Health Tracker for the Heart. AIA Accelerator

Transcription

1 Health Tracker for the Heart AIA Accelerator Brinc IoT CCMF Incu-Tech Incubation

2 The Problem Credit: APIR Hong Kong

3 The Problem Credit: APIR Hong Kong

4 The Problem Credit: APIR Hong Kong

5 A Global Trend Credit: Population Division, DESA, United Nations

6 A Global Trend Credit: Population Division, DESA, United Nations

7 Escalating Healthcare Cost Credit: South China Morning Post

8 Escalating Healthcare Cost Credit: Localliiz

9 Remote Patient Monitoring

10 US Annual Health Care Spending for Patients with Selected Chronic Conditions Credit: CHRT

11 Heartisans Solace

12 ECG Snapshot ECG Recording 30 second ECG snapshot on the go Record palpitations and any symptoms Share with your cardiologist

13 Blood Pressure Monitoring Peace of mind Cuff less Blood Pressure reading at your will Clinically relevant data Data portal for family members

14 Traditional Blood Pressure Monitor

15 Pain-points of current blood pressure monitor Forget to take measurements Others Cannot measure anytime, anywhere Comments in Facebook page Uncomfortable and stressful measurements 6% 5% 7% 37% Hard to measure accurately 20% 25% Too time-consuming # Findings based on consumer interviews, N=74

16 Traditional Blood Pressure Monitor

17 Pulse Transit Time

18 BP Measured by PTT

19 Symptom Log

20 Labeled Data for Supervised Machine Learning Chest Pain Shortness of Breath Tingling of arm

21 Medication Reminder

22

23 Sudden Cardiac Arrest CPR AED

24 How important is this? 84M Patients 230M Patients 1.2M Patients 380K 549K 10K SCA deaths per year SCA deaths per year SCA deaths per year

25 We calculate the risk of a cardiac arrest up to mins in advance

26 AED MAP

27 Spontaneous Ventricular Tachyarrythmia Database 106 pre-vt records, 26 pre-vf records, and 126 control records of RR interval time series in 78 subjects. recorded by implanted cardioverter defibrillators (Medtronic Jewel PlusTM ICD 7218) Each series contains between 986 and 1022 RR intervals.

28 Machine Learning Artificial Neural Network

29 Testing of Algorithm Accuracy 12. 2% True Positive True 87. 8% False True Negative 13.6 % 10.5 % 86.4 % 89.5 % True False True False

30 On-going Clinical Validation Wearable Pulse Detector to Facilitate Hemodynamic Unstable Ventricular Tachycardia Detection - Subjects: patients undergoing ICD implantation - Main Investigator: Dr. David Chung Wah Siu Effectiveness of SCA Advanced Detection Algorithm with Post-MI Patients - Main Investigator: Dr. David Chung Wah Siu

31 Team TIM LUI Co-founder SANG HWANG Co-founder ADVISER - DR. DAVID SIU Associate Professor - HKU Cardiologist - Queen Mary Hospital FELVIE CONDRILLON Head of Engineering KAREN TANG - RN Clinical Researcher CK TSE Software Engineer SAMUEL LAM Marketing and Operations Manager ANDY TO Software Engineer ANTHONY LAM Software Engineer KEVIN YUEN UX & UI Designer Front-end Developer

32 Thank you heartisanstech heartisans.com heartisanstech

33 Basic Copyright Notice & Disclaimer 2016 This presentation is copyright protected. All rights reserved. You may download or print out a hard copy for your private or internal use. You are not permitted to create any modifications or derivatives of this presentation without the prior written permission of the copyright owner. This presentation is for information purposes only and contains non-binding indications. Any opinions or views expressed are of the author and do not necessarily represent those of Swiss Re. Swiss Re makes no warranties or representations as to the accuracy, comprehensiveness, timeliness or suitability of this presentation for a particular purpose. Anyone shall at its own risk interpret and employ this presentation without relying on it in isolation. In no event will Swiss Re be liable for any loss or damages of any kind, including any direct, indirect or consequential damages, arising out of or in connection with the use of this presentation.