̽��ֱ�� of Cambridge - computer model

Machine learning gives users ‘superhuman’ ability to open and control tools in virtual reality

sc604 — Wed, 08 Nov 2023 07:44:16 +0000

̽��ֱ��researchers, from the ̽��ֱ�� of Cambridge, used machine learning to develop ‘HotGestures’ – analogous to the hot keys used in many desktop applications.

HotGestures give users the ability to build figures and shapes in virtual reality without ever having to interact with a menu, helping them stay focused on a task without breaking their train of thought.

̽��ֱ��idea of being able to open and control tools in virtual reality has been a movie trope for decades, but the researchers say that this is the first time such a ‘superhuman’ ability has been made possible. ̽��ֱ��results are reported in the journal IEEE Transactions on Visualization and Computer Graphics.

Virtual reality (VR) and related applications have been touted as game-changers for years, but outside of gaming, their promise has not fully materialised. “Users gain some qualities when using VR, but very few people want to use it for an extended period of time,” said Professor Per Ola Kristensson from Cambridge’s Department of Engineering, who led the research. “Beyond the visual fatigue and ergonomic issues, VR isn’t really offering anything you can’t get in the real world.”

Most users of desktop software will be familiar with the concept of hot keys – command shortcuts such as ctrl-c to copy and ctrl-v to paste. While these shortcuts omit the need to open a menu to find the right tool or command, they rely on the user having the correct command memorised.

“We wanted to take the concept of hot keys and turn it into something more meaningful for virtual reality – something that wouldn’t rely on the user having a shortcut in their head already,” said Kristensson, who is also co-Director of the Centre for Human-Inspired Artificial Intelligence.

Instead of hot keys, Kristensson and his colleagues developed ‘HotGestures’, where users perform a gesture with their hand to open and control the tool they need in 3D virtual reality environments.

For example, performing a cutting motion opens the scissor tool, and the spray motion opens the spray can tool. There is no need for the user to open a menu to find the tool they need, or to remember a specific shortcut. Users can seamlessly switch between different tools by performing different gestures during a task, without having to pause their work to browse a menu or to press a button on a controller or keyboard.

“We all communicate using our hands in the real world, so it made sense to extend this form of communication to the virtual world,” said Kristensson.

For the study, the researchers built a neural network gesture recognition system that can recognise gestures by performing predictions on an incoming hand joint data stream. ̽��ֱ��system was built to recognise ten different gestures associated with building 3D models: pen, cube, cylinder, sphere, palette, spray, cut, scale, duplicate and delete.

̽��ֱ��team carried out two small studies where participants used HotGestures, menu commands or a combination. ̽��ֱ��gesture-based technique provided fast and effective shortcuts for tool selection and usage. Participants found HotGestures to be distinctive, fast, and easy to use while also complementing conventional menu-based interaction. ̽��ֱ��researchers designed the system so that there were no false activations – the gesture-based system was able to correctly recognise what was a command and what was normal hand movement. Overall, the gesture-based system was faster than a menu-based system.

“There is no VR system currently available that can do this,” said Kristensson. “If using VR is just like using a keyboard and a mouse, then what’s the point of using it? It needs to give you almost superhuman powers that you can’t get elsewhere.”

̽��ֱ��researchers have made the source code and dataset publicly available so that designers of VR applications can incorporate it into their products.

“We want this to be a standard way of interacting with VR,” said Kristensson. “We’ve had the tired old metaphor of the filing cabinet for decades. We need new ways of interacting with technology, and we think this is a step in that direction. When done right, VR can be like magic.”

̽��ֱ��research was supported in part by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Reference:
Zhaomou Song; John J Dudley; Per Ola Kristensson. ‘HotGestures: Complementing Command Selection and Use with Delimiter-Free Gesture-Based Shortcuts in Virtual Reality.’ IEEE Transactions on Visualization and Computer Graphics (2023). DOI: 10.1109/TVCG.2023.3320257

Researchers have developed a virtual reality application where a range of 3D modelling tools can be opened and controlled using just the movement of a user’s hand.

We need new ways of interacting with technology, and we think this is a step in that direction

Per Ola Kristensson

HotGestures give users ‘superhuman’ ability to open and control tools in virtual reality

̽��ֱ�� of Cambridge

Modelling a sailboat in virtual reality

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Researchers build more detailed picture of the movement of Greenland Ice Sheet

sc604 — Fri, 10 Feb 2023 15:14:39 +0000

Researchers have found that the movement of glaciers in Greenland is more complex than previously thought, with deformation in regions of warmer ice containing small amounts of water accounting for motion that had often been assumed to be caused by sliding where the ice meets the bedrock beneath.

Codecheck confirms reproducibility of COVID-19 model results

sc604 — Mon, 08 Jun 2020 23:00:01 +0000

̽��ֱ��code, script and documentation of the 16 March report, which is available on Github, was subject to an independent review led by Dr Stephen Eglen, from Cambridge’s Department of Applied Mathematics and Theoretical Physics.

Eglen co-founded Codecheck last year to help evaluate the computer programs behind scientific studies. Researchers provide their code and data to Codecheck, who run the code independently to ensure the work can be reproduced.

Last week, Codecheck certified the reproducibility of arguably the most talked-about computational model of the COVID-19 pandemic, that of the Imperial College group led by Professor Neil Ferguson. ̽��ֱ��model suggested that there could be up to half a million deaths in the UK if no measures were taken to slow the spread of the virus, and has been cited as one of the main reasons that lockdown went into effect soon after. However, the Imperial group did not immediately make their code publicly available.

Codecheck.org.uk provided an independent review of the replication of key findings from Report 9 using CovidSim reimplementation. ̽��ֱ��process matches domain expertise and technical skills, taking place as an open peer review. ̽��ֱ��reviewer conducts the codecheck and submits the resulting certificate as part of their review.

̽��ֱ��results confirm that the key finding of Report 9 - on the impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand - are reproducible. Eglen did not review the epidemiology that went into the Imperial model, however.

In his analysis, Dr Eglen said: “Each run generated a tab-delimited file in the output folder. Two R scripts provided by Prof Ferguson were used to summarise these runs into two summary files... These files were compared against the values generated by Prof Ferguson... ̽��ֱ��results were found to be identical. Inserting my results into his Excel spreadsheet generated the same pivot tables.”

̽��ֱ��codecheck found that: “Small variations (mostly under 5%) in the numbers were observed between Report 9 and our runs.” ̽��ֱ��codecheck confirmed the trends and findings of the original report.

Building in part on code originally developed, published and peer-reviewed in 2005 and 2006, the code used for Report 9 continues to be actively developed to allow examination of the wider range of control policies now being deployed as countries relax lockdown. ̽��ֱ��Imperial team is sharing the code to enhance transparency and to allow others to contribute and make use of the simulation.

Refactoring the code has allowed changes to be made more quickly and reliably, including incorporating new data that has become available as the pandemic has progressed.

In addition to the features presented in Imperial Report 9, further strategies can now be examined such as testing and contact tracing, which was not a UK policy option in March.

Users also now have the ability to vary intensity of interventions over time and to calibrate the model to country-specific epidemic data.

Adapted from a piece originally published on the Imperial College London website

How you can support Cambridge's COVID-19 research effort

Donate to support COVID-19 research at Cambridge

Cambridge researcher confirms reproducibility of high-profile Imperial College coronavirus computational model.

Photo by Christian Wiediger on Unsplash

Closeup of computer keyboard

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Location, location, location: researchers develop model to predict retail failure

sc604 — Mon, 08 Oct 2018 23:01:44 +0000

Using information from ten different cities around the world, the researchers, led by the ̽��ֱ�� of Cambridge, have developed a model that can predict with 80% accuracy whether a new business will fail within six months. ̽��ֱ��results will be presented at the ACM Conference on Pervasive and Ubiquitous Computing (Ubicomp), taking place this week in Singapore.

While the retail sector has always been risky, the past several years have seen a transformation of high streets as more and more retailers fail. ̽��ֱ��model built by the researchers could be useful for both entrepreneurs and urban planners when determining where to locate their business or which areas to invest in.

“One of the most important questions for any new business is the amount of demand it will receive. This directly relates to how likely that business is to succeed,” said lead author Krittika D’Silva, a Gates Scholar and PhD student at Cambridge's Department of Computer Science and Technology. “What sort of metrics can we use to make those predictions?”

D’Silva and her colleagues used more than 74 million check-ins from the location technology platform Foursquare from Chicago, Helsinki, Jakarta, London, Los Angeles, New York, Paris, San Francisco, Singapore and Tokyo; and data from 181 million taxi trips from New York and Singapore.

Using this data, the researchers classified venues according to the properties of the neighbourhoods in which they were located, the visit patterns at different times of day, and whether a neighbourhood attracted visitors from other neighbourhoods.

“We wanted to better understand the predictive power that metrics about a place at a certain point in time have,” said D’Silva.

Whether a business succeeds or fails is normally based on a number of controllable and uncontrollable factors. Controllable factors might include the quality or price of the store’s product, its opening hours and its customer satisfaction. Uncontrollable factors might include unemployment rates of a city, overall economic conditions and urban policies.

“We found that even without information about any of these uncontrollable factors, we could still use venue-specific, location-related and mobility-based features in predicting the likely demise of a business,” said D’Silva.

̽��ֱ��data showed that across all ten cities, venues that are popular around the clock, rather than just at certain points of day, are more likely to succeed. Additionally, venues that are in demand outside of the typical popular hours of other venues in the neighbourhood tend to survive longer. ̽��ֱ��data also suggested that venues in diverse neighbourhoods, with multiple types of businesses, tend to survive longer.

While the ten cities had certain similarities, the researchers also had to account for their differences.

“ ̽��ֱ��metrics that were useful predictors vary from city to city, which suggests that factors affect cities in different ways,” said D’Silva. “As one example, that the speed of travel to a venue is a significant metric only in New York and Tokyo. This could relate to the speed of transit in those cities or perhaps to the rates of traffic.”

To test the predictive power of their model, the researchers first had to determine whether a particular venue had closed within the time window of their data set. They then ‘trained’ the model on a subset of venues, telling the model what the features of those venues were in the first time window and whether the venue was open or closed in a second time window. They then tested the trained model on another subset of the data to see how accurate it was.

According to the researchers, their model shows that when deciding when and where to open a business, it is important to look beyond the static features of a given neighbourhood and to consider the ways that people move to and through that neighbourhood at different times of day. They now want to consider how these features vary across different neighbourhoods in order to improve the accuracy of their model.

Reference:
Krittika D’Silva et al. ‘ ̽��ֱ��Role of Urban Mobility in Retail Business Survival.’ Paper presented to the Ubicomp 2018, Singapore, 8-12 October 2018. https://ubicomp.org/ubicomp2018/program/program.html

Researchers have used a combination of location and transport data to predict the likelihood that a given retail business will succeed or fail.

One of the most important questions for any new business is the amount of demand it will receive.

Krittika D’Silva

toastbrot81

Regent Street

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Computer model of blood development could speed up search for new leukaemia drugs

cjb250 — Mon, 09 Feb 2015 16:00:00 +0000

̽��ֱ��human body produces over 2.5 million new blood cells during every second of our adult lives, but how this process is controlled remains poorly understood. Around 30,000 new patients each year are diagnosed with cancers of the blood each year in the UK alone. These cancers, which include leukaemia, lymphoma and myeloma, occur when the production of new blood cells gets out of balance, for example if the body produces an overabundance of white blood cells.

Biomedical scientists from the Wellcome Trust-MRC Cambridge Stem Cell Institute and the Cambridge Institute for Medical Research collaborated for the past 2 years with computational biologists at Microsoft Research and Cambridge ̽��ֱ��’s Department of Biochemistry. This interdisciplinary team of researchers have developed a computer model to help gain a better understanding of the control mechanisms that keep blood production normal. ̽��ֱ��details are published today in the journal Nature Biotechnology.

“With this new computer model, we can carry out simulated experiments in seconds that would take many weeks to perform in the laboratory, dramatically speeding up research into blood development and the genetic mutations that cause leukaemia,” says Professor Bertie Gottgens whose research team is based at the ̽��ֱ��’s Cambridge Institute for Medical Research.

Dr Jasmin Fisher from Microsoft Research and the Department of Biochemistry at the ̽��ֱ�� of Cambridge says: “This is yet another endorsement of how computer programs empower us to gain better understanding of remarkably complicated processes. What is ground-breaking about the current work is that we show how we can automate the process of building such programs based on raw experimental data. It provides us with a blueprint to develop computer models relevant to other human diseases including common cancers such as breast and colon cancer.”

To construct the computer model, PhD student Vicki Moignard from the Stem Cell Institute measured the activity of 48 genes in over 3,900 blood progenitor cells that give rise to all other types of blood cell: red and white blood cells, and platelets. These genes include TAL1 and RUNX1, both of which are essential for the development of blood stem cells, and hence to human life.

Computational biology PhD student Steven Woodhouse then used the resulting dataset to construct the computer model of blood cell development, using computational approaches originally developed at Microsoft Research for synthesis of computer code. Importantly, subsequent laboratory experiments validated the accuracy of this new computer model.

One way the computer model can be used is to simulate the activity of key genes implicated in blood cancers. For example, around one in five of all children who develop leukaemia has a faulty version of the gene RUNX1, as does a similar proportion of adults with acute myeloid leukaemia, one of the most deadly forms of leukaemia in adults. ̽��ֱ��computer model shows how RUNX1 interacts with other genes to control blood cell development: the gene produces a protein also known as Runx1, which in healthy patients activates a particular network of key genes; in patients with leukaemia, an altered form of the protein is thought to suppress this same network. If the researchers change the ‘rules’ in the network model, they can simulate the formation of abnormal leukaemia cells. By tweaking the leukaemia model until the behaviour of the network reverts back to normal, the researchers believe they can identify promising pathways to target with drugs.

Professor Gottgens adds: “Because the computer simulations are very fast, we can quickly screen through lots of possibilities to pick the most promising ones as pathways for drug development. ̽��ֱ��cost of developing a new drug is enormous, and much of this cost comes from new candidate drugs failing late in the drug development process. Our model could significantly reduce the risk of failure, with the potential to make drug discovery faster and cheaper.”

̽��ֱ��research was supported by the Medical Research Council, the Biotechnology and Biological Sciences Research Council, Leukaemia and Lymphoma Research, the Leukemia and Lymphoma Society, Microsoft Research and the Wellcome Trust.

Dr Matt Kaiser, Head of Research at UK blood cancer charity Leukaemia & Lymphoma Research, which has funded Professor Gottgens’ team for over a decade, said: “For some leukaemias, the majority of patients still ultimately die from their disease. Even for blood cancers for which the long-term survival chances are fairly good, such as childhood leukaemia, the treatment can be really gruelling. By harnessing the power of cutting-edge computer technology, this research will dramatically speed up the search for more effective and kinder treatments that target these cancers at their roots.”

Reference
Moignard, V et al. Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nature Biotech; 9 Feb 2015.

̽��ֱ��first comprehensive computer model to simulate the development of blood cells could help in the development of new treatments for leukaemia and lymphoma, say researchers at the ̽��ֱ�� of Cambridge and Microsoft Research.

With this new computer model, we can carry out simulated experiments in seconds that would take many weeks to perform in the laboratory

Bertie Gottgens

E. M. Unit, Royal Free Hospital

SEM image of normal red blood cells, computer-coloured red

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New research highlights the key role of ozone in climate change

sc604 — Mon, 01 Dec 2014 15:02:33 +0000

Many of the complex computer models which are used to predict climate change could be missing an important ozone ‘feedback’ factor in their calculations of future global warming, according to new research led by the ̽��ֱ�� of Cambridge and published today (1 December) in the journal Nature Climate Change.

Computer models play a crucial role in informing climate policy. They are used to assess the effect that carbon emissions have had on the Earth’s climate to date, and to predict possible pathways for the future of our climate.

Increasing computing power combined with increasing scientific knowledge has led to major advances in our understanding of the climate system during the past decades. However, the Earth’s inherent complexity, and the still limited computational power available, means that not every variable can be included in current models. Consequently, scientists have to make informed choices in order to build models which are fit for purpose.

“These models are the only tools we have in terms of predicting the future impacts of climate change, so it’s crucial that they are as accurate and as thorough as we can make them,” said the paper’s lead author Peer Nowack, a PhD student in the Centre for Atmospheric Science, part of Cambridge’s Department of Chemistry.

̽��ֱ��new research has highlighted a key role that ozone, a major component of the stratosphere, plays in how climate change occurs, and the possible implications for predictions of global warming. Changes in ozone are often either not included, or are included a very simplified manner, in current climate models. This is due to the complexity and the sheer computational power it takes to calculate these changes, an important deficiency in some studies.

In addition to its role in protecting the Earth from the Sun’s harmful ultraviolet rays, ozone is also a greenhouse gas. ̽��ֱ��ozone layer is part of a vast chemical network, and changes in environmental conditions, such as changes in temperature or the atmospheric circulation, result in changes in ozone abundance. This process is known as an atmospheric chemical feedback.

Using a comprehensive atmosphere-ocean chemistry-climate model, the Cambridge team, working with researchers from the ̽��ֱ�� of East Anglia, the National Centre for Atmospheric Science, the Met Office and the ̽��ֱ�� of Reading, compared ozone at pre-industrial levels with how it evolves in response to a quadrupling of CO2 in the atmosphere, which is a standard climate change experiment.

What they discovered is a reduction in global surface warming of approximately 20% – equating to 1° Celsius – when compared with most models after 75 years. This difference is due to ozone changes in the lower stratosphere in the tropics, which are mainly caused by changes in the atmospheric circulation under climate change.

“This research has shown that ozone feedback can play a major role in global warming and that it should be included consistently in climate models,” said Nowack. “These models are incredibly complex, just as the Earth is, and there are an almost infinite number of different processes which we could include. Many different processes have to be simplified in order to make them run effectively within the model, but what this research shows is that ozone feedback plays a major role in climate change, and therefore should be included in models in order to make them as accurate as we can make them. However, this particular feedback is especially complex since it depends on many other climate processes that models still simulate differently. Therefore, the best option to represent this feedback consistently might be to calculate ozone changes in every model, in spite of the high computational costs of such a procedure.”

“ ̽��ֱ��results reported here do not imply that climate change ceases to be an issue: rather that the sorts of impacts predicted by recent UN IPCC reports for later this century may be delayed - and even then by only by a few years,” said Dr Manoj Joshi of the ̽��ֱ�� of East Anglia, one of the paper's co-authors.

“Climate change research is all about having the best data possible,” said Nowack. “Every climate model currently in use shows that warming is occurring and will continue to occur, but the difference is in how and when they predict warming will happen. Having the best models possible will help make the best climate policy.”

̽��ֱ��models which are used to predict how climate change will occur could be much improved by including the key role of ozone, which is often overlooked in current models.

These models are the only tools we have in terms of predicting the future impacts of climate change

Peer Nowack

Wisconsin Department of Natural Resources via flickr

Milkweed with Ozone Damage

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How some of the first animals lived - and died

sc604 — Mon, 11 Aug 2014 19:00:00 +0000

A bizarre group of uniquely-shaped organisms known as rangeomorphs may have been some of the earliest animals to appear on Earth, uniquely suited to ocean conditions 575 million years ago.

A new model devised by researchers at the ̽��ֱ�� of Cambridge has resolved many of the mysteries around the structure, evolution and extinction of these ‘proto animals’. ̽��ֱ��findings are reported today (11 August) in the journal Proceedings of the National Academy of Sciences of the United States of America.

Rangeomorphs were some of the earliest large organisms on Earth, existing during a time when most other forms of life were microscopic in size. Most rangeomorphs were about 10 centimetres high, although some were up to two metres in height.

These creatures were ocean dwellers which lived during the Ediacaran period, between 635 and 541 million years ago. Their bodies were made up of soft branches, each with many smaller side branches, forming a geometric shape known as a fractal, which can be seen in many familiar branching shapes such as fern leaves and even river networks.

Rangeomorphs were unlike any modern organism, which has made it difficult to determine how they fed, grew or reproduced, and therefore difficult to link them to any particular modern group. However, despite the fact that they looked like plants, evidence points to the fact that rangeomorphs were actually some of the earliest animals.

“We know that rangeomorphs lived too deep in the ocean for them to get their energy through photosynthesis as plants do,” said Dr Jennifer Hoyal Cuthill of Cambridge’s Department of Earth Sciences, who led the research. “It’s more likely that they absorbed nutrients directly from the sea water through the surface of their body. It would be difficult in the modern world for such large animals to survive only on dissolved nutrients.”

“ ̽��ֱ��oceans during the Ediacaran period were more like a weak soup – full of nutrients such as organic carbon, whereas today suspended food particles are swiftly harvested by a myriad of animals,” said co-author Professor Simon Conway Morris.

Starting 541 million years ago, the conditions in the oceans changed quickly with the start of the Cambrian Explosion – a period of rapid evolution when most major animal groups first emerge in the fossil record and competition for nutrients increased dramatically.

Rangeomorphs have often been considered a ‘failed experiment’ of evolution as they died out so quickly once the Cambrian Explosion began in earnest, but this new analysis shows just how successful they once were.

Rangeomorphs almost completely filled the space surrounding them, with a massive total surface area. This made them very efficient feeders that were able to extract the maximum amount of nutrients from the ocean water.

“These creatures were remarkably well-adapted to their environment, as the oceans at the time were high in nutrients and low in competition,” said Dr Hoyal Cuthill. “Mathematically speaking, they filled their space in a nearly perfect way.”

Dr Hoyal Cuthill examined rangeomorph fossils from a number of locations worldwide, and used them to make the first computer reconstructions of the development and three-dimensional structure of these organisms, showing just how well-suited they were to their Ediacaran environment.

As the Cambrian Explosion began however, the rangeomorphs became ‘sitting ducks’, as they had no known means of defence from predators which were starting to evolve, and the changing chemical composition of the ocean meant that they could no longer get the nutrients they required to feed.

“As the Cambrian began, these Ediacaran specialists could no longer survive, and nothing quite like them has been seen again,” said Dr Hoyal Cuthill.

New three-dimensional reconstructions show how some of the earliest animals on Earth developed, and provide some answers as to why they went extinct.

As the Cambrian began, these specialists could no longer survive, and nothing quite like them has been seen again

Jennifer Hoyal Cuthill

Palaeontological reconstruction of rangeomorph fronds from the Ediacaran Period (635-541 million years ago) built using computer models of rangeomorph growth and development.

Yes

Can your phone double up as your life-coach?

fpjl2 — Sat, 29 Dec 2012 08:00:01 +0000

On January 1^st, millions of people will wake up with their sore heads full of New Year resolutions to achieve more fulfilling, less stressful lives. Now, researchers are developing a data-gathering mobile platform to help identify the causes of stress for individuals and encourage people to build healthier, happier lifestyles - something that could become a preventative measure for a huge number of medical conditions.

Between use of a phone’s inbuilt sensors and monitoring from local sources, the Android Remote Sensing app, or AIRS, can gather a huge amount of data - from environmental aspects such as location, weather, noise levels, even vicinity devices to gauge crowds, to social aspects such as calendar events and communication spikes in email, text and calls - providing a startlingly informed account of a person’s day.

This automatic recording is coupled with the ability to add emotional data by updating your mood through a series of emoticons, along with text annotations. ECG or heart rate sensors can also be used to show physiological reactions.

All this feeds into a person’s unique life “narrative” to determine what the researchers describe as “meaningful events” - those combinations which trigger stress and strong emotion.

“By steering people to become self-aware of stress and activity management, systems such as AIRS may be able to help people before they develop health problems in later life, when costly treatments are required with limited success,” said Dr Dirk Trossen, technical manager of the project at Cambridge’s Computer Laboratory.

“ ̽��ֱ��time before prescribed medicine is critical in prevention and cutting costs for health services. This requires close monitoring and awareness of lifestyle on the part of individuals - so if the ubiquitous phone in your pocket can also assist with better living in general it’s a win/win situation.”

AIRS provides essential input for the desktop-based MyRoR platform for lifestyle management, developed by Dana Pavel from the ̽��ֱ�� of Essex’s School of Computer Science, as part of the wider PAL project. ̽��ֱ��project - funded by the Engineering and Physical Sciences Research Council and the Technology Strategy Board - is investigating personal and social communication services for health and lifestyle monitoring.

̽��ֱ��MyRoR platform correlates this information and delivers it as an easy to digest blog-style timeline, allowing the user to detect spikes in various activities and surroundings - and their relation to the diarised emotional values and physiological symptoms of stress.

̽��ֱ��outputs from Pavel’s MyRoR platform are sets of sharable graphics that provide a user-friendly entry into the complex data, offering the “essence” of the individual’s day or week. “ ̽��ֱ��graphics, or media objects, that present the visual story are a more natural way of representing the dense information, bringing it all together in a fun, concise and engaging way,” said Dana Pavel, from Essex’s School of Computer Science. “These stories allow users to hone in on what’s important, the situations with most meaning.”

Users can then employ the AIRS app to craft lifestyle approaches that help flatten stress levels - such as automatic settings that suspend email and calls at key points to create pockets of calm in the day - which can continue beyond initial physical monitoring to support a more balanced life.

There have been a number of user tests - with both ECG monitoring and just the smartphone app - and feedback from users has been positive. “ ̽��ֱ��platform gives people the opportunity to step outside their lives and analyse in-depth contextual data from their day to day existence - an important chance for serious reflection on aspects of daily life that are impacting perhaps without even realising,” said Trossen.

Importantly for the researchers, given the personal nature of the data, information security and software transparency have been paramount. All personal data is stored locally, and is wiped if a phone is stolen and unlocked, and the app has been made ‘open source’ - with all hard coding accessible - and freely available through Google Play.

“This kind of assisted living though mobile technologies is in its infancy, but it is essential that solutions adapt to people, not the other way around, said Trossen.

“Systems should enhance lives and help involve individuals in the information that is having an impact on them every minute.”

For more information, please contact Dirk Trossen on dt355@cam.ac.uk

Researchers are developing a smartphone platform that enables careful monitoring of lifestyle to pinpoint and help avert triggers for stress and negative emotion.

If the ubiquitous phone in your pocket can also assist with better living in general it’s a win/win situation.

Dirk Trossen

AIRS widgets on the Android home screen

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