1. Novel Smart Sensor Glove for Arthritis Rehabilitation
Names: Alon Tsilik, Gal Halevi, Boaz Katzover
21/05/2014

2. Overview RA – What is it? Statistics Detection and detection issues
Main goal and motivations
Current gloves systems
Tyndell/uu glove
Tyndell/uu glove software
Gloves systems in VR and gaming

3. RA RA affects the synovial tissue that lubricates the joints.
This condition affects bones, joints and muscles.
Stiffness, swelling and Lack of Flexibility are common symptoms.

4. Statistics In 2010, RA affected 500,000 of the UK populations.
4-10 Patients lose their jobs in 5 years of diagnosis.
the most common condition for which people
receive Disability Living Allowance

5. Current detection methods
RA is currently diagnosed by clinicians and therapists using x-rays and manual evaluation methods.
Current techniques
HAQ, Grip Strength Dynamometer,
Goniometer, Tape measure

6. Current detection issues
Outcomes are easily influenced by clinicians training and experience.
All measurements are recorded in handwritten form.
Joint stiffness is currently unmeasured.
Current process is time consuming.

7. Main goal
This project focuses on an accurate hand measurement tool to detect hand Range of Motion (ROM), joint stiffness and to match each specific patient the treatment that is the best for him.
The motivation for developing a smart sensor glove:
More accurate diagnostic .
Measure joint angles in a dynamic way.
Less time spend on diagnostic.
Patient can perform tasks at home.

8. Gloves Systems Gloves structure Sensors on a cotton glove Gloves roles
1.Measuring fingers movement
2.Measuring fingers range of movement
Disadvantages
1.Physically fits to a specific size
2.Adjust calibration for each patient

9. Popular Data Gloves Systems currently available
Cyber glove
22 bend sensor
virtual bend
calibration calibration calibration
5DT
14 optic fiber sensors
X-IST
5 bend sensors + 5 pressure sensors
or 15 bend sensors + double axis sensor
cotton + silk

10. Tyndell/UU 20 bend sensors 16 triple axis sensors 11 force sensors
Flexible PCB
No calibration requires
Fits with both hands by flipping the PCB
wireless data transformation
Visual image by program

11. Rehabilitative System Design - Overview
Biomechanical model – Model of the human hand illustrating bones & joints of interest.
Sensors choice – Sensor that have been picked, where they are placed and why.
Hardware spec – Flexible PCB ,Zigbee.
Patient’s tasks – Preconditions and how it will be done.

12. Biomechanical model

13. Sensors choice Main objective
The glove integrates a total number of 47 sensors mainly to capture hand and finger motion.
Main objective
Measurement of joint range of the hand, including:
Extension
Flexion
Adduction/Abduction
of the MCP, PIP and DIP joints of the fingers and thumb in degrees.

14. Bend sensors
The bend sensors measures the finger flexion, joint movement, splaying of fingers and wrist rotation.
The position of the bend sensors cross over the DIP, PIP and MCP joints, between the fingers and an additional bend sensor on the lateral side of the wrist.

15. Kapandji index measurement

16. Force sensors
The 11 force sensors are mainly used for the Kapandji index measurement (also known as opposition scale).
The force sensors are located on the tip of the index, middle, ring and little fingers. In addition there are 3 more force sensors along the index finger and 4 more on the little finger.

17. tri-axial accelerometers
The glove integrates 16 3-axial accelerometers. One on each of the finger’s phalanx and one on the palm.
They provide additional useful information on the rotation motion of the hand such as shaking/vibration motion.

18. Flexible Circuit PCB What is a PCB?
Contains 8 layers with overall thickness of mm.
Meander type structure.
How data is transferred? Zigbee.

19. Patients tasks– First steps
Before talking about the UI we need to explain how the treatment with the help of the glove will carry out.
The software system manages objective routines defined by a clinician and performed by the patient at home at set times thorough the day.

20. Patients tasks
1. Attend a clinic session - Each patient has to undergo some basic training. 2. During this visit the results are recorded and used as a comparison to future objectives completed at home. 3. The objectives are typically completed first thing in the morning when the patient arises, at lunchtime and in the evening.

21. Software system and task’s results
Software system calculates angular and velocity data generated from the glove when the patient is performing an objective routine.
Completed routines are uploaded to a cloud system for immediate access by the clinician for analysis and patient feedback.

22. The Analysis of Data
The software as an assistive tool for analyzing data.
The benefit in the use of sensors.
The software as a measuring tool.
The control system (Clinician side).
Patient side interface.

23. The Analysis of Data An objective consists of 12 to 20 repetitions.
Each one is analyzed for time taken during flexion and extension, minimum and maximum ROM and minimum and maximum velocity.
Analysis of angular and velocity percentage change throughout
each flexion and extension portion of a repetition provides
dynamic analysis of joint movement and an indicator of change between repetitions
Information is used by the clinician as an assistive tool to detect change in movement over time for each patient.

24. The use of sensors – The Benefit
Multiple accelerometers, bend sensors and force sensors eliminates the need for calibration and offers accessibility to users with limited ROM.
Accelerometers - improve accuracy of both static and dynamic finger joint movement.
Bend sensors - work in collaboration with accelerometers to accurately measure finger joint angle, velocity and acceleration.
Force sensors - provide measurement for opposition testing of the thumb to the fingers and palm, such as Kapandji scoring.

25. The software as a measuring tool
Minimal and maximum flexion and extension ranges of each digit.
Adduction and abduction range for each digit.
Thumb-index finger web space.
Amount of joint stiffness for each digit.
Recording, storage and analysis of patient data.
Analysis of historical patient movement

26. The Control System
Live movement data captured from the data glove is displayed numerically and graphically.
Numeric data includes bend sensor, force sensor and three axes from each accelerometer.
A 3D hand graphically represents numerical data captured from the glove.
The hand moves synchronously with all glove sensors.

27. How is the data received from the glove displayed by the controlling software?
Objective summary window
Objective detail window
Bend sensor data is converted to degrees and verified against accelerometer calculations.
Completed objective routines are shown in the objective summary window (a).
An objective consists of many repetitions that are displayed in the objective detail window(b). One repetition is achieved once the joint under
investigation is opened and closed. Repetitions consist of velocity (c) and angular movement (d). Charts show repetitions 1-4 in overlay mode allowing instant comparison of repetitions.
Velocity movement
Angular movement

28. Dynamic Movement Characterization Using A Data Glove
Flexion and extension movement is sigmoidal shaped and an open-closed hand movement produces a Gaussian shaped curve.
Angular velocity and angular acceleration become inaccurate..

29. Summary panel for each group of repetitions within the reference point
Detailed breakdown of each repetition for each reference point sensor
The comparison objective summary panel
Fig. 12(A) is a summary panel for each group of repetitions
within the reference point. Each summary displays the
maximum degree change and overall percentage change for
total flexion and extension movement. Fig. 12(B) provides a
detailed breakdown of each repetition for each reference point
sensor. It displays peak flexion and extension angular and
percentage change, together with peak velocity change. Fig.
12(C) displays the comparison objective summary panel. It too
displays maximum angular and velocity degree change for
flexion and extension movement. Fig 11(D) displays a detailed
breakdown for each glove sensor included in the selected
objective summary.
Detailed breakdown for each glove sensor included in the selected objective summary

30. Patient Interface
Provides live feedback of glove sensor movement and progress of the objective routine performed by the patient.
The repetition progress panel provides real-time indicators on
the status of each flexion and extension action for each sensor
included in the objective routine.
Hand movement performed by the patient is displayed as a 3D animated hand

31. Conclusions
To date, Clinicians use manual, time consuming techniques to quantify hand limitations.
Current methods have the capability to detect hand ROM, with some issues.
The proposed system will provide an automatic hand ROM measuring tool capable of measuring joint movement, joint stiffness and comparison analysis of historical movement data.

32. Gloves in VR and Gaming
Cyber gloves can be used in the virtual reality and gaming industry
In the past there were wired gloves that can be used even as a mouse
Today most gloves are wireless or Bluetooth technology
Most gloves are also can provide there position in
the 3D space together with the specific
hand/figure position

33. Cyber Glove

34. CyberGlove 3 provides up to 22 high-accuracy joint-angle measurements
Sensor resolution: <1 degree
up to 120 records/sec
30 meter radius from Wi-Fi source
Wireless technology
Operating system Windows 7
Interface: Wi-Fi, USB, micro SD card

35. CyberGlove 3 8-sensor model features : 2 bend sensors on each finger
4 abduction sensors
Sensors measuring thumb crossover, palm arch, wrist flexion,
and wrist abduction.
Each sensor is extremely thin and flexible being virtually undetectable in the lightweight elastic glove.
Designed for Comfort and Functionality

36. System extras Two batteries and an external battery charger
Provisions for InterSense, Polhemus, and Ascension six degrees of freedom (DOF) tracking sensors are available for the glove wristband. That supported in VirtualHand software.

37. Of VR Examples

38. The virtual glove in gaming

39. P5 Based upon proprietary bend sensor and remote tracking
Provides users total intuitive interaction with 3D and virtual environments, such as games, websites and educational software.
Retail price of $39.00

40. Specs
Lightweight, ergonomic design for easy, intuitive play. Weighs just 125 grams.
5 independent finger measurements
optical tracking system
6 degrees of tracking (X, Y, Z, Yaw, Pitch and Roll) to ensure realistic movement Bend-sensor and optical-tracking technology to provide true-to-life mobility
Easy, plug-and-play setup – plugs
right into the USB port of your PC
Infrared control receptor

41. P5 Glove

42. Have a pleasant evening
Thanks for listening…
Have a pleasant evening