Development of a mobile medical application for imaging and analysis of arthritis of the hand

2014 CMBEC37 ConferenceVancouver, BC

May 21 – 23, 2014etreatmd.com

Nicholas MacKinnon, Shanil Gunasekara, Fartash Vasefi

May 2014©2014 eTreat Medical Diagnostics Inc.

www.etreatmd.comCorresponding author: [email protected]

DEVELOPMENT OF A MOBILE MEDICAL APPLICATION FOR IMAGING AND

ANALYSIS OF ARTHRITIS OF THE HANDeTreat Medical Diagnostics Inc.



Outline

• eTreat Mobile Health Approach

• Hand Arthritis

• Image transfer and security

• Image Analysis

• Reporting and Tracking

• Arthtrac Market

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eTreat Mobile Health

• Mobile apps and cloud computing to manage

chronic health problems throughout the world



Global Demand for Mobile Health Applications

• By 2017 mobile health revenue to reach $23 billion

• 70% will be chronic disease management.

• eTreat is focused on apps directed to chronic diseases

such as arthritis, diabetic ulcers, chronic wounds, skin

conditions and muscular/skeletal disorders.



• App captures data from camera and sensors of phone

• App captures user input from prompts

• Data upload for analysis and cloud health record

• Information and reports go to users, clinicians, etc.

eTreat Mobile Health Concept



Specific Apps for Specific Conditions

• App provides a report like a lab test

• Asks questions and logs data

• Provides useful information and reminders to user

• Info stored securely in cloud Electronic Health Record



Secure Cloud Processing and EHR

• Every App has a cloud processing engine and database

• EHR captures and logs user encounters with App

• Data and analyses captured by EHR

• EHR is a full clinical record system ( HIPA, HL7 compliant)

• Data owned by the user

• Can send to medical practitioners and other EHR systems



First Chronic Disease App – Hand Arthritis

• Common chronic health problem affecting articulating joints

• Causes pain, deformity and moderate to severe disability.

• Symptomatic OA has inflammatory episodes that result in joint swelling and tenderness

• Irritation of nerves and blood vessels of synovial membrane (encapsulates and lubricates the joint)

Disease Africa The Americas

Eastern

Mediterranean Europe

South-East

Asia

Western

Pacific

Population 857 939 605 899 1830 1808

Hand Arthritis 58 64 41 61 124 123

Foot Arthritis 54 59 38 57 115 114

Hand and Foot Arthritis Prevalence (millions) by WHO region, 2004

Radiographic Arthritis

Symptomatic

Arthritis



ArthTrac: Procedure overview

User log-in/registration

Instructions for image capture

Capture image of the subject hand on white

letter/A4 size paper

Verify Image is OK

Send image to cloud for image analysis (patent

pending method)

Store data to cloud electronic health record

(EHR)

Receive processed image from cloud

Receive measurement data analysis report



ArthTrac: Procedure overview and Screenshots

User log-in/registration

Instructions for image capture

Capture image of the subject hand on white

letter/A4 size paper

Verify Image is OK

Send image to cloud for image analysis (patent

pending method)

Store data to cloud electronic health record

(EHR)

Receive processed image from cloud

Receive measurement data analysis report



Image Processing :

Distortion removalSpatial calibration

Background removalAnatomical analysis

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A

B

CD A’ B’

C’D’

21

6 m

m

279 mm

ArthTrac: Distortion correction and calibration

– Letter/ A4 Paper is identified

–Distortion is removed

– Image is cropped and scaled



ArthTrac: Image processing identifies hand

– Image processing software processes and segments image

– Hand is separated from Background

– The image is analyzed and converted to a binary format

– The binary image is analyzed and the boundary determined

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0 200 400 600 800 1000 1200 1400 1600 1800400

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800

1000

1200

1400

1600

1800

2000

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ArthTrac: Boundary information is analyzed

• Boundary image can now be analyzed to provide arthritis metrics

• Analysis algorithm identifies key fiduciary feature coordinates

• Tips and vertexes of fingers

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ϴ

ArthTrac: Features located on boundary data

– Fiduciary features of hand are now identified

– Boundary image can now be analyzed to provide arthritis metrics

– Distances, angles, widths can become features for analysis

– From analysis can identify anatomical irregularities

– Anatomical characteristics can be compared over time

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(1) (2)

(3) (4)

Analysis of Normal and Arthritic Hand

• Normal Hand • Osteoarthritic Hand

(5) (6)

(7) (8)



(1)

100 200 300 400 500 600140

150

160

170

180

100 200 300 400 500140

160

180

200

Finger #3 Thickness

Finger #2 Thickness

Analysis of Phalange Width



Analysis of Phalange Angular Deviation

• Normal Hand • Osteoarthritic Hand



ArthTrac: Secure Transfer to Servers and EHR

• Regulatory Compliance

– HIPAA compliant to ensure confidentiality

– CEN ISO/IEEE 11073 standard

– HL7 compliant data to effectively interface with electronic health record

– ISO 13485 / GMP compliant as medical device

– Fingerprint blurring for additional security

– Cloud based app and image processing server

– Cloud based EHR database server

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May 21 – 23, 2014etreatmd.com27

Conclusion

• eTreat is focusing on chronic disease apps for arthritis, diabetes, chronic wounds, skin conditions and muscular/skeletal disorders.

• Our prototype of our first app for hand arthritis, using cloud image processing has been demonstrated

• The scientific basis of our patent pending image analysis software has been described

• Questions?

Website: etreatmd.com

Tel: 1+ 604.836.5482

[email protected]

Development of a mobile medical application for imaging and analysis of arthritis of the hand

Health & Medicine

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