适合于穿戴应用的多道通用电生理采集系统

Multi-channel general bioelectric acquisition system for wearable applications

随着移动医疗概念的普及,电生理采集系统的可穿戴性设计已成为研究热点。然而,人体的电生理信号的幅值非常微弱,甚至低至数十微伏,特别在运动状态的人体上,电生理信号常常被淹没在各种各样的干扰和噪声中,难以检测和提取。同时,穿戴性应用对采集模块的体积、电路复杂性、耗电及抗干扰能力等方面提出苛刻要求。本文就此提出一种新型的多道通用电生理信号采集系统,不仅对微幅级的微弱电生理信号保持足够高的分辨度,且具有大动态范围,能有效完成在高噪声、强运动伪迹干扰的情况下的多电生理信号采集。系统结构上分为采集端和移动计算平台两部分,通过蓝牙完成上下位机之间的通信。其中采集端采用低功耗单片机MSP430结合24 bit的?-∑型模数转换器完成信号采集,除模数转换器前面必须使用的抗混叠滤波器外,前端再无任何模拟处理电路。在移动计算平台上,基于LabVIEW开发环境设计程序作为信号处理节点,既用作控制界面,又用作信号处理器。多实验证明系统具有通用性强,最多可四通道同时采集,系统噪声低至3μV,动态范围高于±300 mv,且对微弱信号保持高分辨能力的特点,非常适合于穿戴应用,在移动医疗领域具有重要的应用价值。

With the popularity of mobile health care, the design of wearable bioelectric signal acquisition system has been one of the hot research area. However, the bioelectric signals of human body usually has very weak amplitude, even as small as tens of microvolts. And the weak signals of human in motion state is rather difficult to be detected and collected for the signals are almost submerged in a variety of interference and noise. The wearable applications has strict demand on the volume of acquisition module, circuit complexity, power consumption, resostance to interference. A new multi-channel general bioelectric acquisition system was introduced in this paper, with a high enough resolution for week bioelectrie signal of micro-amplitude, large dynamic rang, effectively completing the bioelectri signal acquisition under artifact interference of strong noise and movements. The new system consists of two parts： collector and mobile platform intercommunicated by Bluetooth. The collector collected bioelectric signal by low power consumption single-chip microcomputer MSP430, combined with 24 bit △-∑ analog-digital converter （ADC）. There was no any other analog processing circuits, except for anti-aliasing filters which were necessary for ADC. LabVIEW-based Graphical User Interface （GUI） designed on the mobile platform was used as control interface and signal processor. Experiments in this paper showed that the system could collect most of the bioelectric signals by maximal four channels in the same time. The system noise was as low as 3μV, and the dynamic range was greater than ±300 mv, with high resolution for the weak signals. This system is proved to be suitable for wearable applications, and it has important significance in the field of mobile health care.