Sweat Biomarker Sensor Incorporating Picowatt, Three-Dimensional Extended Metal Gate Ion Sensitive Field Effect Transistors

Ion sensitive field effect transistors (ISFETs) form a very attractive solution for wearable sensors due to their capacity for ultra-miniaturization, low power operation, and very high sensitivity, supported by complementary metal oxide semiconductor (CMOS) integration. This paper reports for the first time, a multianalyte sensing platform that incorporates high performance, high yield, high robustness, three-dimensional-extended-metal-gate ISFETs (3D-EMG-ISFETs) realized by the postprocessing of a conventional 0.18 μm CMOS technology node. The detection of four analytes (pH, Na+, K+, and Ca2+) is reported with excellent sensitivities (58 mV/pH, −57 mV/dec(Na+), −48 mV/dec(K+), and −26 mV/dec(Ca2+)) close to the Nernstian limit, and high selectivity, achieved by the use of highly selective ion selective membranes based on postprocessing integration steps aimed at eliminating any significant sensor hysteresis and parasitics. We are reporting simultaneous time-dependent recording of multiple analytes, with high selectivities. In vitro real sweat tests are carried out to prove the validity of our sensors. The reported sensors have the lowest reported power consumption, being capable of operation down to 2 pW/sensor. Due to the ultralow power consumption of our ISFETs, we achieve and report a final four-analyte passive system demonstrator including the readout interface and the remote powering of the ISFET sensors, all powered by an radio frequency (RF) signal.

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Francesco Bellando, Mihai Adrian Ionescu, Pierpaolo Palestri, Luca Selmi, Junrui Zhang

Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power integrated sensors, very little is known about their noise characterization when being operated in a liquid gate configuration. The noise characteristics in various regimes of their operation are important to select the most suitable conditions for signal-to-noise ratio (SNR) and power consumption. This work reports systematic DC, transient, and noise characterizations and models of a back-end of line (B)-modified foundry-made ISFET used as pH sensor. The aim is to determine the sensor sensitivity and resolution to pH changes and to calibrate numerical and lumped element models, capable of supporting the interpretation of the experimental findings. The experimental sensitivity is approximately 40 mV/pH with a normalized resolution of 5 mpH per µm2, in agreement with the literature state of the art. Differences in the drain current noise spectra between the ISFET and MOSFET configurations of the same device at low currents (weak inversion) suggest that the chemical noise produced by the random binding/unbinding of the H+ ions on the sensor surface is likely the dominant noise contribution in this regime. In contrast, at high currents (strong inversion), the two configurations provide similar drain noise levels suggesting that the noise originates in the underlying FET rather than in the sensing region.

2021

Assessment of Foot Signature Using Wearable Sensors for Clinical Gait Analysis and Real-Time Activity Recognition

Benoît Mariani

Locomotion is one of the most important abilities of humans. Actually, gait locomotion provides mobility, and symbolizes freedom and independence. However, gait can be affected by several pathologies, due to aging, neurodegenerative disease, or trauma. The evaluation and treatment of mobility diseases thus requires clinical gait assessment, which is commonly done by using either qualitative analysis based on subjective observations and questionnaires, or expensive analysis established in complex motion laboratories settings. This thesis presents a new wearable system and algorithmic methods for gait assessment in natural conditions, addressing the limitations of existing methods. The proposed system provides quantitative assessment of gait performance through simple and precise outcome measures. The system includes wireless inertial sensors worn on the foot, that record data unobtrusively over long periods of time without interfering with subject's walking. Signal processing algorithms are presented for the automatic calibration and online virtual alignment of sensor signals, the detection of temporal parameters and gait phases, and the estimation of 3D foot kinematics during gait based on fusion methods and biomechanical assumptions. The resulting 3D foot trajectory during one gait cycle is defined as Foot Signature, by analogy with hand-written signature. Spatio-temporal parameters of interest in clinical assessment are derived from foot signature, including commonly parameters, such as stride velocity and gait cycle time, as well as original parameters describing inner-stance phases of gait, foot clearance, and turning. Algorithms based on expert and machine learning methods have been also adapted and implemented in real-time to provide input features to recognize locomotion activities including level walking, stairs, and ramp locomotion. Technical validation of the presented methods against gold standard systems was carried out using experimental protocols on subjects with normal and abnormal gait. Temporal aspects and quantitative estimation of foot-flat were evaluated against pressure insoles in subjects with ankle treatments during long-term gait. Furthermore, spatial parameters and foot clearance were compared in young and elderly persons to data obtained from an optical motion capture system during forward gait trials at various speeds. Finally, turning was evaluated in children with cerebral palsy and people with Parkinson's disease against optical motion capture data captured during timed up and go and figure-of-8 tests. Overall, the results demonstrated that the presently proposed system and methods were precise and accurate, and showed agreement with reference systems as well as with clinical evaluations of subjects' mobility disease using classical scores. Currently, no other methods based on wearable sensors have been validated with such precision to measure foot signature and subsequent parameters during unconstrained walking. Finally, we have used the proposed system in a large-scale clinical application involving more than 1800 subjects from age 7 to 77. This analysis provides reference data of common and original gait parameters, as well as their relationship with walking speed, and allows comparisons between different groups of subjects with normal and abnormal gait. Since the presented methods can be used with any foot-worn inertial sensors, or even combined with other systems, we believe our work to open the door to objective and quantitative routine gait evaluations in clinical settings for supporting diagnosis. Furthermore, the present studies have high potential for further research related to rehabilitation based on real-time devices, the investigation of new parameters' significance and their association with various mobility diseases, as well as for the evaluation of clinical interventions.

EPFL2012

Wearable System with Integrated Passive Microfluidics for Real-Time Electrolyte Sensing in Human Sweat

Erick Antonio Garcia Cordero

Wearable systems embodied as patches could offer noninvasive and real-time solutions for monitoring of biomarkers in human sweat as an alternative to blood testing, with applications in personalized and preventive healthcare. Sweat is considered to be a biofluid of foremost interest for analysis due the numerous biomarkers it contains. Recent studies have demonstrated that the concentration of some of these biomarkers in sweat, such as the electrolytes studied in this work, can be directly correlated to their concentrations in blood, making sweat a trusted biofluid candidate for non-invasive diagnostics. Until now, the biggest impediment to onâbody sweat monitoring was the lack of technology to analyze sweat composition in realâtime and mainly to continuously collect it. The goal of this work was to develop the building blocks of such wearable system for sweat electrolyte monitoring, with main emphasis on the passive microfluidics, the integrated miniaturized quasi-reference electrode and the functionalization of the sensing devices. The basic sensor technology is formed by Ion Sensitive Field Effect Transistors (ISFET) realized in FinFET and ultra-thin body Silicon on Insulator technology. This thesis shows the development of a state-of-the-art microsystem that allows multisensing of pH, Na+, K+ electrolyte concentrations in sweat, with high selectivity and high sensitivities (â50 mV/dec for all electrolytes), in a wearable fashion. The microsystem comprises a biocompatible skin interface that collects even infinitesimal quantities of sweat (of the order of hundreds of picoliters to tenths of nanoliters), which the body produces in periods of low physical effort. One of the main achievements of this work is the integration of Ion Sensing Fully Depleted FETs and zero power consumption microfluidics, enabling low power (less than 50 nWatts/sensor) wearable biosensing. The thesis presents the needed technological processes and optimizations, together with their characterization, in order to achieve a Lab-On-Skin system.