CN-121987215-A - Application of flexible bioelectric device in bioelectric signal sensing

Abstract

The invention discloses an application of a flexible bioelectric device in bioelectric signal sensing, and the flexible bioelectric device has an in-situ signal filtering function. The main materials of the flexible bioelectronic device, namely polyacrylamide, gelatin methacrylamide and chitosan, show selective filtering performance, and can effectively filter dynamic noise under target frequency, so that the active in-situ signal filtering function of molecular level is realized.

Inventors

• LUO TINGTING
• FANG SHU
• YANG RUNHUAI
• SONG ZIHAO
• SHANG ANQI
• LIU WEI
• LI SHANTIAN
• LU XINGQI

Assignees

• 安徽医科大学

Dates

Publication Date

20260508

Application Date

20260127

Claims (3)

1. 1. The application of the flexible bioelectric device in bioelectric signal sensing is characterized in that the flexible bioelectric device has an in-situ signal filtering function.
2. 2. The use according to claim 1, wherein the frequency range of the in-situ signal filtering by the flexible bioelectronics device is 30-50Hz.
3. 3. The use according to claim 1, wherein the method of manufacturing the flexible bioelectronic device comprises the steps of: S1, dissolving acrylamide Am, methacrylate gelatin GelMA and chitosan powder in acetic acid solution, uniformly stirring, adding carboxylated multi-walled carbon nanotube MWCNT into the mixed solution, and carrying out ultrasonic treatment, water bath and degassing treatment to obtain a precursor solution; s2, mixing sodium dihydrogen phosphate and sodium dihydrogen phosphate, adding sodium bicarbonate, adding ammonium persulfate as an initiator, fully stirring, and degassing to obtain a gelling solution for inducing chitosan physical crosslinking; S3, selecting a material with carboxyl, amino and hydroxyl groups to manufacture a die for cross-linking and forming of the polymer; And S4, mixing and stirring the precursor solution prepared in the step S1 and the gelling solution prepared in the step S2 in a ratio of 1:1-2:1, then injecting the mixture into the die prepared in the step S3, standing at room temperature until the polymer is in a gel state, and integrally forming to prepare the flexible electronic device.

Description

Application of flexible bioelectric device in bioelectric signal sensing Technical Field The invention relates to the technical field of bioelectronics, in particular to application of a flexible bioelectronic device in bioelectric signal sensing. Background Flexible bioelectronics are increasingly important in the fields of health monitoring, early disease diagnosis, rehabilitation assistance, intelligent medical equipment and the like, and an indispensable communication bridge is provided for fusion and interaction between human beings and machines. Numerous flexible bioelectronic studies have focused on improvements in interface toughness, biocompatibility, antibacterial properties, electrical properties, mechanical properties, and the like. However, flexible bioelectronics, when applied in a dynamic environment where body fluids are abundant and unavoidable, face a further challenge in how to achieve high signal-to-noise ratio sensing. When the flexible bioelectrode is used for monitoring bioelectricity signals in a complex environment, dynamic interference can be introduced into a target signal to form signal artifacts, so that the signal-to-noise ratio of the signal is reduced. Therefore, a key bottleneck impeding the development of flexible bioelectronics technologies is that the bioelectronics applied in complex environments have electrical property mismatch with tissue interfaces, resulting in signal artifacts and non-ideal signal-to-noise ratios, which severely limit the application of flexible bioelectronics in complex in-vivo and in-vitro environments for long-term, stable, and high-precision requirements. In order to effectively improve the signal-to-noise ratio of flexible bioelectronic devices applied in wet dynamic physiological environments (such as body fluids, sweat, blood, and tissue interfaces), researchers have explored many ways, and the main technical routes can be summarized into the following two categories: The first type of strategy focuses on device-organism interface optimization. The method has the core thought that interface impedance is reduced by enhancing interface toughness, so that fidelity and stability of signal transmission are improved. Specific implementation methods include, but are not limited to, introducing chemical bonds (such as covalent bonds, coordination bonds) and dynamic weak bonds (such as hydrogen bonds, ionic bonds, and host-guest interactions) to build a firm interface, forming an interpenetrating network structure by using the physical entanglement between a molecular topology structure and a high molecular chain to enhance the interfacial interactions, designing micro-nano-scale geometrical structures (such as microneedles and porous films) to increase the contact area and using a mechanical interlocking effect to increase the interfacial adhesion, and performing functional doping modification on conductive materials (such as hydrogels and elastomers) to synchronously optimize the electrical and mechanical properties. However, the strategy of interface optimization has a fundamental limitation that the transmission impedance of target bioelectric signals (such as nerve action potential and electromyographic signals) is reduced, and meanwhile, the transmission impedance of various dynamic interference signals (such as motion artifacts, electrode-skin interface fluctuation and environmental electromagnetic noise) in the environment is also reduced indiscriminately. As a result, although the overall signal amplitude is often increased, the actual improvement effect of the signal-to-noise ratio is limited, and the target signal is still submerged in the noise background of the synchronous amplification. The second strategy is to turn to back-end signal processing, i.e., after signal acquisition, to passively filter out dynamic interference by a digital filtering algorithm or an external hardware filtering circuit (e.g., an RC low-pass filter). The method has the advantages of mature technology and flexible design. However, the disadvantages are also remarkable, namely, when the frequency component of the interference signal overlaps with the frequency band of the target bioelectric signal (namely, spectrum aliasing exists), the noise is difficult to effectively peel off by the traditional linear filtering method on the premise of not damaging the useful signal, and the inherent contradiction between the filtering precision and the signal fidelity exists. Second, both the computational process of digital filtering and the response time of hardware filtering inevitably introduce certain signal delays, which are unacceptable for bioelectronic applications requiring real-time feedback (e.g., closed-loop neuromodulation, real-time prosthetic control). In addition, the external filtering hardware increases the volume, power consumption and complexity of the system, which is contrary to the original design of the flexible bioelectric device, which is light, th