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An Evaluation of the Leap Motion Depth Sensing Camera for Tracking Hand and Fingers Motion in Physical Therapy
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An Evaluation of the Leap Motion Depth Sensing Camera for Tracking Hand and Fingers Motion in Physical Therapy

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An Evaluation of the Leap Motion Depth Sensing Camera for Tracking Hand and Fingers Motion in Physical Therapy by Darryl Charles, Katy Pedlow, Suzanne McDonough, …

An Evaluation of the Leap Motion Depth Sensing Camera for Tracking Hand and Fingers Motion in Physical Therapy by Darryl Charles, Katy Pedlow, Suzanne McDonough,
Ka Shek and Therese Charles

Published in: Technology, Health & Medicine

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  • 1. Close Range Depth Sensing Cameras for Virtual Reality based Hand Rehabilitation Darryl Charles1, Katy Pedlow2, Suzanne McDonough2, Ka Shek3, and Therese Charles3 1Computer Science Research Institute, School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland BT52 1SA 2Centre for Health and Rehabilitation Technologies, School of Health Sciences, University of Ulster, Jordanstown, Northern Ireland BT37 0QB 3SilverFish Studios, Coleraine, Northern Ireland BT52 2NR
  • 2. Introduction • Our interest is in low cost, technology based, games enhanced physical rehabilitation • Previous work has used webcams and Kinect – Effective but has issues, e.g. lag and resolution • Leap Camera released – Low lag, high resolution tracking of fingers – We investigated beta camera and sdk – Developed several VR therapies for fingers. • In this paper we present results from trials with professional physiotherapists
  • 3. Previous Research • Video of previous webcam and augmented reality games from Ulster ->
  • 4. Leap Motion Camera/Controller
  • 5. Leap Motion camera/controller • Low cost (approx. £70 in the UK) • Small (0.5” x 1.2” x 3” with a weight of 0.1 pounds) • Built-in infrared LEDs to detect objects within a dome of approximately 8 cubic feet above it • Minimal latency and high spatial precision (0.01mm)
  • 6. Leap Demo • On Screen (Visualizer + other examples)
  • 7. Method • Construct virtual simulations of 3 common rehab tasks for hand and fingers – Leap Motion and a natural interface controller – Use a 3D game engine for construction – Collaborate with commercial developers (SilverFish Studios) and academics from the Centre for Health and Rehabilitation Technologies (CHaRT) • Trial simulated tasks with clinicians – Give us understanding of the potential and limitations of the Leap – Obtain feedback from professionals at Regional Acquired Brain Injury Unit (RABIU) at Musgrave Hospital in Belfast before considering patient trials
  • 8. Task 1 – Cotton Balls Activity Description Progression Parameters Feedback Parameters Cotton balls and a container are placed on a table. The user is asked to pick the cotton balls up off of the table and place them in the container. The use is encouraged to use a pincer grasp. • Size of Container • Distance of container from user • Height of container • Number of cotton balls • Time required to place a set number of cotton balls in the container • Number of repetitions
  • 9. Task 2 – Stacking Blocks Activity Description The user is given rectangular blocks (wooden or plastic), and is asked to build a tower by stacking blocks vertically on the table. Progression • Distance of blocks from the user. Parameters • Number of blocks • Size of blocks Feedback Parameters • Number of repetitions in a set time period • Time: Time required to complete the task
  • 10. Task 3 - Nine Hole Peg Test (NHPT) • The standardized equipment for the test typically consists of: – A board, in wood or plastic, with 9 holes (10 mm diameter, 15 mm depth), placed apart by 32 mm (Mathiowetz et al. 1985) or 50 mm (Heller et al. 1987) – A container for the pegs. Initially the container was a square box (100 x 100 x 10 mm) apart from the board. The most current container is a shallow round dish at the end of the board (Grice et al., 2003) – 9 pegs (7 mm diameter, 32 mm length) (Mathiowetz et al. 1985) – Stopwatch
  • 11. Virtual Tasks • Video or live demo of software Screenshots of three simulated rehab tasks. From left to right: Cotton Balls, Nine Hole Peg Test, and Stacking Blocks.
  • 12. Trial Participants Participant Q1. Occupation 1 Physiotherapist 2 3 4 5 6 7 8 Q2. Years of Experience 10+ Q3. Use Games for Rehab No Q4. Play Games Occupational Therapist Student 10+ Yes Occasionally 0 No Never Occupational Therapist Occupational Therapist Occupational Therapist Occupational Therapist Occupational Therapist 1-2 Yes Occasionally 3-5 Yes Occasionally 3-5 Yes Never 5-10 Yes Occasionally 5-10 Yes Never Occasionally
  • 13. Post Trial Questions Background information 1. What is your occupation? Physiotherapist / Occupational therapist / Other 2. How many years clinical experience do you have? 3. Do you use computer games for rehabilitation? YES/NO System specific questions (Answers on a Likert Scale 1 – 7) 4. Do you play games? 5. I feel that with practise I would become proficient in using the control interface 6. I feel that with practise I would become proficient in using the control interface 7. The tasks presented on the screen are easy to understand 8. The content on the screen is appropriate for the patient population 9. The prototypes provide a good illustration of all the functionalities I would require it to have e.g. type of tasks, movements emphasised Patient population related questions (Answers on a Likert Scale 1 – 7) 10. I feel it would be easy to use this system in my clinical environment 11. I can see the benefit of this system for my general patient population 12. I can see the benefit of this system for the older patient population 13. I can see the benefit of this system for the younger patient population 14. I feel patients would be motivated to use this system 15. I feel my patients would benefit from this type of system in their home environment 16. I feel the system needs to be adapted to suit my patient population Please state how it would need adapted (follow up comment)
  • 14. Full Results
  • 15. Mean Responses per Question
  • 16. Variation per Participant Participant Q1. Occupation Q2. Years of Experience Q3. Use Games for Rehab Q4. Play Games Q5 – Q16 Mean Response Interquartile Range 1 Physiotherapist 10+ No Occasionally 1.33 0.75 2 Occupational Therapist 10+ Yes Occasionally 2.25 0.75 3 Student 0 No Never 2.67 2.5 4 Occupational Therapist 1-2 Yes Occasionally 4.00 2 5 Occupational Therapist 3-5 Yes Occasionally 1.75 1.75 6 Occupational Therapist 3-5 Yes Never 4.17 1 7 Occupational Therapist 5-10 Yes Occasionally 1.00 0 8 Occupational Therapist 5-10 Yes Never 3.58 3 6 Yes 2 No 5 Occasionally 3 Never 2.59 (Mean) 1.47 (Mean) Summary
  • 17. Summary of Results • Mean response to all questions = 2.59 (scale 1-7) – Six of respondents had a mean response to the questions of less than 3 • 4 clinicians over 5 years experience provided a (mean = 2.04) – 4 other responded with a (mean = 3.14) • • • • Tasks easy to understand (mean = 1.88) Good illustration of rehab tasks (mean = 2.38) Suitable for young patients (mean = 1.6) Suitable for home environment (mean = 2.5)
  • 18. Discussion • Ease of use of system – We spent most time on this – it is tricky! – Some clinicians did the interface tricky – especially at the start • Issues: its an unfamiliar UI, hand position must remain parallel to table surface (+/- 10 degrees or so) • Lessons: user needs time to attune, lots of positions cues required, VR headset like Oculus Rift may help – Several clinicians felt that older people could have problems learning to use the system • Clinicians felt that the system has potential but the tasks should be converted into games and could be more tailored to their treatements • Clinicians were excited about the use of the system in the home – especially since it is so cheap and easy to set up.
  • 19. Participant Comments • “Develop programmes for different orientation, i.e. vertical and horizontal” (Participant 1) • “More functional activities; i.e. lift a cup, bringing to a mouth. Puzzles - to incorporate cognitive skills” (Participant 4) • “May be set games for different age groups” (Participant 7)
  • 20. Conclusion • The results were very encouraging • We have learned a lot about designed virtual rehab. software that use the Leap controller • Next phase – Move software to Unity3D – Design games for the Leap in collaboration with clinicians – Trial games with patients