More people are physically active due to the Sweatcoin app which rewards you for walking – researchers at the Institute of Digital Healthcare, WMG at the University of Warwick have found. Sweatcoin gets people outdoors and walking to earn a virtual currency to spend in their marketplace.
Reaching your target number of steps a day is a little easier for those using the app called Sweatcoin which rewards users with a virtual currency for walking.
Sweatcoin works by converting the number of steps recorded on your phone into a virtual currency of Sweatcoins.
Every 1,000 steps generate 0.95 Sweatcoins and these can be used to purchase products on the in-app marketplace, (with prices ranging from 5 to 20,000 Sweatcoins), in local shops, or be transferred between other users.
Currently, steps recorded outdoors are rewarded due to the use of a GPS-based verification algorithm used to stop people cheating their phone’s step-counting algorithm.
The Institute of Digital Healthcare, WMG at the University of Warwick analysed daily step count data from 6000 users of the app, and found that there was a sustained average increase of nearly 20% in daily step count over a 6-month period after users had registered with the app, in comparison with a 3-month period prior to downloading the app.
Following a survey on a sample of the original 6000 users, those who were classified as less physically active and overweight were found to be most likely to increase their daily step count when using the app, meaning that Sweatcoin was having impact on an important section of the population who previously had low levels of physical activity.
Dr Mark Elliott, Assistant Professor at the Institute of Digital Healthcare, WMG - University of Warwick comments:
“We were delighted to have the opportunity to work with Sweatcoin and investigate how their app impacts on physical activity behaviour change. By analysing the daily step count data from a sample of Sweatcoin users and combining this with data from the surveys and focus groups facilitated by our researchers, we were able to identify which types of user had shown the biggest change in terms of increased physical activity from using the app.”
Anton Derlyatka co-founder at Sweatcoin comments:
"Incentivising people to walk more is key to improving levels of sustained physical activity. Yet, traditional ideas such as providing educational seminars or discounted gym passes, just don’t deliver. The University of Warwick found that an economy built on movement, as created by Sweatcoin, establishes sustained motivation for people to be more active. For an increasingly sedentary population facing an obesity and wellness crisis, these are significant findings.”
Lord Philip Hunt, Sweatcoin Advisory board member commented:
“Most health apps and initiatives tend to be aimed at those who are already active. Sweatcoin has huge potential in encouraging and incentivising non-active people to get walking. Given the health gains that can be achieved through increased physical activity, this is the kind of breakthrough we need to help motivate who can benefit most.”
A new innovation hub is being launched at WMG in partnership with GEFCO today. The Hub will focus on cutting edge research into the future of automotive supply chains, the dual challenges of electrification and using and reusing resources for as long as possible.
The hub is closely linked to the ESRC (Economic and Social Research Council) funded Centre for Doctoral Training at the University of Warwick.
The first two projects will research new circular business models for the supply, refurbishment and re-use of batteries for the electric automotive supply chain, and the use of new technologies to design fully-traceable and re-usable packaging.
A third project will examine the opportunities for logistics service providers to expand their business models to offer supply chain finance complimentary to out-sourcing of material and information flows.
Professor Janet Godsell, from the Supply Chain Research Group, WMG, University of Warwick will head up the new hub, she comments: “Digital technology provides an opportunity to re-think the way in which we do business, and blurs the traditional distinction between manufacturing and logistics. A distinction further blurred as we seek to develop new business models that more holistically consider reuse, repair, remanufacture and recycling.”
Helen Grover, Human Resources Director at GEFCO UK comments:
“We are delighted to work with GEFCO to launch their Supply Chain Innovation Hub at WMG, University of Warwick. This £180k investment will support GEFCO to provide leading edge digital supply chain solutions that meet their customer needs in a cost effective and sustainable way.
“We are looking forward to working with WMG, University of Warwick because it allows us to be involved with cutting edge research and puts us at the forefront of the future of sustainable manufacture and logistics. The partnership sits perfectly with our company ethos of always seeking new innovative solutions to maintain our growth and to improve the way our industry works”.
At GEFCO, we believe long-lasting cooperation with partners is the key to shared growth. Building on 69 years of expertise and a strong heritage in the automotive industry, we design smart, flexible solutions for complex supply chains. Today, the GEFCO Group is the European leader in automotive logistics, and a top 10 global partner in multimodal supply chain solutions.
The Group is present in 47 countries, includes over 300 destinations in its current network and employs 13,000 people globally. GEFCO reported a turnover of €4.4 billion in 2017.
GEFCO has been present in the UK since 1981. With headquarters located in Coventry, GEFCO UK employs 600 people in 18 sites. https://uk.gefco.net/
Website: www.gefco.net; Twitter: @GEFCO_Group
Professor Jan Godsell
New research has found that a novel Artificial Intelligence (AI) system can dramatically reduce the time needed to ensure that abnormal chest X-rays with critical findings will receive an expert radiologist opinion sooner, cutting the average delay from 11 days to less than 3 days. Chest X-rays are routinely performed to diagnose and monitor a wide range of conditions affecting the lungs, heart, bones, and soft tissues.
Researchers from WMG at the University of Warwick, working with Guy’s and St Thomas’ NHS Hospitals, extracted a dataset of half million anonymised adult chest radiographs (X-rays) and developed an AI system for computer vision that can recognise radiological abnormalities in the X-rays in real-time and suggest how quickly these exams should be reported by a radiologist. In the process of building the AI system, the team developed and validated a Natural Language Processing (NLP) algorithm that can read a radiological report, understand the findings mentioned by the reporting radiologist, and automatically infer the priority level of the exam. By applying this algorithm to the historical exams, the team generated a large volume of training exams that allowed the AI system to understand which visual patterns in X-rays were predictive of their urgency level.
The research team, led by Professor Giovanni Montana, Chair in Data Science in WMG at the University of Warwick, found that normal chest radiographs were detected with a positive predicted value of 73% and a negative predicted value of 99%, and at a speed that meant that abnormal radiographs with critical findings could be prioritised to receive an expert radiologist opinion much sooner than the usual practice.
The results of the research are published today, 22nd January 2019 in the leading journal Radiology in a paper entitled “Automated triaging and prioritization of adult chest radiographs using deep artificial neural networks.”
WMG’s Professor Giovanni Montana said:
“Artificial intelligence led reporting of imaging could be a valuable tool to improve department workflow and workforce efficiency. The increasing clinical demands on radiology departments worldwide has challenged current service delivery models, particularly in publicly-funded healthcare systems. It is no longer feasible for many Radiology departments with their current staffing level to report all acquired plain radiographs in a timely manner, leading to large backlogs of unreported studies. In the United Kingdom, it is estimated that at any time there are over 300,000 radiographs waiting over 30 days for reporting. The results of this research shows that alternative models of care, such as computer vision algorithms, could be used to greatly reduce delays in the process of identifying and acting on abnormal X-rays - particularly for chest radiographs which account for 40% of all diagnostic imaging performed worldwide. The application of these technologies also extends to many other imaging modalities including MRI and CT.”
Note for Editors:
All historical radiographs in our dataset were formally reported by one of 276 different reporters including board-certified radiologists, trainee radiologists and accredited reporting radiographers. The reports and images used in this study were anonymized prior to modelling thus did not contain any referral information or patient-identifying data.
Professor Giovanni Montana