Electronic-Nose for Detecting Environmental Pollutants: Signal Processing and Analog Front-End Design
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Analog Integr Circ Sig Process (2012) 70:15–32 DOI 10.1007/s10470-011-9638-1 Electronic-nose for detecting environmental pollutants: signal processing and analog front-end design Hyuntae Kim • Bharatan Konnanath • Prasanna Sattigeri • Joseph Wang • Ashok Mulchandani • Nosang Myung • Marc A. Deshusses • Andreas Spanias • Bertan Bakkaloglu Received: 24 November 2010 / Revised: 18 February 2011 / Accepted: 24 March 2011 / Published online: 11 April 2011 Ó Springer Science+Business Media, LLC 2011 Abstract Environmental monitoring relies on compact, 1 Introduction portable sensor systems capable of detecting pollutants in real-time. An integrated chemical sensor array system is Diesel and gasoline internal combustion engines produce developed for detection and identification of environmental exhaust, which is a complex mixture of gases and fine pollutants in diesel and gasoline exhaust fumes. The system particles. Several previous studies have linked respiratory consists of a low noise floor analog front-end (AFE) fol- diseases and cancer to exposure to gasoline and diesel lowed by a signal processing stage. In this paper, we exhaust [1–4]. present techniques to detect, digitize, denoise and classify a National Institutes of Health (NIH) launched an initia- certain set of analytes. The proposed AFE reads out the tive for exploring the environmental roots of these diseases output of eight conductometric sensors and eight ampero- [5]. A reliable and reproducible quantitative measure of metric electrochemical sensors and achieves 91 dB SNR at exposure is required to establish a direct linkage of these 23.4 mW quiescent power consumption for all channels. diseases to diesel and/or gasoline exhaust. Traditionally the We demonstrate signal denoising using a discrete wavelet detection of environmental emissions has been performed transform based technique. Appropriate features are by using analytical instruments such as gas chromatogra- extracted from sensor data, and pattern classification phy/mass spectrometry (GC/MS) that are expensive, have methods are used to identify the analytes. Several existing high operating costs and require trained personnel [6]. pattern classification algorithms are used for analyte These techniques are not appropriate for real-time on-site detection and the comparative results are presented. operation. Electronic noses (e-noses), which rely on arrays of partially-selective chemical sensors for detection of Keywords Electronic nose Á Gas sensors Á Analog front volatile chemicals, are a portable and cost-effective alter- end Á ADC Á Chopper stabilization Á Feature extraction native [7]. In the past, e-noses have been used in diverse applications such as spoilage detection of foodstuffs [8, 9], disease diagnosis [10, 11] and process control [12]. Envi- ronmental monitoring has become an important area of application of e-noses during the past two decades due to H. Kim (&) Á B. Konnanath Á P. Sattigeri Á A. Spanias Á B. Bakkaloglu the increasing awareness of the effects of pollution on Arizona State University, Tempe, AZ 85287, USA human health and the quality of the environment [13]. e-mail: [email protected]; [email protected] Previously, electronic noses have been used for environ- mental monitoring in applications such as detection of J. Wang University of California-San Diego, San Diego, CA 92093, USA smoke compounds [14], the determination of indoor air quality [15] and odor emission rate of a compost hall [16]. A. Mulchandani Á N. Myung However they have not been applied for real-time exhaust University of California-Riverside, Riverside, CA 92501, USA monitoring problem. Monitoring a large number of pollu- M. A. Deshusses tant gases and particulates in the air is an emerging Duke University, Durham, NC 27708, USA application where the potential of the electronic nose is yet 123 16 Analog Integr Circ Sig Process (2012) 70:15–32 to be established. The introduction of the electronic nose for this task is very challenging. In addition to very com- plex target mixtures and low detection thresholds, varying ambient conditions such as temperature and humidity dis- tort the analyte signatures [13]. Thus, the classification method must be robust to changes in analyte concentration levels and environmental factors such as temperature and humidity. A mobile sensor system is being developed [17, 18] which is designed to be capable of monitoring up to 40 analytes in diesel and gasoline exhaust in real-time. The system is light-weight and low-cost and can be worn as a badge, similar to a radiation counter. These light-weight badges will each house an array of electrochemical nanosensors for detecting and measuring trace analytes in exhaust gases. This is in contrast to the current analytical techniques which are expensive, bulky Fig. 2 Proposed badge style sensor platform module and have significant power requirements. The system consists of: (c) data conversion circuits. (a) an array of partially selective conductometric and The surface of the chip provides a CE (counter elec- amperometric sensors which perform chemical trode), RE (reference electrode) and eight WE (working sensing, electrode) array for amperometric sensors. Also, the chip (b) an integrated microelectronic component for power provides gate voltage and current sweeping for eight FET management and data collection (i.e. the analog front- based conductometric sensors. end) After sensor data acquisition, the next steps in the signal (c) a signal processing module for automatic identifica- processing stage are denoising, feature extraction and tion of the pollutants. classification for which we have developed and imple- A block diagram of the system is illustrated in Fig. 1 mented customized algorithms. These algorithms have and its prototype badge style sensor platform is shown in been evaluated using data from two distinct real-life sce- Fig. 2. A reconfigurable analog front-end (AFE) sensor narios, namely; interface circuit provides data acquisition and interfaces to • The sensors are exposed to a pollutant (usually present the DSP microcontroller. The electrochemical micro-elec- in high concentration) for a long period of time, and as tronics supports a multi-channel electrochemical array with a result the sensors saturate and the outputs have a high performance amperometric and conductometric sen- steady-state value. sors. This sensor front-end consists of • The sensors are exposed to a pollutant gas for a short (a) low noise, programmable readout-amplifiers, period due to which we obtain a transient response (b) sensor stimuli DAC and consisting of peaks in the sensor output. CMOS ANALOG FRONT-END and OFF-CHIP DATA OFFLINE SENSOR INTERFACE STORAGE PROCESSING Amperometric Sensor Array Conductometric Sensor Array Power Pattern Management Classification Fig. 1 Block diagram of the proposed exhaust monitoring system 123 Analog Integr Circ Sig Process (2012) 70:15–32 17 Appropriate combinations of features and classification voltage converter, a resistor string digital-to-analog con- algorithms for each scenario have been tested offline using verter (DAC) and a nested chopped analog-to-digital con- Matlab. verter (ADC) for the amperometric sensor as shown in The rest of the paper is organized as follows. Section 2 Fig. 4. The gas sensor interface circuitry is made of a current presents the details of the analog front-end. Section 3 steering DAC, a resistor string DAC for sensor stimuli, and a describes the denoising approach. The feature extraction nested chopped low-offset ADC for the conductometric and classification techniques as well as the results obtained sensor in Fig. 6. The whole system operates with a supply on synthetic and experimental datasets are detailed in voltage of 1.8 V and is implemented in 0.18 lm CMOS Sects. 4 and 5 respectively. The last Sect. 6 presents con- process with one poly and six layers of metal. cluding remarks. 2.1 Amperometric sensor AFE: system implementation 2 Analog front-end design The amperometric sensor produces current output depending on gas concentration while the AFE applies a voltage To satisfy the size and power consumption requirements of between working electrodes (WEs) and reference electrode the measurement system, an integrated readout IC, data (RE). The applied voltage stimulus can determine sensing acquisition and data signal processing module are required. mode in amperometric sensor system such as pulse vol- The signal chain for the readout system is illustrated in tammetry or a cyclic voltammetry. In Fig. 4, a three bit Fig. 3(a). Figure 3(b) shows typical measurement setup for resistor string DAC is used as a stimulus for staircase vol- analog front-end (AFE) with both conductometric and tammetry. Stimuli sets the potential applied across the amperometric sensors. In a typical test application the vapor electrochemical cell and can be either constant voltage or to be tested is injected into the small chamber and AFE cyclic voltammetry measurement [19, 20, 44]. Based on delivers the electrical signals from chemical reaction with sensor response characterization, a 125 mV DC stair step gas sensors. The AFE consists of a potentiostat, a current-to- stimulus is generated to get reduction/oxidation between the Fig. 3 Diagram and bench characterization setup of exhaust gas detection AFE. a Block diagram. b Test setup CE RE FLASH WEs MEMORY MICRO 2:1 CONTROLLER Power Management (a) Inject gases Agilent 54641 WE Function Generator CE RE Microcontroller & SD card Agilent Logic Analyzer ADC Li-ion Battery CH1 CH2 CH3 CH4 (b) 123 18 Analog Integr Circ Sig Process (2012) 70:15–32 Reference Electrode (RE) and the selected Working Elec- amplifiers should have as high of a signal swing as possible. trode (WE), sweeping from -125 to 870 mV differential To achieve high swing, the operational amplifiers signal with respect to a reference electrode (RE) absolute should have rail-to-rail outputs and the operational ampli- potential of 1 V. However, the approach with DC constant fiers should drive the large double layer capacitor of voltage causes only oxidation of electrochemical gases to the CE and WE.