of the prosthesis (invented by Chen Peng and Liu Jun in 2016) Prosthesis Surface EMG Signal Acquisition System Based on Wireless Sensor Network [P], Patent No. CN105434088A)

[0004] To sum up, the existing technologies generally suffer from complicated preparation process and high preparation cost. The use of commercial 3D printing raw materials to prepare sensors is a waste of resources and insufficient product stability. Ordinary sensors are susceptible to noise interference by obtaining muscle tension data from the body surface. , skin and other tissues cause signal attenuation and other problems, and the application range is small, the safety is poor, and the service life is short.

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