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Context Aware Computing for Personalised Healthcare

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This presentation highlights the emergence of context aware computing in the area of personalised healthcare services.

Publié dans : Technologie
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Context Aware Computing for Personalised Healthcare

  1. 1. Saurav Gupta CONTEXT AWARE MOBILE AGENT FOR REDUCING STRESS AND OBESITY BY MOTIVATING PHYSICAL ACTIVITY
  2. 2. Problem March 2016 2 o People, at large, are suffering from stress and obesity. With various studies showing strong correlation between stress and obesity. o After studying the physical activity patterns amongst people in India, it was found that majority of them are inactive. o Also, people, while being mobile, their operating environment/context changes frequently, which limits the duration and degree of physical activity.
  3. 3. Objectives March 2016 3 o To enable adoption of active and healthy lifestyle amongst the people, while being ‘on-the-fly’ o To bring about a behavioral change amongst the people to shift from curative care to preventive care To achieve these objectives, a ‘Context-Aware Mobile Agent’ was seen as the solution
  4. 4. Literature Study March 2016 4 Distributed implicitHCI Context- Aware I Autonomous Intelligent Virtual Environments Physical Environments HCI (Cooperate) HCI (Compete) Human Environments ICT UbiComp System ICT CCI HCICPICPI (Sense, Adapt) The UbiCom System Model (source: Ubiquitous Computing, Wiley) EVOLUTION: Human to Human Human to Computer Computer to Human Computer to Physical Environment
  5. 5. Literature Study March 2016 5 ‘Context is any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.’ ‘A system is context-aware if it uses context to provide relevant in-formation and/or services to the user, where relevancy depends on the user’ s task’ (Source: Dey and Abowd)
  6. 6. Literature Study March 2016 6
  7. 7. Literature Study March 2016 7 Context aware System capabilities: • Contextual Sensing: It is the retrieving the contextual data in a user-friendly format. • Contextual Adaptation: It is the ability of the context aware system to adapt to the changing environment. • Contextual Resource Discovery: The context aware system identifies the additional resources that it would require to present an improved adaptation by the user. • Contextual Augmentation: In this, the context aware system is able to co-relate the contextual information with existing factual digital information.
  8. 8. Abstract Layered Architecture March 2016 8
  9. 9. Abstract Layered Architecture March 2016 9 Challenges in Context Aware Systems: • Data acquired may not provide a holistic view of the operating environment of the user • The quality of data depends on the quality of sensors utilized in acquiring the contextual information. • The data acquired may not provide the actual information desired by the system. Hence, appropriate interpretation mechanisms need to be deployed to understand the data acquired. • The measurement units involved while acquiring the data maybe multiple. For example, the data maybe in centimeters, meters, kilometers or miles.
  10. 10.  Step 1a  Identify the ‘subjects’ who were obese  To quantify obesity, Body Mass Index was used. It is defined as:  Out of the 97 people surveyed, 33 subjects having BMI of 25 and above were identified Methodology March 2016 10
  11. 11. Methodology March 2016 11 2 31 51 13 Obese Overweight Normal Underweight BMI Index Series1
  12. 12.  Step 1b  Identify the ‘subjects’ who were stressed  To identify subjects suffering from Stress, a questionnaire was designed. It comprised of 05 Indicators:  Physical Indicator (comprised of 21 questions)  Sleep Indicator (comprised of 05 questions)  Behavioral Indicators (comprised of 17 questions)  Emotional Indicators (comprised of 21 questions)  Personal Habits (comprised of 09 questions)  Each question was based on a 5-point Likert scale  A tablet-based mobile application was designed to capture the user inputs. Methodology March 2016 12
  13. 13. Methodology March 2016 13  Step 1b (cont’d)
  14. 14. Methodology March 2016 14  Step 1b (cont’d) 0%6% 26% 37% 31% PHYSICAL STRESS Very Low Medium High Very High Danger 8% 38% 20% 14% 20% SLEEP STRESS Very Low Medium High Very High Danger 2% 48% 40% 7% 3% BEHAVIOURAL STRESS Very Low Medium High Very High Danger 5% 13% 15% 67% EMOTIONAL STRESS Very Low Medium High Very High Danger 2%6% 17% 34% 41% PERSONAL STRESS Very Low Medium High Very High Danger
  15. 15. Methodology March 2016 15  Step 1b (cont’d)  97 people were surveyed in random control trial  The people were selected in the age group of 25-35 years of age  All the subjects who were overweight/obese were also stressed  Out of these, 33 (n=33) were identified as subjects who had either form of stress and were either overweight/obese.
  16. 16. Methodology March 2016 16  Step 2  System Design M.Tech Thesis |Saurav Gupta |CDAC
  17. 17. Methodology March 2016 17  Step 2 (Cont’d)  For Location  Google Fused Location API was integrated  Uses data from WiFi, Mobile towers and GPS available on smartphone.  Location determined based on latitude and longitude coordinates. Accuracy up to 50 meters.  Based on user inputs, 03 locations were classified as:  Home Location  Work Location  Other/Outside Location
  18. 18. Methodology March 2016 18 Favorable Range Extreme Range Temperature 18ºC - 35ºC < 17ºC & >35ºC Humidity Level upto 90% >90% Forecast Clear Skies Sunny Cloudy Windy Rain Thunderstorm Hailstorm  Step 2 (Cont’d)  For Temperature/ Weather  Open Weather API was used and integrated  Two divisions were done based on temperature: Favorable Range and Extreme Range. The grouping was done as follows:
  19. 19. Methodology March 2016 19  Step 2 (Cont’d)  Rule Aggregator  Generates a code based on the data received.  For ex: for the code ‘H-I-AT’ generated, it signifies that the subject is at Home, in an ideal environment/ temperature and in an acceptable time zone.
  20. 20. Methodology March 2016 20  Step 2  Application Screenshots
  21. 21. Methodology March 2016 21  Step 3  Message Database  Researchers believe that a ‘positive and a motivating’ set of messages has a long lasting impact  A database was created for sending alerts to the subjects.  The format of the message was defined as:  ‘Positive motivational message + Activity type’  A database of Positive and motivational messages was created  Activity type was determined based on the code generated by the Rule Aggregator.  Broadly, outdoor activities were recommended only when the subject was at home and the weather was ideal. For the remaining, indoor related activities were advised to the subjects
  22. 22. March 2016 22 Results  The mobile application, ‘Let’s Exercise’ was installed on 33 subjects.  The evaluation study was done for a period of 04 weeks in the month of September 2014.  A post study questionnaire was filled by the participants. Male Female Series1 26 7 0 5 10 15 20 25 30 AxisTitle Gender Ratio
  23. 23. March 2016 23 Results 36% 44% 7% 13% FIRST WEEK Yes No Too busy to do it Will do but later 42% 46% 2% 10% SECOND WEEK Let's do it No, thanks Too busy to do it Will do but later 60% 31% 2% 7% THIRD WEEK Let's do it No, thanks Too busy to do it Will do but later 59%24% 3% 14% FOURTH WEEK Let's do it No, thanks Too busy to do it Will do but later
  24. 24. March 2016 24 FINAL OUTCOME First Week Second Week Third Week Fourth Week Series1 49% 52% 67% 73% 0% 10% 20% 30% 40% 50% 60% 70% 80% POSITIVERESPONSE%AGE Response Trend
  25. 25. March 2016 25 Results EFFECTIVENESS AA A N D DD The technology was effective in understanding the user context 60.6 30.3 9.1 0 0 The technology accurately determines my location 57.6 30.3 12.1 0 0 The technology accurately determines the weather 48.5 36.4 15.1 0 0 The technology was efficient in understanding the user context 66.6 27.3 6.1 0 0 The technology has motivated me to do physical activities 69.7 27.3 3 0 0 USEFULNESS AA A N D DD The technology provided is useful 54.6 36.3 9.1 0 0 The technology provided is informative 48.5 45.5 6 0 0 I would use this app frequently 48.5 39.4 9.1 3 0 The technology is convenient to use 63.6 30.3 6.1 0 0 SATISFACTION AA A N D DD I am satisfied with the technology developed 60.6 24.2 15.2 0 0 The technology performed as expected 51.5 42.4 6.1 0 0 I would adopt this app as part of my daily routine 24.2 36.4 24.2 15.2 0 The prompts/ alerts were apt and appropriate 48.5 45.4 6.1 0 0
  26. 26. March 2016 26 Papers Published  S. Gupta and S. P. Sood, “Context Awareness Mobile Agent for reducing Stress and Obesity by Motivating Physical Activity-a design approach”, 2nd International Conference on Computing for Sustainable Global Development, IEEE- IndiaCom 2015; paper presented.  Paper also published in the Book ‘Proceedings of the 9th INDIACom, 2015 2nd International Conference on Computing for Sustainable Global Development’ having ISSN 0973-7529 and ISBN 978-93-80544-15-1  S. Gupta, S. P. Sood and D. K. Jain, “Let’s Exercise: A Context Aware Mobile Agent for Motivating Physical Activity”, Third International Conference on Emerging Research in Computing, Information, Communications and Applications, SPRINGER-ERCICA 2015; paper accepted.  Paper to be also published in Springer Series ‘Advances in Intelligent Systems and Computing’ having ISSN No. 2194-5357
  27. 27. March 2016 27 Future Work  Application ‘Let’s Exercise’ published on Google Play Store and made available for free download.  Integration of additional sensors and APIs  Work Calendar / Skype Status/ inclusion of diet plans  Integration of Fitness trackers  Social Media Integration  Gami-fy the system  Score activity based points/ credits  Share on social media  Compete with friends
  28. 28. March 2016 28 Conclusion  Context Aware Computing, with their ability to sense and adapt, can help bring about a behavioral change amongst the individuals to take up physical activity.  Context Aware system could serve as a potential tool to solve real life health problems and providing personalized healthcare services to individuals.  At a broader level, Context aware computing can help solve many health-related issues and thereby help improve healthcare delivery.
  29. 29. Thank You saurav@cdac.in March 2016 29

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