Wireless Intraocular Pressure Sensing Using Microfabricated Minimally Invasive Flexible-Coiled LC Sensor Implant

This paper presents an implant-based wireless pressure sensing paradigm for long-range continuous intraocular pressure (IOP) monitoring of glaucoma patients. An implantable parylene-based pressure sensor has been developed, featuring an electrical LC-tank resonant circuit for passive wireless sensing without power consumption on the implanted site. The sensor is microfabricated with the use of parylene C (poly-chlorop- xylylene) to create a flexible coil substrate that can be folded for smaller physical form factor so as to achieve minimally invasive implantation, while stretched back without damage for enhanced inductive sensor–reader coil coupling so as to achieve strong sensing signal. A data-processed external readout method has also been developed to support pressure measurements. By incorporating the LC sensor and the readout method, wireless pressure sensing with 1-mmHg resolution in longer than 2-cm distance is successfully demonstrated. Other than extensive on-bench characterization, device testing through six-month chronic in vivo and acute ex vivo animal studies has verified the feasibility and efficacy of the sensor implant in the surgical aspect, including robust fixation and long-term biocompatibility in the intraocular environment. With meeting specifications of practical wireless pressure sensing and further reader development, this sensing methodology is promising for continuous, convenient, direct, and faithful IOP monitoring

Assessment of avocado textural changes during ripening by using contactless air-coupled ultrasound

[EN] In the present study, the use of the air-coupled ultrasonic technique has been analysed as a new tool for the contactless assessment of the avocado post-harvest textural modifications during ripening. Thus, ultrasonic parameters, such as maximum wave amplitude and ultrasound velocity, and textural ones, such as hardness, elastic modulus and relaxation capacity, were measured on avocado slices. During ripening, avocado reduced its elastic modulus (from 2.29 +/- 0.75 to 0.16 +/- 0.08 MPa), became softer and became more viscoelastic, which was well described from zero and first-order kinetic models. These changes increased ultrasound attenuation, decreasing the maximum amplitude of the ultrasonic signal (from 336.6 to 55.4 V/m), while the ultrasonic velocity remained constant, between 320.1 +/- 6.9 and 316.4 +/- 82.6 m/s. Thereby, the maximum ultrasonic amplitude, which adequately correlated with textural parameters (r(avg) = 0.85), could be used to assess the post-harvest ripening on avocado slices.The authors acknowledge the financial support from the Ministerio de Economia y Competitividad (MINECO) and Agencia Estatal de InvestigaciOn in Spain (Project RTC-2017-6314-2) and the Generalitat Valenciana. M.D. Farifias is grateful to the European Social Fund (ESF 2014-2020) and Generalitat Valenciana for her post-doctoral fellowship (APOSTD/2018/203). The author E.A. Sanchez-Torres acknowledges the support of the undergraduate student Sara Serrano Garcia on the experimental work.Fernandez-Caballero-Fariñas, MD.; Sanchez-Torres, EA.; Sanchez-Jimenez, V.; Díaz, R.; Benedito Fort, JJ.; Garcia-Perez, J. (2021). Assessment of avocado textural changes during ripening by using contactless air-coupled ultrasound. Journal of Food Engineering. 289:1-9. https://doi.org/10.1016/j.jfoodeng.2020.1102661928

Frequency-modulated atomic force microscopy localises viscoelastic remodelling in the ageing sheep aorta

We gratefully acknowledge funding from the Royal Society for the provision of an International Travel Grant for Collaboration (R112205) to RA, and Wellcome Trust Value in People Award to RA and MJS. MJS and BD gratefully acknowledge the support of the Medical Research Council (www.mrc.ac.uk: grant reference G1001398)

A WIRELESS, PASSIVE SENSOR FOR MEASURING TEMPERATURE AT ORTHOPEDIC IMPLANT SITES FOR EARLY DIAGNOSIS OF INFECTIONS

Sensorized implants with embedded wireless, passive temperature sensors were developed for early detection of implant-associated infections. The operation principle of the sensor is based on the hypothesis that infections can lead to an increase in local temperature prior to the rise of body temperature. The sensor was an inductive capacitive (LC) circuit that has been used for monitoring of different parameters wirelessly, often in difficult to access environments. The sensor was fabricated on to an interference screw, which is used for tendon and ligament reconstruction surgeries. In this project, a sensorized interference screw was designed and fabricated by accommodating an LC sensor. Different designs of sensors and detection coils were made and tested for optimal performance. Infection at the site of an orthopedic implant is a serious challenge in the field of orthopedic surgery. These infections can lead to adverse health and economic burdens for the patients. The rate of failure of implants due to infections was around 2% to 2.4% during 2001-2009 period and rising. The treatment cost for orthopedic-associated infections has increased to 566 million USD in 2009 and is projected to 1.62 billion USD by 2020. Several techniques are used to evaluate infections, including X-rays radiography, bone scans, and lab blood tests, but primarily it is based on swelling and increased pain at the site of infection. Several studies have shown relations between temperature and infections, they focused on surface tissue layers and to our knowledge, there have been few similar studies in deeper layers. The goal of this project is to develop a device that can operate within deeper tissues

Bayesian changepoint analysis for atomic force microscopy and soft material indentation

Material indentation studies, in which a probe is brought into controlled physical contact with an experimental sample, have long been a primary means by which scientists characterize the mechanical properties of materials. More recently, the advent of atomic force microscopy, which operates on the same fundamental principle, has in turn revolutionized the nanoscale analysis of soft biomaterials such as cells and tissues. This paper addresses the inferential problems associated with material indentation and atomic force microscopy, through a framework for the changepoint analysis of pre- and post-contact data that is applicable to experiments across a variety of physical scales. A hierarchical Bayesian model is proposed to account for experimentally observed changepoint smoothness constraints and measurement error variability, with efficient Monte Carlo methods developed and employed to realize inference via posterior sampling for parameters such as Young's modulus, a key quantifier of material stiffness. These results are the first to provide the materials science community with rigorous inference procedures and uncertainty quantification, via optimized and fully automated high-throughput algorithms, implemented as the publicly available software package BayesCP. To demonstrate the consistent accuracy and wide applicability of this approach, results are shown for a variety of data sets from both macro- and micro-materials experiments--including silicone, neurons, and red blood cells--conducted by the authors and others.Comment: 20 pages, 6 figures; submitted for publicatio