Hearty: take a closer look at your heart
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The document describes heARty, a demonstrator combining the Internet of Things and augmented reality. It uses an inexpensive "magic mirror" and pulse sensor to display a 3D model of the user's heart overlaid on their chest, beating in real-time sync with their actual heart rate. This allows users to visualize and learn about biological data spatially registered to their own body. Potential applications include improving self-care and medical training by making heart function and biometrics more engaging and understandable for both the general public and medical professionals.
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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
2015 Healthcare IT Vision: Top 5 eHealth Trends
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Real time wireless health monitoring
In the last decade the healthcare monitoring systems have drawn considerable attentions of the researchers. The prime goal was to develop a reliable patient monitoring system so that the healthcare professionals can monitor their patients, who are either hospitalized or executing their normal daily life activities. In this work we present a mobile device based wireless healthcare monitoring system that can provide real time online information about physiological conditions of a patient. Our proposed system is designed to measure and monitor important physiological data of a patient in order to accurately describe the status of her/his health and fitness. In addition the proposed system is able to send alarming message about the patient’s critical health data by text messages or by email reports. By using the information contained in the text or e-mail message the healthcare professional can provide necessary medical
advising. The system mainly consists of sensors, the data acquisition unit, microcontroller (i.e., Arduino), and software (i.e., LabVIEW). The patient’s temperature, heart beat rate, muscles, blood pressure, blood glucose level, and ECG data are monitored, displayed, and stored by our system. To ensure reliability and accuracy the proposed system has been field tested. The test results show that our system is able to measure the patient’s physiological data with a very high accuracy.
The Future of mHealth - Jay Srini - March 2011
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Digital medicine comes of age - ISDM E-Newsletter Feb 2020
This newsletter discusses the growing use of digital technologies in healthcare. It covers how digital tools are being used to track and model the spread of coronavirus. It also discusses applications of virtual reality for medical training, pain management, and personal health. Upcoming events on digital therapeutics and innovation in healthcare are also listed.
Artificial intelligence(AI) in Medical education
This document discusses the use of artificial intelligence in medical education. It describes how AI has the potential to transform medical education through personalized learning, virtual patients and simulations, medical imaging analysis, and data-driven insights. Some benefits mentioned include adaptive assessments, virtual training scenarios to practice clinical skills safely, and access to real-world case studies and evidence-based insights. The document also outlines some challenges in implementing AI and discusses ethical considerations like bias, privacy, and the need for human oversight.
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Hearty: take a closer look at your heart
- 1. heARty Take a closer look at your heart P. Hogan, G. Scavo, P. Scott, C. Valentine, F. Wild Knowledge Media Institute
- 2. 2 Demand in medical healthcare 2 Solution: healthcare decentralisation
- 4. 4 Healthcare devices Wearable Form factor Always connected (IoT/IoP) High learnability High understandability
- 5. 5 heARty heARty is a demonstrator combining IoT and Augmented Reality that shows how it is possible to improve health-related learning experience through imaging technologies and inexpensive hardware. The user stands in front of a “magic mirror” and is able to see a full-size 3D model of his heart overlaid on his chest beating at the exact same rate of his heart.
- 6. 6 heARty
- 8. 8 Implementation + pulse sensor heARty application Magic Mirror User + parametric speed heart 3D model +
- 9. 9 Advantages Convey information in a complementary channel - numbers and graphs require knowledge and expertise to be correctly interpreted Visualise biological data spatially overlaid on the “patient’s” body Visual learning of 3D information… in 3D!
- 10. 10 Potential users General public Training medical staff
- 11. 11 Conclusions Convey information spatially registered through Augmented Reality Add complementary visualisations for biological data to improve learnability for less skilled medical staff Increase engagement of self-care through the combination of wearables and AR with the metaphor of the “magic mirror”
- 12. 12 Challenges What are the biodata visualisations that AR can provide and other channels can’t? What AR visualisations are suitable to what users? Are we giving “too much” information to the final user (hypochondria)? What is the limit after which information becomes “toxic”? Live vs aggregated data
- 13. 13 Thank you. Giuseppe Scavo Knowledge Media Institute giuseppe.scavo@open.ac.uk