Virtual Environments

Transcription

1 Re-Learning Motor Control Using Virtual Environments Maureen K. Holden, PhD, PT Northeastern University, Boston, MA, USA International Neurorehabilitation Symposium 2009 University of Zurich, Switzerland February 13, 2009

2 Issues today in VE/Hi-Tech Rehabilitation Motor Re-Learning Assessing Motor Learning and Generalization Training Parameters Measures Study Results Ongoing and Future Work Issues for Designers, Clinicians

3 Where we are. 10+ yrs Development in Hi- Tech rehab Systems using VE, Robotics, both Some efforts at Telemedicine approach Small studies showing efficacy with variety of approaches Now focus should shift to

4 Where we should be headed. Better communication between development engineers and clinicians using the new devices Increased focus on Feature assessment on devices Value of different training parameters Value of different practice conditions, schedules Efficacy for different patient populations Larger studies

5 What are the active ingredients in motor re-learning using technology? Are VE and robotics simply TOOLS to enhance performance, not a treatment in themselves? OR Are the VE/robotics technologies themselves a treatment, and not just and adjunct to treatment?

6 The real real treatment is Actual practice of the movement What form it takes, What kind of feedback is used How practice is structured FOR SUCCESS Technology must match task demands and patient needs For example.

7 Maureen K. Holden, PhD, PT

8 How can we tell whether motor learning has occurred?

9 Performance vs. Learning Acquisition Immediate change seen during training Retention True learning Change still present hours to years later Transfer or motor generalization What else can you do?

10 Example Virtual World test Maureen K. Holden, PhD, PT

11 Virtual World - Pouring Trajectories S3 - Pre / Post 16 sessions Virtual Teacher

12 Real World Pour Test Maureen K. Holden, PhD, PT

13 Example Real World Test - Transfer Trained Location - Near Center Pre Post 16 Rx Maureen K. Holden, PhD, PT Maureen K. Holden, PhD, PT

14 Example Real World Test - Generalization Untrained Location - Far Right Pre Post 16 Rx Maureen K. Holden, PhD, PT Maureen K. Holden, PhD, PT

15 Example Real World Test - Learning across Time S1 Left-Pour Time-Mean Across Conditions Seconds Pre Post-16 Post-32

16 Training Parameters How do they affect motor relearning in and out of VE? Conditions of Practice Feedback Type and Frequency Practice Schedules

17 Concept of Deliberate Practice -(Ericsson et al. 1993) Activities specifically designed to improve the current level of performance; Requires effort and is not inherently enjoyable This can describe much of PT treatment although hopefully sometimes it is fun!!

18 Monkeys with experimental stroke in M1

19 Effects assessed by measuring cortical remapping

20 Use vs. Learning Plautz, Milliken & Nudo: (2000)

21 Plautz, Milliken & Nudo: (2000), Small Well Training

22 External vs. Internal Focus Movement planned in terms of goals in external world A task goal similar to real world function can facilitate motor learning Example- Bar horizontal vs. Keep your hands horizontal

23 Some results in patients w/ stroke Only 2 movements were trained Deliberate practice External focus goal oriented movement Idea was to test amount of motor generalization Careful selection of movements to be trained

24 Far Reach Near Reach

25 Mail Box Used to train forward reach with supination

26 Used to Train Side Reach Shoulder Abduction w/ Elbow Extension

27 S4 - Virtual World Motor Learning Mailbox Scene Pre Training Post Training

28 % Change % Change % Change Fugl- * Meyer Clinical Test Results (n=8) * FM Total UE FM Motor UE ~ Wolf * Strength Total Time * Shoulder Flexion Grip *p<0.05

29 What about Feedback? Concurrent vs Delayed feedback Immediate vs Summary Frequency of Feedback Type KR and KP Modality Visual Kinesthetic Auditory Use of a Model Error feedback

30 Examples of Feedback using my VE system Insert videos of training here

31 Practice Schedules Distributed practice shown to be best in most studies But, CI study results has shifted clinical focus to massed practice Not well studied in patient populations

32 Sensory Modalities Gross vs fine motor control Gross motor more driven by propioceptive feedback Fine motor control more driven by exteroceptive feedback Visual feedback for goal orientation and hand target coordination Auditory feedback for timing Task relevance

33 Measurements Clinical Tests Impairment based Functional assessments Combinations of these Laboratory Tests, derived from Kinematic data Kinetic data EMG data Combinations of these

34 Clinical Test Examples UE recovery and function Fugl- Meyer (stroke, TBI) Jebson Test of Hand Function Wolf Motor Test (stroke, TBI) MAL Motor Activity Log ARAT Action Research Arm Test Function / ADL measures FIM (Functional Independence Measure) Barthel Index

35 Clinical Test Examples - LE recovery, Gait and Balance Fugl- Meyer (stroke, TBI) FAC Functional Ambulation Classification 6- min Walk Test TUG Timed Get Up and Go Test DGI Dynamic Gait Index Temporal- Distance Measures Berg Balance Test (max=56) FIM (Functional Independence Measure) Range of FIM test is (18=totally independent to 126=totally dependant on another person)

36 Example of FM Range of Motion (ROM) subtest = 24 Pain subtest = 12 Sensation subtest = 24 Motor subtest = 66 Total Score (higher = healthy) =126

37 Fugl-Meyer, cont. Motor Max Score = 66 9 Subtests w/ 35 items total 1. Reflexes = 4 2. Flexor Synergy = Extensor Synergy = 6 4. Movement Combining Synergies = 6 5. Movement Out of Synergy = 6 6. Normal Reflex Activity = 2 7. Wrist Stability / AROM =10 8. Finger Flexion/ Extension and Grasp =14 9. Coordination and Speed = 6 TOTAL = 66

38 Example Jebsen 7 Functional Tasks Timed (sec.) Hand Writing Card turning Manipulating small objects Paper clips, pennies, bottle caps; grasp and drop into a container Simulated feeding (beans w/ spoon move to can) Stacking checkers Moving large light objects 5 empty 1-lb cans Moving large heavy objects 5 full 1-lb cans

39 Example Wolf Motor 15 Functional Tasks Timed (sec.) 1. Forearm to table (side): (shoulder abduction) 2. Forearm to box (side): (greater abduction) 3. Extend elbow (side): (Reach across table) 4. Extend elbow (to the side): (with 1 lb weight) 5. Hand to table (front): (lap to table) 6. Hand to box (front): (increased shoulder flex) 7. Reach and retrieve (front): (pull 1- lb weight) 8. Lift can (front): (cylindrical grasp, lift to mouth) cont.

40 Example Wolf Motor 15 Functional Tasks Timed (sec.) 9. Lift pencil (front): (3- jaw chuck grasp) 10. Pick up paper clip (front): (pincer grasp) 11. Stack checkers (front): (onto center) 12. Flip cards (front): (pincer grasp, supinate) 13. Turning the key in lock (front): (R/L, fully) 14. Fold towel (front): (grasp, fold x2) 15. Lift basket (standing): (Grasp, lift, move)

41 Home-Based Virtual Environment Training via TeleRehabiliation VE Display Video of Therapist Webcam Audio/Video Video of Patient VE Display Motion Capture VE Software at Patient Home Internet 3D Data, Software State Control Signals from Therapist VE Software at Clinic Video Camera Therapist at Clinic Patient at Home

42 Subjects (Holden, Dyar, Dayan-Cimadoro Cimadoro, 2007) N=11 (12 admitted, 1 drop out) Chronic Stroke (>6 mo post w/ no current UE rehab therapy) Age = 56.7 ± 15.6 yr. 6 Male, 5 Female 5 Right, 6 Left Hemiparesis 3.8 ± 3.1 yr. post stroke FM Motor entry score = 38.4 ± 13.9

43 Treatment Design (Holden, Dyar, Dayan-Cimadoro Cimadoro, 2007) 2 Blocks of 15 sessions: Each block, 1hr./day, 5x/wk for 3 weeks; Total=30 sessions (30 hr.) Patient at home; therapist at MIT Three categories of control trained: Reaching movements (into workspace) Hand to body movements (grooming) Repeated reciprocal movement Customized scenes for each subject

44 Upper Extremity Stroke (Holden, Dyar, Dayan-Cimadoro Cimadoro,, 2007) Mail Box: Example of Reaching into Workspace Teacher Used to train forward reach with supination Patient Start Position Example of Reaching into Workspace Task

45 Upper Extremity Stroke Sleeve Pull: Example of Hand to Body Task Hand moves up arm

46 Full Supination Upper Extremity Stroke Turning Palm Up Clock: Example of Repeated Reciprocal Task Teacher Start Front View Full Pronation

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48 Improved Performance during VE Training of Supination Rx 1 Rx 14 Rx 30

49 Mailbox Diagonal Task - S1 Velocity (top) and Position (bottom) Profiles Velocity (cm/sec) Time (sec) Velocity (cm/sec) Time (sec) Pos(cm) y x z Time (sec) Pre-Training Pos(cm) 20 0 y x z Time (sec) Post-Training

50 Fugl-Meyer - % Improved Mean Score * +6.7* +7.6* Change *p<0.003

51 Wolf Motor Mean Time Mean Time Change (sec.) * -18.4* *p<0.0125

52 Shoulder Strength - % Improved +91 %* +118 %* +169 %* *p<0.003

53 Grip Strength - % Improved +14 % +124 % +53 % p=0.025 p=0.089

54 Do the advantages of VE systems for motor retraining translate to better results in terms of motor relearning when compared to other rehabilitation techniques?

55 VR vs CI results (Holden, Dyar, Dayan-Cimadoro Cimadoro, 2007) (Wolf et. al, 2006) Telerehab VR n=11, no ctrl gp; baseline, pre/post WMT entry = 43.3s 6wk therapy; 30hr Change at 4 mo. = s, 53% decrease Constraint- Induced n= 106 in CI group; control gp=std care WMT entry= 19.3s 2wk therapy; ~60hr Change at 1 yr = s, 52% decrease

56 Future Directions Fancy Glove System Vs Cheap Glove

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58 OK Sign - Healthy Subject

59 OK Sign - Subject w/ Stroke

60 NU MUVER - Components Rehabilitation or Input Device P5 Glove Software Platform or Game Engine Panda 3D Virtual Scene Rehab Diner Image of a Healthy Subject Wearing the P5

61 NU-MUVER - Proof of Concept Scene

62 NU Ankle Portable system ROM feedback in VR Center of Pressure feedback for balance and weight shifing Adjustable resistance to active motion

63 Issues for Developers How similar is VE to real world practice How important is the veracity of simulation?? Expensive, highly flexible systems that do a lot VS Inexpensive systems that do less but are easy to operate by patients in the home environment? Can these technologies be used in a telemedicine framework? What about web-based? Remember that the nature of the task drives the relevance of sensory inputs

64 Issues for Clinicians What types of training parameters work best? Conditions of practice Feedback types Practice schedules How do effects vary by patient characteristics? What do we know about efficacy? Do the advantages of VE/robotic systems translate to better results when compared to other rehabilitation techniques?

65 Thank You!

66 Questions?

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68 Wolf Motor - % Improved