Key scientific and technological advances are transforming healthcare through sensors, data, and machine learning. These include collecting health data through lifelogging and wearables; learning data-driven models of health and disease; and using real-time decision support augmented with intelligence. However, for these technologies to benefit all, policies must ensure affordable access to data collection, informed consent, representative data collection, and trustworthy models that individuals and healthcare professionals can use. The goal is to thoughtfully leverage these opportunities to improve health and longevity for all in society.
Please cite as: Kamel Boulos MN. Creating self-aware and smart healthy cities. Invited plenary keynote address followed by sub-plenary round table at WHO 2014 International Healthy Cities Conference, Athens, Greece, 25 October 2014. http://www.healthycities2014.org/ehome/89657/192014/?&
PPT updated in May 2015.
Oct 2017: See also https://www.slideshare.net/sl.medic/how-the-internet-of-things-and-people-can-help-improve-our-health-wellbeing-and-quality-of-life
Towards a successful implementation of game mechanics (gamification) in e-hea...Maged N. Kamel Boulos
Cite as: Kamel Boulos MN. Towards a successful implementation of game mechanics (gamification) in e-health interventions (updated: 09//2015). In: Baptista TM, Kamel Boulos MN, Rodrigues FM, Rocha A. E-Health, psychology and medicine: the future of a close cooperation (invited symposium). In: Proceedings of the 14th European Congress of Psychology, Milan, Italy, 7-10 July 2015. URL: http://www.ecp2015.it/scientific-program/invited-symposia/ - WebCite cache: http://www.webcitation.org/6YIHINbi0
From The Guardian to Cisco, big business to small, it seems that everybody is talking about the Internet of Things — but what exactly is IoT and why does it matter?
Taking a deep dive, we explore the many faces of IoT in Healthcare. Technology research and advisory company, Gartner, currently place the Internet of Things at the peak of inflated expectations and there are certainly challenges. But IoT also holds real promise for healthcare and it is already making an impact today.
We demonstrate why the Internet of Things has a far reaching impact across all determinants of health and how it could lead to a broader model of healthcare. We look at some of the technologies that are available to buy or that are already in development today, whilst also exploring some of the very real challenges that integrating such technologies into healthcare presents. Finally, we offer some ideas about how you can get involved, whether you are a healthcare professional or not.
Presented at SW2012 @ ISWC2012.
http://amitsheth.blogspot.com/2012/08/semantics-empowered-physical-cyber.html
This is an old version of this talk, for more recent information on this topic (eg talks, papers, events), see: http://wiki.knoesis.org/index.php/PCS
Please cite as: Kamel Boulos MN. Creating self-aware and smart healthy cities. Invited plenary keynote address followed by sub-plenary round table at WHO 2014 International Healthy Cities Conference, Athens, Greece, 25 October 2014. http://www.healthycities2014.org/ehome/89657/192014/?&
PPT updated in May 2015.
Oct 2017: See also https://www.slideshare.net/sl.medic/how-the-internet-of-things-and-people-can-help-improve-our-health-wellbeing-and-quality-of-life
Towards a successful implementation of game mechanics (gamification) in e-hea...Maged N. Kamel Boulos
Cite as: Kamel Boulos MN. Towards a successful implementation of game mechanics (gamification) in e-health interventions (updated: 09//2015). In: Baptista TM, Kamel Boulos MN, Rodrigues FM, Rocha A. E-Health, psychology and medicine: the future of a close cooperation (invited symposium). In: Proceedings of the 14th European Congress of Psychology, Milan, Italy, 7-10 July 2015. URL: http://www.ecp2015.it/scientific-program/invited-symposia/ - WebCite cache: http://www.webcitation.org/6YIHINbi0
From The Guardian to Cisco, big business to small, it seems that everybody is talking about the Internet of Things — but what exactly is IoT and why does it matter?
Taking a deep dive, we explore the many faces of IoT in Healthcare. Technology research and advisory company, Gartner, currently place the Internet of Things at the peak of inflated expectations and there are certainly challenges. But IoT also holds real promise for healthcare and it is already making an impact today.
We demonstrate why the Internet of Things has a far reaching impact across all determinants of health and how it could lead to a broader model of healthcare. We look at some of the technologies that are available to buy or that are already in development today, whilst also exploring some of the very real challenges that integrating such technologies into healthcare presents. Finally, we offer some ideas about how you can get involved, whether you are a healthcare professional or not.
Presented at SW2012 @ ISWC2012.
http://amitsheth.blogspot.com/2012/08/semantics-empowered-physical-cyber.html
This is an old version of this talk, for more recent information on this topic (eg talks, papers, events), see: http://wiki.knoesis.org/index.php/PCS
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Lifelogging - A long term data analytics challengeCathal Gurrin
A talk delivered at the DBTA workshop on Lifelogging and Long-term Digital Preservation in Lugano, November 2015. The talk introduces lifelogging and the concept of the digital self. It highlights some potential advantages of lifelogging and suggests the technologies that we need to develop (or have developed) to realise these advantages. Finally it concludes with some insights based on my nine years of practitioner experience.
Standout Studies of Health Games, presentation at Games for Health Conference...Debra Lieberman
Here are some recent noteworthy studies of health games. They are grouped by topic area and included are many of my tweets about research on health games.
For many doctors, the idea of a light, portable, powerful device that they could integrate with their daily professional lives was the stuff of fairy tales… until the iPad. Come and learn more about how doctors are using this device to improve point-of-care service, make rounding more efficient, etc. iPads will be available for hands-on study, and Kimberley (your technology fairy godmother) will explain how you can check one out!
Ehealth: enabling self-management, public health 2.0 and citizen scienceKathleen Gray
Invited presentation, Technology in Diabetes Joint Symposium, Australian Diabetes Society & Australian Diabetes Educators Association Annual Scientific Meeting, August 2014.
Quantified Self Ideology: Personal Data becomes Big DataMelanie Swan
A key contemporary trend emerging in big data science is the quantified self: individuals engaged in the deliberate self-tracking of any kind of biological, physical, behavioral, or transactional information, as n=1 individuals or in groups. The quantified self is one dimension of the bigger trend to integrate and apply a variety of personal information streams including big health data (genome, transcriptome, environmentome, diseasome), quantified self data streams (biosensor, fitness, sleep, food, mood, heart rate, glucose tracking, etc.), traditional data streams (personal and family health history, prescription history) and IOT (Internet of things) activity data streams (smart home, smart car, environmental sensors, community data). This talk looks at how personal data and group data are becoming big data as individuals and communities share, collaborate, and work with large personalized data sets using novel discovery methods such as anomaly detection and exception reporting, longitudinal baseline analysis, episodic triggers, and hierarchical machine learning.
Best practices to assess and enhance brain function via mobile devices and ...SharpBrains
(Session held at the 2014 SharpBrains Virtual Summit; October 28-30th, 2014)
8:15–9:45am. Best practices to assess and enhance brain function via mobile devices and wearables
- Corinna E. Lathan, Founder and CEO of AnthroTronix
- Eddie Martucci, VP Research & Development at Akili Interactive Labs
- Alex Doman, Co-Founder of Sleep Genius
- Joan Severson, President of Digital Artefacts
- Chair: Keith Epstein, Senior Strategic Advisor at AARP
Learn more here:
http://sharpbrains.com/summit-2014/agenda/
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
Selected Summit Sponsors and Partners showcase their most promising brain health & enhancement initiatives and solutions.
8.30-10am. At the frontier with Neuroscape, VR/ AR and Photobiomodulation
*Adam Gazzaley, UCSF Professor of Neurology, presents Neuroscape
*Dr. Walter Greenleaf, Medical VR/ AR Expert at Stanford Virtual Human Interaction Lab, provides an overview of health applications of virtual & augmented reality (VR/AR)
*Dr. Lew Lim, Founder & CEO of Vielight, discusses photobiomodulation as a new way to enhance brain function
contact information.
10.30-11am. Dr. Bob Schafer, Director of Research at Lumos Labs, presents their expanding vision for brain training, including mindfulness.
*Álvaro Fernández, CEO and Editor-in-Chief of SharpBrains
*Sarah Lenz Lock, Senior Vice President for Policy at AARP and Executive Director of the Global Council on Brain Health (GCBH)
*Dr. April Benasich, Director of the Baby Lab at the Rutgers Center for Molecular and Behavioral Neuroscience
*Chaired by: Dr. Cori Lathan, Co-Chair of the World Economic Forum’s Council on the Future of Human Enhancement
Slidedeck supporting session held during the 2017 SharpBrains Virtual Summit: Brain Health & Enhancement in the Digital Age (December 5-7th). Learn more at: https://sharpbrains.com/summit-2017/
What are scalable best practices to spread smart health? SharpBrains
Maximizing health and well-being requires quality decision-making and positive lifestyles across millions, if not billions, of individual decision-makers. How can we accelerate the adoption of smart health behaviors in scalable and systematic ways, ensuring benefits at both the individual and population levels, and empowering consumers, patients and professionals?
- Chair: Jayne Plunkett, Head of Casualty Reinsurance at Swiss Re, YGL Class of 2010
- Misha Pavel, Program Director of Smart and Connected Health at the National Science Foundation
- Dharma Singh Khalsa, President of the Alzheimer’s Research and Prevention Foundation
- Josh Wright, Managing Director of ideas42
This session took place at the 2013 SharpBrains Virtual Summit: http://sharpbrains.com/summit-2013/agenda/
Smart Data - How you and I will exploit Big Data for personalized digital hea...Amit Sheth
Amit Sheth's keynote at IEEE BigData 2014, Oct 29, 2014.
Abstract from:
http://cci.drexel.edu/bigdata/bigdata2014/keynotespeech.htm
Big Data has captured a lot of interest in industry, with the emphasis on the challenges of the four Vs of Big Data: Volume, Variety, Velocity, and Veracity, and their applications to drive value for businesses. Recently, there is rapid growth in situations where a big data challenge relates to making individually relevant decisions. A key example is personalized digital health that related to taking better decisions about our health, fitness, and well-being. Consider for instance, understanding the reasons for and avoiding an asthma attack based on Big Data in the form of personal health signals (e.g., physiological data measured by devices/sensors or Internet of Things around humans, on the humans, and inside/within the humans), public health signals (e.g., information coming from the healthcare system such as hospital admissions), and population health signals (such as Tweets by people related to asthma occurrences and allergens, Web services providing pollen and smog information). However, no individual has the ability to process all these data without the help of appropriate technology, and each human has different set of relevant data!
In this talk, I will describe Smart Data that is realized by extracting value from Big Data, to benefit not just large companies but each individual. If my child is an asthma patient, for all the data relevant to my child with the four V-challenges, what I care about is simply, “How is her current health, and what are the risk of having an asthma attack in her current situation (now and today), especially if that risk has changed?” As I will show, Smart Data that gives such personalized and actionable information will need to utilize metadata, use domain specific knowledge, employ semantics and intelligent processing, and go beyond traditional reliance on ML and NLP. I will motivate the need for a synergistic combination of techniques similar to the close interworking of the top brain and the bottom brain in the cognitive models.
For harnessing volume, I will discuss the concept of Semantic Perception, that is, how to convert massive amounts of data into information, meaning, and insight useful for human decision-making. For dealing with Variety, I will discuss experience in using agreement represented in the form of ontologies, domain models, or vocabularies, to support semantic interoperability and integration. For Velocity, I will discuss somewhat more recent work on Continuous Semantics, which seeks to use dynamically created models of new objects, concepts, and relationships, using them to better understand new cues in the data that capture rapidly evolving events and situations.
Smart Data applications in development at Kno.e.sis come from the domains of personalized health, energy, disaster response, and smart city.
WHITE PAPER: How safe is your quantified self? from the Symantec Security Res...Symantec
Fueled by technological advances and social factors, the quantified self movement has experienced rapid growth. Quantified self, also known as self-tracking, aims to improve lifestyle and achievements by measuring and analyzing key performance data across a range of activities.
Symantec has found security risks in a large number of self tracking devices and applications. One of the most significant findings was that all of the wearable activity-tracking devices examined, including those from leading brands, are vulnerable to location tracking.
Our researchers built a number of scanning devices using Raspberry Pi mini computers and, by taking them out to athletic events and busy public spaces, found that it was possible to track individuals.
Symantec also found vulnerabilities in how personal data is stored and managed, such as passwords being transmitted in clear text and poor session management. As we collect, store, and share more data about ourselves, do we ever pause to consider the risks and implications of sharing this additional data?
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Lifelogging - A long term data analytics challengeCathal Gurrin
A talk delivered at the DBTA workshop on Lifelogging and Long-term Digital Preservation in Lugano, November 2015. The talk introduces lifelogging and the concept of the digital self. It highlights some potential advantages of lifelogging and suggests the technologies that we need to develop (or have developed) to realise these advantages. Finally it concludes with some insights based on my nine years of practitioner experience.
Standout Studies of Health Games, presentation at Games for Health Conference...Debra Lieberman
Here are some recent noteworthy studies of health games. They are grouped by topic area and included are many of my tweets about research on health games.
For many doctors, the idea of a light, portable, powerful device that they could integrate with their daily professional lives was the stuff of fairy tales… until the iPad. Come and learn more about how doctors are using this device to improve point-of-care service, make rounding more efficient, etc. iPads will be available for hands-on study, and Kimberley (your technology fairy godmother) will explain how you can check one out!
Ehealth: enabling self-management, public health 2.0 and citizen scienceKathleen Gray
Invited presentation, Technology in Diabetes Joint Symposium, Australian Diabetes Society & Australian Diabetes Educators Association Annual Scientific Meeting, August 2014.
Quantified Self Ideology: Personal Data becomes Big DataMelanie Swan
A key contemporary trend emerging in big data science is the quantified self: individuals engaged in the deliberate self-tracking of any kind of biological, physical, behavioral, or transactional information, as n=1 individuals or in groups. The quantified self is one dimension of the bigger trend to integrate and apply a variety of personal information streams including big health data (genome, transcriptome, environmentome, diseasome), quantified self data streams (biosensor, fitness, sleep, food, mood, heart rate, glucose tracking, etc.), traditional data streams (personal and family health history, prescription history) and IOT (Internet of things) activity data streams (smart home, smart car, environmental sensors, community data). This talk looks at how personal data and group data are becoming big data as individuals and communities share, collaborate, and work with large personalized data sets using novel discovery methods such as anomaly detection and exception reporting, longitudinal baseline analysis, episodic triggers, and hierarchical machine learning.
Best practices to assess and enhance brain function via mobile devices and ...SharpBrains
(Session held at the 2014 SharpBrains Virtual Summit; October 28-30th, 2014)
8:15–9:45am. Best practices to assess and enhance brain function via mobile devices and wearables
- Corinna E. Lathan, Founder and CEO of AnthroTronix
- Eddie Martucci, VP Research & Development at Akili Interactive Labs
- Alex Doman, Co-Founder of Sleep Genius
- Joan Severson, President of Digital Artefacts
- Chair: Keith Epstein, Senior Strategic Advisor at AARP
Learn more here:
http://sharpbrains.com/summit-2014/agenda/
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
Selected Summit Sponsors and Partners showcase their most promising brain health & enhancement initiatives and solutions.
8.30-10am. At the frontier with Neuroscape, VR/ AR and Photobiomodulation
*Adam Gazzaley, UCSF Professor of Neurology, presents Neuroscape
*Dr. Walter Greenleaf, Medical VR/ AR Expert at Stanford Virtual Human Interaction Lab, provides an overview of health applications of virtual & augmented reality (VR/AR)
*Dr. Lew Lim, Founder & CEO of Vielight, discusses photobiomodulation as a new way to enhance brain function
contact information.
10.30-11am. Dr. Bob Schafer, Director of Research at Lumos Labs, presents their expanding vision for brain training, including mindfulness.
*Álvaro Fernández, CEO and Editor-in-Chief of SharpBrains
*Sarah Lenz Lock, Senior Vice President for Policy at AARP and Executive Director of the Global Council on Brain Health (GCBH)
*Dr. April Benasich, Director of the Baby Lab at the Rutgers Center for Molecular and Behavioral Neuroscience
*Chaired by: Dr. Cori Lathan, Co-Chair of the World Economic Forum’s Council on the Future of Human Enhancement
Slidedeck supporting session held during the 2017 SharpBrains Virtual Summit: Brain Health & Enhancement in the Digital Age (December 5-7th). Learn more at: https://sharpbrains.com/summit-2017/
What are scalable best practices to spread smart health? SharpBrains
Maximizing health and well-being requires quality decision-making and positive lifestyles across millions, if not billions, of individual decision-makers. How can we accelerate the adoption of smart health behaviors in scalable and systematic ways, ensuring benefits at both the individual and population levels, and empowering consumers, patients and professionals?
- Chair: Jayne Plunkett, Head of Casualty Reinsurance at Swiss Re, YGL Class of 2010
- Misha Pavel, Program Director of Smart and Connected Health at the National Science Foundation
- Dharma Singh Khalsa, President of the Alzheimer’s Research and Prevention Foundation
- Josh Wright, Managing Director of ideas42
This session took place at the 2013 SharpBrains Virtual Summit: http://sharpbrains.com/summit-2013/agenda/
Smart Data - How you and I will exploit Big Data for personalized digital hea...Amit Sheth
Amit Sheth's keynote at IEEE BigData 2014, Oct 29, 2014.
Abstract from:
http://cci.drexel.edu/bigdata/bigdata2014/keynotespeech.htm
Big Data has captured a lot of interest in industry, with the emphasis on the challenges of the four Vs of Big Data: Volume, Variety, Velocity, and Veracity, and their applications to drive value for businesses. Recently, there is rapid growth in situations where a big data challenge relates to making individually relevant decisions. A key example is personalized digital health that related to taking better decisions about our health, fitness, and well-being. Consider for instance, understanding the reasons for and avoiding an asthma attack based on Big Data in the form of personal health signals (e.g., physiological data measured by devices/sensors or Internet of Things around humans, on the humans, and inside/within the humans), public health signals (e.g., information coming from the healthcare system such as hospital admissions), and population health signals (such as Tweets by people related to asthma occurrences and allergens, Web services providing pollen and smog information). However, no individual has the ability to process all these data without the help of appropriate technology, and each human has different set of relevant data!
In this talk, I will describe Smart Data that is realized by extracting value from Big Data, to benefit not just large companies but each individual. If my child is an asthma patient, for all the data relevant to my child with the four V-challenges, what I care about is simply, “How is her current health, and what are the risk of having an asthma attack in her current situation (now and today), especially if that risk has changed?” As I will show, Smart Data that gives such personalized and actionable information will need to utilize metadata, use domain specific knowledge, employ semantics and intelligent processing, and go beyond traditional reliance on ML and NLP. I will motivate the need for a synergistic combination of techniques similar to the close interworking of the top brain and the bottom brain in the cognitive models.
For harnessing volume, I will discuss the concept of Semantic Perception, that is, how to convert massive amounts of data into information, meaning, and insight useful for human decision-making. For dealing with Variety, I will discuss experience in using agreement represented in the form of ontologies, domain models, or vocabularies, to support semantic interoperability and integration. For Velocity, I will discuss somewhat more recent work on Continuous Semantics, which seeks to use dynamically created models of new objects, concepts, and relationships, using them to better understand new cues in the data that capture rapidly evolving events and situations.
Smart Data applications in development at Kno.e.sis come from the domains of personalized health, energy, disaster response, and smart city.
WHITE PAPER: How safe is your quantified self? from the Symantec Security Res...Symantec
Fueled by technological advances and social factors, the quantified self movement has experienced rapid growth. Quantified self, also known as self-tracking, aims to improve lifestyle and achievements by measuring and analyzing key performance data across a range of activities.
Symantec has found security risks in a large number of self tracking devices and applications. One of the most significant findings was that all of the wearable activity-tracking devices examined, including those from leading brands, are vulnerable to location tracking.
Our researchers built a number of scanning devices using Raspberry Pi mini computers and, by taking them out to athletic events and busy public spaces, found that it was possible to track individuals.
Symantec also found vulnerabilities in how personal data is stored and managed, such as passwords being transmitted in clear text and poor session management. As we collect, store, and share more data about ourselves, do we ever pause to consider the risks and implications of sharing this additional data?
Physical Cyber Social Computing: An early 21st century approach to Computing ...Amit Sheth
Keynote given at WiMS 2013 Conference, June 12-14 2013, Madrid, Spain. http://aida.ii.uam.es/wims13/keynotes.php
Video of this talk at: http://videolectures.net/wims2013_sheth_physical_cyber_social_computing/
More information at: More at: http://wiki.knoesis.org/index.php/PCS
and http://knoesis.org/projects/ssw/
Replacing earlier versions: http://www.slideshare.net/apsheth/physical-cyber-social-computing & http://www.slideshare.net/apsheth/semantics-empowered-physicalcybersocial-systems-for-earthcube
Abstract: The proper role of technology to improve human experience has been discussed by visionaries and scientists from the early days of computing and electronic communication. Technology now plays an increasingly important role in facilitating and improving personal and social activities and engagements, decision making, interaction with physical and social worlds, generating insights, and just about anything that an intelligent human seeks to do. I have used the term Computing for Human Experience (CHE) [1] to capture this essential role of technology in a human centric vision. CHE emphasizes the unobtrusive, supportive and assistive role of technology in improving human experience, so that technology “takes into account the human world and allows computers themselves to disappear in the background” (Mark Weiser [2]).
In this talk, I will portray physical-cyber-social (PCS) computing that takes ideas from, and goes significantly beyond, the current progress in cyber-physical systems, socio-technical systems and cyber-social systems to support CHE [3]. I will exemplify future PCS application scenarios in healthcare and traffic management that are supported by (a) a deeper and richer semantic interdependence and interplay between sensors and devices at physical layers, (b) rich technology mediated social interactions, and (c) the gathering and application of collective intelligence characterized by massive and contextually relevant background knowledge and advanced reasoning in order to bridge machine and human perceptions. I will share an example of PCS computing using semantic perception [4], which converts low-level, heterogeneous, multimodal and contextually relevant data into high-level abstractions that can provide insights and assist humans in making complex decisions. The key proposition is to explain that PCS computing will need to move away from traditional data processing to multi-tier computation along data-information-knowledge-wisdom dimension that supports reasoning to convert data into abstractions that humans are adept at using.
[1] A. Sheth, Computing for Human Experience
[2] M. Weiser, The Computer for 21st Century
[3] A. Sheth, Semantics empowered Cyber-Physical-Social Systems
[4] C. Henson, A. Sheth, K. Thirunarayan, Semantic Perception: Converting Sensory Observations to Abstractions
TRANSFORMING BIG DATA INTO SMART DATA: Deriving Value via Harnessing Volume, ...Amit Sheth
Keynote given at ICDE2014, April 2014. Details at: http://ieee-icde2014.eecs.northwestern.edu/keynotes.html
A video of a version of this talk is available here: http://youtu.be/8RhpFlfpJ-A
(download to see many hidden slides).
Two versions of this talk, targeted at Smart Energy and Personalized Digital Health domains/apps at: http://wiki.knoesis.org/index.php/Smart_Data
Previous (older) version replaced by this version: http://www.slideshare.net/apsheth/big-data-to-smart-data-keynote
Expo day: Digital Artefacts (BrainBaseline), HeartMath, Sleep Genius, The Al...SharpBrains
Expo Day (continued) @ 2014 SharpBrains Virtual Summit. Summit Sponsors announce and showcase their latest initiatives and solutions:
1–1.30pm. Digital Artefacts: Joan Severson, President
1.45–2.15pm. HeartMath: Catherine Calarco, Chief Marketing Officer
2.30-3pm. Sleep Genius: Colin House, CEO
3.15–3.45pm. The Alzheimer’s Research and Prevention Foundation: Dr. Dharma Singh Khalsa, President
Learn more here:
http://sharpbrains.com/summit-2014/agenda/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Stroulia Nov27.2019
1. Sensors, Data, and Health
Eleni Stroulia
stroulia@ualberta.ca
https://hypatia.cs.ualberta.ca/wp6
Professor, Computing Science
University of Alberta
NSERC, AI, IBM, AGE-WELL, DITA
2. key scientific and technological
advances are transforming our
understanding of health and
healthcare
4
6. Gamification
https://www.behaviormodel.org/
4
• Collecting Data - Lifelogging the Quantified Self
• Learning Data-driven Models of Health and Disease
• Real-time Decision-Making Support Augmented with
Intelligence
• Employing Game Elements to Incentivize Healthy Behaviors
9. Recognizing
Depression
From Voice
Deep Neural Networks can be
configured to accurately detect
(the level of) depression in
one’s voice.
The method is language
independent. Detecting Depression from Voice
M Tasnim, E Stroulia; Canadian Conference on Artificial Intelligence, 2019
10. Serious Games
for Cognitive
Training
Effective cognitive assessment
and training can be
implemented in fun tablet-
based games, such as
whack-a-mole,
word-search,
bejewelled, and
mahjong. Detecting Depression from Voice
M Tasnim, E Stroulia; Canadian Conference on Artificial Intelligence, 2019
http://vibrant-minds.org
12. Ambient Sensors
In the Smart Condo, sensors
unobtrusively observe the
occupants’ activities.
Subsequent analysis
recognizes Activities of
Daily Living, a key
indicator of functional
independence.
https://www.youtube.com/watch?v=MWWDAZmO6Hg
The smart condo project: services for independent living NM Boers, D
Chodos, P Gburzynski, L Guirguis, J Huang, R Lederer, L Liu, I Nikolaidis, C
Sadowski, E Stroulia; E-Health, assistive technologies and applications, 2011
Sensor-data fusion for multi-person indoor location estimation
13. Cameras for
Functional
Mobility
Analysis
The Virtual Gym guides older
adults through personalized
exercise postures, specified by
their therapists.
It can be deployed on an
external display or through a
Virtual Reality mode.
VirtualGym: A kinect-based system for seniors exercising at home
V Fernandez-Cervantes, N Neubauer, B Hunter, E Stroulia, L Liu; Entertainment Computing, 2018
Sensor-enabled Functional-Mobility Assessment: An Exploratory Investigation
S Golestan, DJD Romero, E Stroulia, A Miguel-Cruz, L Liu;
2019 IEEE 5th World Forum on Internet of Things
14. This requires that
1. we establish policies to ensure that everyone can afford data-
collection devices, and they consent to the use of their data.
2. so that representative data is collected,
3. and high-quality models are constructed,
4. that individuals and health professionals can trust and use.
Scientific and engineering advances present us today with
many opportunities to lead healthier lives, longer.
Our challenge is to thoughtfully take advantage of these
opportunities to uplift everyone in our society.
Editor's Notes
It is my great pleasure to share with you some thoughts on the transformative role that technology is playing in redefining the way we understand our health, the healthcare system, and our role in managing our own health and that of our loved ones.
I have been working for several years on technologies for supporting seniors to live independently longer, and I am excited to tell you a bit about my projects, the work and results of my team, and the general socio-technical context that has enabled and motivated this research.
I have to start by acknowledging that this work has been a true interdisciplinary collaboration between Computing Science and Occupational Therapy, with substantial contributions from Medicine, Industrial Design and Education.
This work has been supported by many funding organizations, including NSERC, Alberta Innovates, IBM, AGE-WELL and DITA.
Let’s start with an exploration of the key scientific and technological advances that underlie my work and much related work around the world.
In the the next 4 slides, I will briefly review the 4 factors that are revolutionizing the health sector today.
The first key technology is our ability to collect, clean, curate, and store Big Data about ourselves!
The most extreme lifelogger was Robert Shields, who manually recorded 25 years of his life from 1972 to 1997 at 5-minute intervals 37-million word diary is recording his body temperature, blood pressure, medications, urination and bowel movements; he slept for only two hours at a time so he could describe his dreams.[4]
In modern times, likely the first person to capture continuous physiological data together with live first-person video from a wearable camera, was Steve Mann, the father of wearable computing.
25 million are active fitbit users, and fitbit has apparently fallen to third place after Apple and Xiaomi.
And today, this Big Data stream can actually generate insight and knowledge through machine learning, and more generally data science.
My department is renowned for our ML expertise, third/fourth in international rankings in this area, one of the three Pancanadian AI strategy institutes.
The overall workflow of learning from data involves the following steps:
Data capture and cleanupraw data may be captured through devices but data records may be corrupted or lost before being stored due to network congestion or device failures, so cleanup and/or imputation may be needed
Identify distinctive features in the data representationoften the first pass of feature selection is done by domain experts with knowledge that enables them to eliminate data attributes that are not distinctiveother methodologies adopt feature-selection steps, where features that correlate with other features are excluded
Generate various different hypotheses that might “cover” the datait is useful to think of ML algorithms as searches over a space of possible hypotheses, using policies or heuristics to guide the exploration towards stronger hypotheses with more support for them
Verify whether the data support the hypothesis with sufficient confidence
In the end, the discovered hypotheses represent consistent patterns in the data that can be used in different reasoning tasks: prediction, action selection, realistic construction of new data instances, simulation.
All algorithms require configuration of multiple parameters, often through trial-and-test
Different algorithms perform better on different types of data sets and for different data classes, so we often employ ensembles of ML algorithms
Adoption depends on trust, SO
To build fairness (and by implication trust) through
(a) representative data
(b) ethical heuristics and optimization functions
to integrate our knowledge in the process explainability
Having transformed data into knowledge the question becomes “how to use it to improve decision making and action”
This is possible with the variety of (a) specialized computational devices we have at our disposal, and (b) networking protocols that we can deploy in different settings.
Today we are developing software systems that are distributed and heterogeneous, including
sensors on persons, buildings, vehicles,
that establish ad-hoc networks opportunistically when they find themselves in the presence of each other
communicate their data to the cloud, where different types of servers (multicore, GPUs,…) can efficiently analyze the data to extract knowledge, which
can then be exposed end-user applications at the point of care, or study, or work (through mobile devices)
So we can all be data producers and contribute our experiences to the model-learning process, as long as we have access to the sensing devices and to the internetwork; and on the other hand, we can benefit from this knowledge as long we have access to the internetwork, the mobile devices and the applications.
We need to ensure democratic access to this infrastructure!
Finally, I think it is interesting to talk about another means of supporting good decision making: by embedding action into a game and making “good behaviors” necessary to win the game! This is the idea of gamification!
In 2011 Jane McGonigal published her book Reality is Broken and the position of the book was that game play can have positive and in long-lasting affects on our mood and emotional health.
Fogg’s Behavior Model (FBM) explains why and how game mechanics/dynamics are able to drive actions. FBM asserts that human behavior is a result of the precise temporal convergence of three factors:
Motivation: the person wants desperately to perform the behavior (i.e. he is highly motivated)
Ability: the person can easily carry out the behavior (i.e. he considers the behavior very simple)
Trigger: the person is triggered to do the behavior (i.e. he is cued, reminded, asked, called to action, etc.)
So if studies of accelerometer-collected data have led us to learn that sedentary behavior (too much sitting over the day) is bad, then when a wearable sensor observes that I am sitting for a long time the paired application on my smartphone may remind me to stand up and move, and may give me “points” if I actually act on the advice and through these points I may be able to win an award or maybe simply outperform my friends against whom I am competing.
So if Data is the fundamental ground on which whole this edifice relies, the question becomes where is data come from?
And to answer this question I will adopt the theory of proxemics (Edward T. Hall, the cultural anthropologist who coined the term in 1963), which posits that our behaviour, communication, and social interaction can be observed and understood in different scales of space: intimate, personal, social and public.
Based on this theory, I believe it makes sense to consider the data that we are collecting about ourselves as observations of our lives in these different space scales.
At the intimate scale, we consider ingestible sensors; at the publics pace we are considering epidemiological data.
I am working at the other two scales:
Personal where wearables and mobile devices exist
Social where ambient sensors are deployed.
Let’s start with wearables and mobile apps.
I will start with my most recent project!
Key intuition: mood can be detected in one’s voice
Experimental hypothesis: we can learn a model to distinguish between depressed and non-depressed individuals based on a short speech segment
Study:
Benchmark data in English and German; one speech example per person, with labels
Towards Adoption: we envision the architecture depicted here
Key intuitions:
The more time one devotes to a task, the better they become at it
The more engaging a task is, the more time one is likely to spend on it
Gamification of learning/training
Experimental hypothesis:
Individuals with dementia can learn new skills with extensive practice through games embedding these skills
Study:
We built games to embed various skills, with different levels to make them increasingly challenging
whack-a-mole – attention and reaction
Word-search – attention and language
Bejeweled –pattern matching
Model-driven engineering of product lines so that we can generate multiple levels, instrumented to collect performance data; the different levels play two roles:
Assessment of skill
Engagement and flow (too easy is boring and too difficult is demotivating)
Towards Adoption: with LTC organizations
And on to the social space, with ambient sensing
My favorite project - the smart condo
Key intuition:
the degree to which one is able to perform ADLs indicates the degree of their functional independence
The Barthel index is a list of ADLs that OTs use to score a person when they are assessing their ability to live alone
Experimental hypothesis:
We can learn a model to distinguish between independent and non-independent individuals based on the sensor-event trace that is generated by ambient sensors embedded in the person’s home
We can infer a valid representation of a person’s ADLs from the sensor-event trace
Study:
26 individuals (alone or in pairs) executed a daily-activity script in 2 hours in the smart condo, in which we have embedded motion sensor, proximity sensors, switches, pressure sensors, cameras
We developed a variety of algorithms to fuse the sensor data and infer an activity trace
Towards Adoption: difficult
Finally focusing on a very important aspect of functional independence, mobility, we are working on a project to evaluate and strengthen the physical abilities of individuals.
This project is parallel to Vibrant Minds, but instead of training the brain we focus on the body.
So here is the recipe that I put forward for the new model of health!
Ingestible sensors are the most intimate of all – they observe our individual bodies
https://www.wired.com/story/this-digital-pill-prototype-uses-bacteria-to-sense-stomach-bleeding/
Bacteria, you see, are microscopic sensing machines. Take Lactococcus lactis, a friendly little microbe that helps turn milk into cheese. It can do its curdling work even better if there’s some heme floating around. That’s the iron-containing molecule that transports oxygen in your blood (and the Impossible Burger’s secret ingredient). But taking up too much heme can be toxic. So the little buggers have a system to sense how much there is, complete with genetic switches to change up their metabolism.
Stanford’s Lu’s team took L. lactis’s on-switch DNA, coupled it with some code for bacterial bioluminescence, and stuck the whole genetic circuit inside a gut-friendly strain of E. coli commonly sold as a probiotic. Those modified cells went into a body-safe capsule equipped with a semipermeable membrane on one side to let in liquid from the gut. Wireless semiconductors powered by a teeny battery were packed in the capsule too—separated from the cells by a tiny see-through window.
The scientists tested their bacteria-on-a-chip prototype in mice with induced gastrointestinal bleeding and in pigs that had blood piped into their stomachs. When the bacteria hit the heme, they lit up. Not much, but enough for a custom phototransistor to capture it and relay that information to a microprocessor—which sent the signal to an Android app developed by an undergraduate engineering student.
We are all familiar with fitbit and smart watches etc… The wearables observe our person (and the functioning ofour bodies) from the outside
Notice how important it is to consider all users!
But there are far more interesting from a clinical diagnosis perspective wearables.
As the diagram illustrates, according to a review of the wearables market by a Stanford team last year (Sep2018), there are many wearables with FDA approval for clinical purposes, substituting expensive devices typically available in offices and hospitals.
can be mechanical, physiological and biochemical
are targeted to consumers, to clinical practice, or to research
Zio:
STEP 1: WEAR THE MONITOR
Your doctor will apply a water-resistant Zio by iRhythm heart monitor to your chest. There are no wires, and it can be hidden by your clothes.
STEP 2: NOTE ANY HEART SYMPTOMS
If you feel anything that you think might be an unusual heart rhythm, press the top of the Zio patch. Then briefly describe it in the provided symptom-log booklet, on the myZioTM mobile app, or at www.myzio.com.
STEP 3: RETURN THE MONITOR BY MAIL
After your prescribed wear time, simply remove your monitor. Then place in the back of the provided Patient Instructions & Button Press Log and put the booklet into the pre-addressed return box and drop into any United States Postal Service mailbox.
STEP 4: REVIEW THE RESULTS WITH YOUR DOCTOR
Based on the clear and complete report we’ll provide, your doctor will have the information he or she needs to make a diagnosis.
Medtronic
AUTO MODE*
Automatically adjusts your basal (background) insulin every five minutes based on your CGM readings.†‡
Helps keep your sugar levels in your target range for fewer lows and highs — day and night.†‡1
SUSPEND BEFORE LOW§
Stops insulin up to 30 minutes before reaching your preset low limits.
Automatically restarts insulin when your levels recover without bothersome alerts.‡
Helps you avoid lows and rebound highs.1
Owlet
~400 USD
We need policy to support this cost through insurance!
And last but not least we have to remember two other sources from humanity at large:
Genetics
And
Demographics
The physical, social and economic environment in which people live, work and play influences the choices they make and how they live their lives.
And of course we know that some diseases are linked to specific genes.
These two facts seem at odds…
The only possible strategy then is to include in our analyses data on the genetics of individuals or gene frequencies for populations. Adding genetic information to our analyses could reduce the amount of unobserved heterogeneity and produce estimates of the contribution of specific genes to variations among individuals or across populations. This is not yet a real option. As long as most of the genes that have been identified are associated with rare diseases (like Huntington's chorea or sickle cell anemia), the potential impact of genetics on demographic research is very limited. However, genetic epidemiologists are now searching for genes that have large effects on common conditions. During the next ten years this might lead to discoveries that will substantially alter demographic research.