7/13/2011 Research Question Optimizing Functional Walking after Neurological Injury: Split-belt Walking and other Novel Approaches What are the most effective methods to retrain walking after injury to the CNS? Kristin Musselman PhD, PT [email protected] Slide 1 Part 1: Split-belt Studies in Young Children Babies on Treadmills • Cerebellum is important for split-belt adaptation • Young children show adaptation – learning is more sensitive to size of motor error & previous experience compared with adults • Split-belt walking can correct asymmetric gait Slide 2 Split-belt Walking Part 1 – Split-belt Work Slide 3 Split-belt Adaptation in Adults Aftereffect (Morton & Bastian 2006) Part 1 – Split-belt Work Slide 4 Part 1 – Split-belt Work Slide 5 1 7/13/2011 61% Adapted Step Length Why do some adapt/not adapt? • 25 children • 8 – 36 months (Musselman et al. J Neurophysiol 2011) Part 1 – Split-belt Work Slide 6 Part 1 – Split-belt Work Protocol for Error Study Error Size may affect learning Part 1 –Split-belt Walking Slide 7 Slide 8 Part 1 – Split-belt Work Slide 9 Promising therapy for asymmetric gait? Preliminary Results: Group Double Support Symmetry Child post-hemispherectomy (Choi et al. 2009) How can we optimize transfer? Part 1 – Split-belt Work Slide 10 Part 1 – Split-belt Work Slide 11 2 7/13/2011 Part 2: Functional Walking Post-SCI Summary Part 1: Split-belt Studies • Children as young as ~10mos can adapt • Many walking skills are needed for walking in the home & community • Children more sensitive to size of motor error and previous experience than adults • SCI-FAP is a valid & reliable measure of functional walking for chronic SCI • Split-belt walking can correct gait asymmetries • Skill training is effective at improving walking ability post-SCI • Investigating ways to ↑ transfer of learning from treadmill to over-ground walking Part 1 – Split-belt Work Slide 12 Part 2 – SCI Work Walking Survey What is functional walking? Surface None 1-3 times 4-9 times >10 times a) Smooth (e.g. tile, Distance Curbs Slide 13 Specific Surface linoleum, hardwood) X tile, linoleum b) Rough (e.g. concrete, X grass, carpet (Lerner-Frankiel et al. 1986) Min velocity 0.5m/s carpet) (Robinett & Vondran 1988, Andrews et al. 2010) c) Slippery (e.g. wet Uneven surfaces d) Soft (e.g. thick floor, ice) carpet, gym mat) (Lord et al. 2004) e) Uneven (e.g. dirt path, gravel) (Patla & Shumway-Cook 1999, 2002) f) Deep (e.g. long grass, Part 2 – SCI Work Slide 14 deep snow) mopped floor X gym mat X 8 dimensions (Andrews et al. 2010) X X Part 2 – SCI Work Most Frequent Walking Tasks Identified pavement Slide 15 Walking & Carrying (Musselman & Yang J Rehabil Med 2007) Part 2 – SCI Work Slide 16 Part 2 – SCI Work Slide 17 3 7/13/2011 The SCI-FAP Scoring the SCI-FAP 1. Carpet 2. Up & Go Assistance Rating 1 = Independent 2 = 1 cane/1 crutch/1 rail 3 = 2 canes/2 crutches/2 rails 4 = Walker 5 = 1 person assist 6 = Unable to complete mEFAP 3. Obstacles 4. Stairs 5. Carry 6. Step Task score = time X assistance rating mean able-bodied time 7. Door Total SCI-FAP score = task scores Part 2 – SCI Work Slide 18 Part 2 – SCI Work Slide 19 Reliability & Validity of the SCI-FAP High reliability Interrater (ICC = 1.00) & test-retest (ICC = 0.98) Content validity Importance of tasks confirmed by experts Discriminative validity Mean scores SCI = 271.3 + 451.0, able-bodied = 7.2 + 0.8 Convergent validity SCI-FAP score correlated with 6MW, 10MW, WISCI II (r = -0.59 to -0.68) Step score = time X assistance rating = 22.6s X 3 = 18.3 mean able-bodied time 3.7s Part 2 – SCI Work (Musselman et al. Neurorehabil Neural Repair 2011) Slide 20 Part 2 – SCI Work Slide 21 Training Skill Walking 1. Important tasks 2. Challenging 3. Variety (Musselman et al. Phys Ther 2009) Part 2 – SCI Work Slide 22 Part 2 – SCI Work Slide 23 4 7/13/2011 mEFAP Summary Part 2: Training & Assessment of Functional Walking • Many skills needed for daily walking • SCI-FAP is a valid & reliable measure of functional walking for chronic SCI • Skill training effectively improves walking speed, skill, endurance and confidence after incomplete SCI Part 2 – SCI Work Slide 24 Part 2 – SCI Work Slide 25 Future Research Measurement 1) Measurement 2) Training 3) Retention Assessments of functional walking lacking (Lord & Rochester 2005, Lam et al. 2008) Goal: Develop measures of: a) functional walking ability b) participation in daily walking Part 3 – Future Work Slide 26 Part 3 – Future Work Measuring Participation Slide 27 Measuring Participation Step Activity Monitor Step Activity Monitor • valid & reliable tool • valid & reliable tool (Haeuber et al. 2004, Mudge et al. 2007, Bowden & Behrman 2007) (Haeuber et al. 2004, Mudge et al. 2007, Bowden & Behrman 2007) + + Questionnaire Walking Log (Resnick et al. 2008) Focus group → Content validity → Reliability, Validity, Sensitivity to change & MCID Part 3 – Future Work Slide 28 Part 3 – Future Work Slide 28 5 7/13/2011 Training Parameters: Specificity Training Parameters: Specificity Partial transfer from split-belt to over-ground walking (Reisman et al. 2009) Train 1 task → worsening of related tasks Goal: Determine extent of transfer between related tasks (Edgerton et al. 1997, Girgis et al. 2007, García-Alías et al. 2009) Train stair-climbing → improved locomotion (Singh et al. 2010) Part 3 – Future Work Slide 29 Part 3 – Future Work Training Parameters: Specificity Slide 30 Retention of Walking Ability Procedure: Little known about walking activity post-rehab (Michael et al. 2005, Patterson et al. 2007) • 6 weeks (Manns & Baldwin 2009) • very low compared with sedentary older adults during 1st (Michael et al. 2005) Assessments: Goals: • Success/failures, speed • Kinematic, EMG analysis • Neurophysiological changes – e.g., TMS a) Describe retention post-rehab b) Identify contributing factors c) Prediction Part 3 – Future Work Slide 31 Dependent Variables: Functional walking ability & participation Part 3 – Future Work Slide 32 Retention of Walking Ability Retention of Walking Ability Independent Variables: Balance Speed LE strength CV fitness impairment Depression Part 3 – Future Work Analysis: Prediction – Machine Learning Age Stroke severity LE Comorbidity Endurance Slide 33 • E.g., Predicting patients at risk for emergency C-section (Mitchell 1997) Learned Rule: If No previous vaginal delivery, and Abnormal 2nd trimester ultrasound, and Malpresentation at admission Then Probability of emergency C-section is 0.6 Part 3 – Future Work Slide 34 6 7/13/2011 Summary Part 3: Future Work Acknowledgements Dr. Jaynie Yang, U of A Yang Lab Susan Patrick Rosie Vishram Kelly Brunton Jen McPhail Katelyn Brown Colleen Budzinski • Maximize functional walking post-injury optimal training parameters prevent decline in walking valid & reliable measurement • Collaborations clinicians, neuroscientists, computer scientists within Dept., University, other institutions Dr. Amy Bastian, JHU Bastian Lab Erin Vasudevan Katie Amenebar Laura Malone James Finley Gelsy Torres-Oviedo Alex Vasquez Gowri Jayaram Dr. Tania Lam, UBC • Applicable to many areas of rehab research Part 3 – Future Work Slide 35 Slide 36 7
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