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Health State Estimation

arXiv.org Artificial Intelligence

Life's most valuable asset is health. Continuously understanding the state of our health and modeling how it evolves is essential if we wish to improve it. Given the opportunity that people live with more data about their life today than any other time in history, the challenge rests in interweaving this data with the growing body of knowledge to compute and model the health state of an individual continually. This dissertation presents an approach to build a personal model and dynamically estimate the health state of an individual by fusing multi-modal data and domain knowledge. The system is stitched together from four essential abstraction elements: 1. the events in our life, 2. the layers of our biological systems (from molecular to an organism), 3. the functional utilities that arise from biological underpinnings, and 4. how we interact with these utilities in the reality of daily life. Connecting these four elements via graph network blocks forms the backbone by which we instantiate a digital twin of an individual. Edges and nodes in this graph structure are then regularly updated with learning techniques as data is continuously digested. Experiments demonstrate the use of dense and heterogeneous real-world data from a variety of personal and environmental sensors to monitor individual cardiovascular health state. State estimation and individual modeling is the fundamental basis to depart from disease-oriented approaches to a total health continuum paradigm. Precision in predicting health requires understanding state trajectory. By encasing this estimation within a navigational approach, a systematic guidance framework can plan actions to transition a current state towards a desired one. This work concludes by presenting this framework of combining the health state and personal graph model to perpetually plan and assist us in living life towards our goals.


Towards automated symptoms assessment in mental health

arXiv.org Machine Learning

Activity and motion analysis has the potential to be used as a diagnostic tool for mental disorders. However, to-date, little work has been performed in turning stratification measures of activity into useful symptom markers. The research presented in this thesis has focused on the identification of objective activity and behaviour metrics that could be useful for the analysis of mental health symptoms in the above mentioned dimensions. Particular attention is given to the analysis of objective differences between disorders, as well as identification of clinical episodes of mania and depression in bipolar patients, and deterioration in borderline personality disorder patients. A principled framework is proposed for mHealth monitoring of psychiatric patients, based on measurable changes in behaviour, represented in physical activity time series, collected via mobile and wearable devices. The framework defines methods for direct computational analysis of symptoms in disorganisation and psychomotor dimensions, as well as measures for indirect assessment of mood, using patterns of physical activity, sleep and circadian rhythms. The approach of computational behaviour analysis, proposed in this thesis, has the potential for early identification of clinical deterioration in ambulatory patients, and allows for the specification of distinct and measurable behavioural phenotypes, thus enabling better understanding and treatment of mental disorders.


AI: Smart Clothes as instructors - Innovation Origins

#artificialintelligence

Until a few years ago, clothing served only to protect people and at the same time still had fashionable aspects. But meanwhile, our second skin can do more and more. The measurement of body data such as pulse value or calorie consumption by means of integrated sensors is almost an old hat. Now, however, the clothing will also take on teaching functions through artificial intelligence: On the one hand as a trainer for humans, on the other hand as a programmer for robots. The latest development comes from Turing Sense.



Design in Tech Report 2018

#artificialintelligence

For this year's report, I took a stab at learning all the CSS/JS that I've always wanted to know, and then went after the task of making a fully responsive report. I've succeeded in doing so, and so this PDF version isn't as good as the real thing. In the next few days I will be sharing a link to the real digital experience. But for now -- enjoy this static version of the report which has a few parts that couldn't render to static form. Because ... this year's report is truly computationally designed and therefore needs to be expressed appropriately (smile). Expect a video version on my new YouTube channel "John Maeda is Learning." What can I do about it? As the marginal return on computing power (a la Moore's law) diminishes and technology is less of a differentiating factor, the value of design has entered the foreground. Five (20%) of the top cumulative-funded VC- backed ventures that have raised additional capital since 2013 are noted to have designer co-founders.


Top 7 Technology Trends in 2017 That Are Moving Faster Than Ever

#artificialintelligence

With the progressing year, the technology diversified ways in which we could communicate and retrieve the information from the pocket fitting devices. Technologies such as IoT, automation, and cognitive computing moved beyond the conceptual stages in 2016. As the year takes up, companies throughout the world are developing their business strategies. In order to move forward in the competition, companies are turning towards major investments in technology. The world's biggest consumer technology convention, CES is one of the best places to find a handful of key technologies. CES 2017 finished another spectacular year with pioneering technology trends including smart homes to self-driving cars. This year is assumed to bring transformative technology trends for us to explore and invest in. AI, also known as Artificial Intelligence has been studied for decades and now the vision of transforming insentient objects into intelligence is gradually becoming a reality. AI based Innovations are now pondering into the market and becoming part of our daily lives with quick adaptability. Artificial intelligence assists humans and handles the tasks flawlessly, without interrupting your comfort. Whether to set an alarm, or remind you of something important, or to play your favorite music or to read out general news for you or to find your phone, AI can make the task more convenient and smart. Sit back and relax while you command your device to do things for you.


Cyber criminals could steal people's most personal information and hold them to ransom, warn UK cyber chiefs

The Independent - Tech

The various pieces of technology that are in our lives could hand over our most personal information to hackers, the UK's most elite cyber security chiefs have warned. Smart phones, watches, televisions, and fitness trackers all collect information on their users that could be used to extort money from people or pose as them. An increasing amount of internet-connected deivces around the home allow hackers far more powerto use "aggressive" and "confrontational" tactics, according to a new report from the Cyber Security Centre (NCSC) and the National Crime Agency (NCA). It highlights the huge amount of personal information that those gadgets contain. Each of them has data including people's photos, personal messages and fitness information – which could be turned on their ownersm, according to the experts.


Top 7 Technology Trends in 2017 That Are Moving Faster Than Ever

#artificialintelligence

With the progressing year, the technology diversified ways in which we could communicate and retrieve the information from the pocket fitting devices. Technologies such as IoT, automation, and cognitive computing moved beyond the conceptual stages in 2016. As the year takes up, companies throughout the world are developing their business strategies. In order to move forward in the competition, companies are turning towards major investments in technology. The world's biggest consumer technology convention, CES is one of the best places to find a handful of key technologies. CES 2017 finished another spectacular year with pioneering technology trends including smart homes to self-driving cars. This year is assumed to bring transformative technology trends for us to explore and invest in. AI, also known as Artificial Intelligence has been studied for decades and now the vision of transforming insentient objects into intelligence is gradually becoming a reality. AI based Innovations are now pondering into the market and becoming part of our daily lives with quick adaptability. Artificial intelligence assists humans and handles the tasks flawlessly, without interrupting your comfort. Whether to set an alarm, or remind you of something important, or to play your favorite music or to read out general news for you or to find your phone, AI can make the task more convenient and smart. Sit back and relax while you command your device to do things for you.


Your.MD Launches Doctor Diagnosis on Facebook - eHealth News ZA

#artificialintelligence

Your.MD, a London-based Artificial intelligence (Al)-powered Personal Health Assistant, has launched a new service that enables users to find relevant and trustworthy health services and products called OneStop. Your.MD launched the beta version of its AI Personal Health Assistant in November 2015 on iOS and Android platforms, marking the world's first Personal Health Assistant to offer medical guidance through end-to-end AI, together with Machine Learning and Natural Language Processing (NLP). Your.MD says OneStop is the first one-stop-shop in digital health to allow people to take full control of each stage of their health issues from understanding their symptoms to finding the best treatment via a chatbot on Facebook Messenger or WeChat. The chatbot aims to achieve three things: Finding out what's wrong with you, suggesting the most likely solution and then offering both public and private services which can help. "Your.MD is truly revolutionary and can make a seismic impact on the global healthcare system by providing accessible, trustworthy and instant healthcare to everyone with a mobile phone," said Your.MD's CEO, Matteo Berlucchi, in the announcement.


Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

arXiv.org Machine Learning

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.