Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning

Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anaesthesiologist and patient with continuous drug monitoring. Direct detection of drugs is achieved with electrochemical techniques, and several options are present in literature to measure propofol (widely used anaesthetics). Still, the sensors proposed do not enable in-situ detection, they do not provide this information continuously, and they are based on bulky and costly lab equipment. In this paper, we present a novel smart pen-shaped electronic system for continuous monitoring of propofol in human serum. The system consists of a needle-shaped sensor, a quasi digital front-end, a smart machine learning data processing, in a single wireless battery-operated embedded device featuring Bluetooth Low Energy (BLE) communication. The system has been tested and characterized in real, undiluted human serum, at 37 ∘ C. The device features a limit of detection of 3.8 μ M, meeting the requirement of the target application, with an electronics system 59% smaller and 81% less power consuming w.r.t. the state-of-the-art, using a smart machine learning classification for data processing, which guarantees up to twenty continuous measure.

Multi-Channel Front-End for Electrochemical Sensing of Metabolites, Drugs, and Electrolytes

Sandro Carrara, Francesca Criscuolo, Giovanni De Micheli, Mandresy Ivan Ny Hanitra, Nadezda Pankratova

A multi-channel front-end for electrochemical sensing is presented. It consists of a multiplexed four-channel readout interface supporting amperometric, voltammetric, and potentiometric measurements. The electronic interface is co-designed according to the target biomarker specifications, and exhibits excellent linearity in both current and voltage sensing. The sensing front-end is characterized with lactate, paracetamol, and lithium sensing, yielding sensitivity of 1.2 ± 0.3 μ A/mM, 69.6 ± 2 nA/μM, and 55.6 mV/decade, respectively. These performances are comparable with the ones obtained with a bulky commercial Autolab potentiostat. Moreover, the limit of detection achieved are of 37 ± 8 μM, 2.1 ± 1.22 μM, and 11 ± 3.5 μM, respectively, for the aforementioned sensors. These values are more than one order of magnitude lower than the relevant detection range. This successful characterization demonstrates the ability of the proposed system to monitor, in a broader sense, metabolites, drugs, and electrolytes. The programmability, versatility and portability of the front-end interface paves the way for a continuous monitoring of different families of biomarkers, suitable for advanced healthcare diagnosis and wearable physiology.

2020

Contribution à l'étude des modes de rayonnement acoustique d'une structure

Olivier Schevin

Noise radiated by different industrial structures that surround us in daily life are more and more considered as environmental pollution. Standards defining a tolerable sound level for each of these noise sources are regularly called into question and respecting them becomes an additional constraint for manufacturers. The last decades have seen the increasing development of means used to fight these noise disturbances. The wide diversity of noises perceived as harmful has contributed to the progressive increase in specificity and efficiency of solutions proposed to reduce the disturbances. For some applications, passive solutions, based on the use of materials capable of absorbing or deviating acoustic or vibratory waves, have progressively been replaced by "active" solutions, based on the generation of an acoustic wave of opposite phase to the disturbing one radiated by the noise source. Power transformers are sources for which passive solutions (anti-noise walls) are usually expensive and not very efficient, particularly at low frequency. Furthermore, characteristics of noise radiated by transformers (low frequency tone noise) are such that they are particularly well suited for the implementation of an active solution. Typically, an active control system dedicated to transformers (feedforward) is composed of actuators, used to generate the anti-noise and usually located near the tank, sensors, used to measure the attenuation obtained and to provide a reference signal, and a controller used to drive the actuators as a function of the information collected by the sensors. When the sensors are microphones, they are usually moved away from the noise source, in such a way that they pick up acoustic pressure that is representative of the noise propagated far away. In the vicinity of the source, local acoustic phenomena can occur which are not propagated far away. A microphone located near the noise source would therefore pick up an acoustic pressure that did not necessarily represent the one that effectively exists far away, the area where we are in fact seeking to reduce the noise. These phenomena, frequently grouped under the term "nearfield" tend to decrease the performance of the control system, owing to the fact that the controller seeks in this case to reduce an acoustic pressure which is not representative of the noise to be reduced. In practice, the significant amount of wiring required as a result of the positioning of the microphones in the far field, has a non-negligible effect on the cost of the system. The possibility of bringing the sensors closer to the source is sufficiently advantageous to envisage to studying the feasibility and the resulting consequences. The present approach consists in representing the primary field radiated by a vibrating structure in terms of a set of "acoustic radiation modes". The use of radiation modes to characterise the behaviour of a structure has received increasing attention since the beginning of 90's, especially for active control applications. Usually, this approach consists in representing the radiated power in terms of a set of surface velocity distributions, called radiation modes, that have the property of radiating independently of each other. Radiation modes result from diagonalization of a discrete expression of the radiation operator. We propose here to study the consequences on the radiation modes of a structure from bringing the microphones closer to it. We will study how the acoustic field varies with the distance and how this can be used to obtain a model, the complexity of which is adapted to the observation distance.

EPFL2001

Rate allocation and optimized decoding in inter-session network coding

Eirina Bourtsoulatze

Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offers a best effort mechanism for data delivery. The emergence of new distributed network architectures, such as peer-to-peer networks and wireless mesh networks, and the need for efficient data delivery mechanisms have motivated researchers to reconsider the way that information is communicated and processed in the networks. This has given rise to a new research field called network coding. The network coding paradigm departs from the traditional routing principle where information is simply relayed by the network nodes towards the destination, and introduces some intelligence in the network through coding at the intermediate nodes. This in-network data processing has been proved to substantially improve the performance of data delivery systems in terms of throughput and error resilience in networks with high path diversity. Motivated by the promising results in the network coding research, we focus in this thesis on the design of network coding algorithms for simultaneous transmission of multiple data sources in overlay networks. We investigate several problems that arise in the context of inter-session network coding, namely (i) decoding delay minimization in inter-session network coding, (ii) distributed rate allocation for inter-session network coding and (iii) correlation-aware decoding of incomplete network coded data. We start by proposing a novel framework for data delivery from multiple sources to multiple clients in an overlay wireline network, where intermediate nodes employ randomized inter-session network coding. We consider networks with high resource diversity, which creates network coding opportunities with possibly large gains in terms of throughput, delay and error robustness. However, the coding operations in the intermediate nodes must be carefully designed in order to enable efficient data delivery. We look at the problem from the decoding delay perspective and design solutions that lead to a small decoding delay at clients through proper coding and rate allocation. We cast the optimization problem as a rate allocation problem, which seeks for the coding operations that minimize the average decoding delay in the client population. We demonstrate the validity of our algorithm through simulations in representative network topologies. The results show that an effective combination of intra- and inter-session network coding based on randomized linear coding permits to reach small decoding delays and to better exploit the available network resources even in challenging network settings. Next, we design a distributed rate allocation algorithm where the users decide locally how many intra- and inter-session network coded packets should be requested from the parent nodes in order to get minimal decoding delay. The capability to take coding decisions locally with only a partial knowledge of the network statistics is of crucial importance for applications where users are organized in dynamic overlay networks. We propose a receiver-driven communication protocol that operates in two rounds. First, the users request and obtain information regarding the network conditions and packet availability in their local neighborhood. Then, every user independently optimizes the rate allocation among different possible intra- and inter-session packet combinations to be requested from its parents. We also introduce the novel concept of equivalent flows, which permits to efficiently estimate the expected number of packets that are necessary for decoding and hence to simplify the rate allocation process. Experimental results indicate that our algorithm is capable of eliminating the bottlenecks and reducing the decoding delay of users with limited resources. We further investigate the application of the proposed distributed rate allocation algorithm to the transmission of video sequences and validate the performance of our system using the NS-3 simulator. The simulation results show that the proposed rate allocation algorithm is successful in improving the quality of the delivered video compared to intra-session network coding based solutions. Finally, we investigate the problem of decoding the source information from an incomplete set of network coded data with the help of source priors in a finite algebraic field. The inability to form a complete decoding system can be often caused by transmission losses or timing constraints imposed by the application. In this case, exact reconstruction of the source data by conventional algorithms such as Gaussian elimination is not feasible; however, partial recovery of the source data may still be possible, which can be useful in applications where approximate reconstruction is informative. We use the statistical characteristics of the source data in order to perform approximate decoding. We first analyze the performance of a hypothetical maximum a posteriori decoder, which recovers the source data from an incomplete set of network coded data given the joint statistics of the sources. We derive an upper bound on the probability of erroneous source sequence decoding as a function of the system parameters. We then propose a constructive solution to the approximate decoding problem and design an iterative decoding algorithm based on message passing, which jointly considers the network coding and the correlation constraints. We illustrate the performance of our decoding algorithm through extensive simulations on synthetic and real data sets. The results demonstrate that, even by using a simple correlation model expressed as a correlation noise between pairs of sources, the original source data can be partially decoded in practice from an incomplete set of network coded symbols. Overall, this thesis addresses several important issues related to the design of efficient data delivery methods with inter-session network coding. Our novel framework for decoding delay minimization can impact the development of practical inter-session network coding algorithms that are appropriate for applications with low delay requirements. Our rate allocation algorithms are able to exploit the high resource diversity of modern networking systems and represent an effective alternative in the development of distributed communication systems. Finally, our algorithm for data recovery from incomplete network coded data using correlation priors can contribute significantly to the improvement of the delivered data quality and provide new insights towards the design of joint source and network coding algorithms.