Are Contact Lenses the Ultimate Computer Screen?

Imagine you have to make a speech, but instead of looking down at your notes, the words scroll in front of your eyes, whichever direction you look in. That’s just one of many features the makers of smart contact lenses promise will be available in the future.

Imagine… you’re a musician with your lyrics, or your chords, in front of your eyes. Or you’re an athlete and you have your biometrics and your distance and other information that you need,” says Steve Sinclair, from Mojo, which is developing smart contact lenses.
His company is about to embark on comprehensive testing of smart contact lens on humans, that will give the wearer a heads-up display that appears to float in front of their eyes.

The product’s scleral lens (a larger lens that extends to the whites of the eye) corrects the user’s vision, but also incorporates a tiny microLED display, smart sensors and solid-state batteries. “We’ve built what we call a feature-complete prototype that actually works and can be worn – we’re soon going to be testing that [out] internally,” says Mr Sinclair. “Now comes the interesting part, where we start to make optimisations for performance and power, and wear it for longer periods of time to prove that we can wear it all day.”

Other smart lenses are being developed to collect health data. Lenses could “include the ability to self-monitor and track intra-ocular pressure, or glucose,” says Rebecca Rojas, instructor of optometric science at Columbia University. Glucose levels for example, need to be closely monitored by people with diabetes. “They can also provide extended-release drug-delivery options, which is beneficial in diagnosis and treatment plans. It’s exciting to see how far technology has come, and the potential it offers to improve patients’ lives.

Research is underway to build lenses that can diagnose and treat medical conditions from eye conditions, to diabetes, or even cancer by tracking certain biomarkers such as light levels, cancer-related molecules or the amount of glucose in tears. A team at the University of Surrey, for example, has created a smart contact lens that contains a photo-detector for receiving optical information, a temperature sensor for diagnosing potential corneal disease and a glucose sensor monitoring the glucose levels in tear fluid.

Source: https://www.bbc.com/

How To Detect Heart Failure From A Single Heartbeat

Researchers have developed a neural network approach that can accurately identify congestive heart failure with 100% accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat, a new study reports.

Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and sustained healthcare costs, clinical practitioners and health systems urgently require efficient detection processes.

Dr Sebastiano Massaro, Associate Professor of Organisational Neuroscience at the University of Surrey, has worked with colleagues Mihaela Porumb and Dr Leandro Pecchia at the University of Warwick and Ernesto Iadanza at the University of Florence, to tackle these important concerns by using Convolutional Neural Networks (CNN) – hierarchical neural networks highly effective in recognising patterns and structures in data.

Published in Biomedical Signal Processing and Control Journal, their research drastically improves existing CHF detection methods typically focused on heart rate variability that, whilst effective, are time-consuming and prone to errors. Conversely, their new model uses a combination of advanced signal processing and machine learning tools on raw ECG signals, delivering 100% accuracy.

We trained and tested the CNN model on large publicly available ECG datasets featuring subjects with CHF as well as healthy, non-arrhythmic hearts. Our model delivered 100% accuracy: by checking just one heartbeat we are able detect whether or not a person has heart failure. Our model is also one of the first known to be able to identify the ECG’ s morphological features specifically associated to the severity of the condition,”  explains Dr Massaro.  Dr Pecchia, President at European Alliance for Medical and Biological Engineering, explains the implications of these findings: “With approximately 26 million people worldwide affected by a form of heart failure, our research presents a major advancement on the current methodology. Enabling clinical practitioners to access an accurate CHF detection tool can make a significant societal impact, with patients benefitting from early and more efficient diagnosis and easing pressures on NHS resources.”

Source: https://www.surrey.ac.uk/

Tool Speeds Up Manufacturing Of Powered Wearable

People could soon power items such as their mobile phones or personal health equipment by simply using their daily movements, thanks to a new research tool that could be used by manufacturers.

In a new paper published by Nano Energy, experts from the Advanced Technology Institute (ATI) at the University of Surrey (UK) detail a new  methodology that allows designers of smart-wearables to better understand and predict how their products would perform once manufactured and in use.

The technology is centred on materials that become electrically charged after they come into contact with each other, known as triboelectric materials – for example, a comb through hair can create an electrical charge. Triboelectric Nanogenerators (TENGs), use this static charge to harvest energy from movement through a process called electrostatic induction. Over the years, a variety of TENGs have been designed which can convert almost any type of movement into electricity. The University of Surrey’s tool gives manufacturers an accurate understanding of the output power their design would create once produced.

This follows the news earlier this year of the ATI announcing the creation of its £4million state-of-the-art Nano-Manufacturing Hub. The new facility will produce plastic nanoscale electronics for wearable sensors, electronic tags and other electronic devices.

Ishara Dharmasena, lead scientist on this project from the University of Surrey, said: “The future global energy mix will depend on renewable energy sources such as solar power, wind, motion, vibrations and tidal. TENGs are a leading technology to capture and convert motion energy into electricity, extremely useful in small scale energy harvesting applications. Our work will, for the first time, provide universal guidance to develop, compare and improve various TENG designs. We expect this technology in household and industrial electronic products, catering to a new generation of mobile and autonomous energy requirements.”

Source: https://www.surrey.ac.uk/