The Solution to the Spinal Disability Crisis? Biometric Technology The Solution to the Spinal Disability Crisis? Rick Hu, MD,FRCSC Clinical Professor, Spinal and Orthopaedic Surgery, University of Calgary Medical Director, co-Founder CaleoHealth CEO/Founder Vivametrica

Vivametrica Leadership Rick Hu, MD CEO/Founder Christy Lane Co-Founder/COO Matt Smuck, MD Co-Founder/Dir. of Research 25 Year experience with Population Health research using large scale Administrative Datasets to determine health characteristics and injury patterns Associate Professor, Mt.Royal University Exercise Scientist. Expert in Physical Activity and Health Assessment. Award winning researcher Associate Professor, Stanford University - Chief of Rehabilitation Medicine, Stanford, Expert in Physical Activity and Musculoskeletal status. Director of the Stanford Wearable Health Lab 2

Digital Biomarkers

Wearable Tech

Where We Are With Wearable Tech Rapidly advancing Health Risk assessment Injury and disability assessment Evolution into Predictive Analytics Wearables Will increase continue to increase for several years

The Blind Men and the Elephant J.G. Saxe – 1826 – 1887

Economy Psyche Anatomy

Perceived vs. Objective Change Self Reported Step Count After Before Tomkins-Lane et al. Arch Phys Med Rehabil. 2012 Nov;93(11):2008-14

Random Normal Vs. vs. “Ceiling” effect Stenosis Diagnosis Uninterrupted walking Random Vs. “Ceiling” effect Steps Normal vs. Stenosis Time Segments Steps Time Segments Tomkins-Lane CC, Haig AJ. Journal of Back and Musculoskeletal Rehabilitation

Relationship between low back pain, performance & obesity Risk Assessment Relationship between low back pain, performance & obesity Increased BMI is a risk factor for low back pain Physical activity (performance) mitigates back pain risk – more so in overweight and obese Small increases in activity have large impact on risk

Disease/Injury Monitoring/Management High Threshold Average Steps Steps Low Threshold Time Post Injury/Post Surgery Tomkins-Lane CC, Haig AJ. Journal of Back and Musculoskeletal Rehabilitation

Predictive Analytics High Threshold Health Status Activity Average Low Threshold T1 T2 Time

Lifestyle and Symptom Modification Significant improvements: Fat mass & trunk fat mass Max continuous activity Symptom severity Mental health Caloric intake

Vivametrica –Scalable Software Platform DATA Management Reference Population Data – Valid Comparisons to “LIKE” groups in the whole population DATA INPUT DATA AGNOSTIC/DEVICE AGNOSTIC Wearable and other DATA inputs, Device Agnostic, Standardized, Individualized API Flexible Outputs Incorporated into Health APPs, Mobile Insurance APPs, Online quote engines, Underwriting automation processes Personalized Risk Measures output to support products and services. Chronic illness, Mood measures, Chronic Pain, Analysis Engine Health and Risk estimates Specific to Age/Gender matched groups in the whole population Information Data Insight Action Vivametrica’s analytics and services provided via secure web access or through API to allow maximal flexibility 14

Vivametrica Analyses POPULATION REFERENCE DATA SETS >200,000 individuals in “normally” distributed population Socioeconomic, Biometric, Activity, Sleep, Mortality Adding MORE DATA monthly INDIVIDUAL ANALYSIS Comparison of characteristics of the individual to age, gender, BMI matched groups in the general population. Estimates of individual and combined health status and risks performed 15

Health Status Analyses ARTHRITIS CHRONIC CARDIAC CHRONIC LUNG MOOD vO2 MAX ROI CARDIAC FITNESS TYPE II DIABETES FINANCIAL CALCULATORS Using our proprietary algorithms we can estimate risk of chronic illness, chronic low back pain, depression and happiness in individuals using data from their wearable technology in addition to age, gender and height and weight. More specific analyses are available as additional information is added to the algorithm 16

The VivaMe Score – Simplified Health Risk Assessment (HRA) Daily activity monitoring data,RHR, SLEEP USE CASES AGE, GENDER, HEIGHT, WEIGHT,RHR MEDICAL CONDITIONS, WELL CONTROLLED Y/N LIFE STYLE CHOICES – SMOKING/ALCOHOL ⓘ Patent Pending 17

Vivametrica Online Tools Goal-Setting Tools Health Risk Assessment Benchmarked to Population Disease Specific Risk Scores

Personalized User Tools – Precision Exercise Prescription Right click and add photo ALERT

Group Health Measurement Wellness Program Effectiveness Data from 3500 Clients % Low Risk at End of Program % Low Risk Before Program

ROI Calculators – Type II Diabetes (Linkage to Claims Data)

What we need for a solution? Measurement tools Personalized Assessment Personalized Prescription Global approach Social support Engagement Alignment of stakeholders

Define / Measure / Track Scalable, Specific Relevant, economical Value Proposition Fundamental Tools Define / Measure / Track Scalable, Specific Relevant, economical Useful now Adaptable for the Future Subject Matter Expertise

For more information: Rick Hu, MD rick@vivametrica.com www.vivametrica.com