血液酒精浓度(BAC)是判别酒后驾车的法定指标，但现有的各类酒驾检测方法均无法满足现场快速准确测定BAC的要求。实际上，饮酒所致血液流变、导电特性的变化可分别通过阻抗血流图(IPG)和生物电阻抗谱(BIS)技术探测。鉴于此，本项目拟将BIS与IPG技术相结合，提出全新的阻抗谱血流图(ISPG)技术和基于ISPG测量的酒驾快速定量评估方法，研究包括：①提出整周期采样理论和BIS超快(亚毫秒级)测量法，并以此构建ISPG测量系统；②设计饮酒对比测量试验，记录若干心动周期的ISPG数据，通过分析ISPG波形特征得到血流动力学参数，拟合ΔZ阻抗谱的Cole阻抗模型得到血液成分参数；③建立基于偏最小二乘(PLS)-Elman神经网络的BAC预测模型，实现BAC的定量评估。本项目提出的整周期采样理论、BIS超快测量法及基于ISPG测量的BAC定量评估方法均属原创，具有较高的学术价值和可预期的应用前景。

Blood alcohol concentration (BAC) is the legal indicator of drunk-driving judgement. However, all sorts of present drunk-driving detecting methods can not reach the requirement of fast and accurate measurement of BAC used on the spot. In fact, drinking-caused blood hemorheological changes and conductive characteristic changes can be detected by impedance plethysmography (IPG) and bioimepdance spectroscopy (BIS), respectively. Based on this vision, a novel IPG-BIS combined impedance spectroscopy plethysmography (ISPG) measurement method is proposed in this project, aiming to fast and quantitatively evaluate drunk-driving. The main researches include: ① An integer-period sampling theory and an ultra-fast (in sub-millisecond scale) BIS measurement method based on this theory are proposed, and then a new ISPG measurement system is constructed. ② Design human drink contrasting measurement experiments by recording the ISPG data of several heartbeat cycles, then obtain both the haemodynamic parameters through ISPG waveform characteristics extraction and the blood component parameters by Cole-model fitting on ΔZ BIS data. ③ Based on the two types of parameters, a BAC prediction model based on partial least square (PLS) combined with Elman neural network algorithm is established, and quantitative evaluation of BAC is ultimately realized. The newly-proposed integer-period sampling theory, the ultra-fast BIS measurement method, and the BAC fast and quantitative drunk-driving assessment method are all original researches, which have high academic value and expectable application prospects.