Signal and information processing for sensing systems group · Santiago Marco
Current smart instrumentation using multi-sensors and/or spectrometers provides a wealth of data that requires sophisticated signal and data processing approaches to extract the hidden information.
In this context, we are interested in intelligent chemical instruments for the detection of volatile compounds and smells. These systems can be based on an array of nonspecific chemical sensors with a pattern recognition engine, taking inspiration from the olfactory system. Some spectrometries, e.g. Ion Mobility Spectrometry, are capable of very fast analysis with good detection limits but poor selectivity.
Our group develops algorithmic solutions for the automatic processing of Gas Sensor Array, Gas Chromatography – Ion Mobility Spectrometry (IMS) and Gas Chromatography – Mass Spectrometry (GC-MS) data for metabolomics and food samples.
In the present PhD thesis, the intention is to develop a device for human augmented olfaction. The device will have the form of an ergonomic mask that a human may wear. When wearing this mask, the human will be able to smell odourless substances, or he will be able to smell odorous emissions that are remote. Using this mask, the human with augmented olfaction capabilities will be able to detect the presence of hazardous odourless volatiles or gases, or he will be able to pilot a drone and report on the odor intensity distribution in the areas under surveillance. In such a way, it will be possible to have an odorous impression relative to areas that cannot be safely reached by humans. The main idea behind is the possibility to combine or connect electronic noses and olfactory displays in a single system. Beyond basic functionality, the project will propose figures of merit to be able to have specifications for this type of novel devices. Special attention will be devoted to portability aspects of the developed instrumentation so it can be easily embedded in the mask-
The PhD student will be in charge of doing a survey on artificial olfaction and olfactory displays technologies. He/She will build tailored electronic systems for the application and implementing the right signal and data processing algorithms for the sensor signals and for the automatic control of the olfactory display. He/She will envision scenarios to show new capabilities that humans can undertake when having augmented olfaction capabilities. This will consider two aspects: smelling odorless compounds and smell remote odors. Beyond the engineering aspects the candidate will also explore the fundamental aspects related to understanding odor coding by biological and artificial olfactory systems. Aspects related to odor receptor ranges, distribution of sensitivities and mixture effects will be explored both with simulations and practical experiments.
The PhD candidate should be able to work autonomously in a multidisciplinary environment at the intersection of electronics, biology and chemistry. He/She should be able to build prototypes for chemical sensor systems, including signal conditioning and signal acquisition and he/she will need to devise and automate small olfactory displays that can be based on different vaporization principles. Finally, the candidate will develop machine learning algorithms to interpret the sensor readings and infer the required excitation of the olfactory display to facilitate a natural smelling sensation by the individual wearing the mask. The candidate will need to fabricate custom pieces using 3D printers or alternative fabrication technologies.
Finally, the candidate will need to have the right communication skills to convey the possibilities offered by this new concept to the scientific community and the general public, either in oral or written form. The use of infographics, videos and other technologies to disseminate the advances made will be encouraged.