1. Aiding Diagnosis of Normal Pressure Hydrocephalus with Enhanced Gait Feature Separability Shanshan Chen, Adam T. Barth, Maïté Brandt-Pearce, John Lach Charles L. Brown Dept. of Electrical & Computer Engineering Bradford C. Bennett Motion Analysis and Motor Performance Lab Department of Orthopedic Surgery Jeffery T. Barth, Donna K. Broshek, Jason R. Freeman, Hillary L. Samples Department of Psychiatry and Neurobehavioral Sciences

2. Normal Pressure Hydrocephalus (NPH) 2

3. Differential Diagnosis in Clinics 3 High Volume Lumbar Puncture (HVLP) procedure Before HVLP Brain imaging Cognitive skills assessments Gait performance After HVLP Cognitive skills assessments Gait performance

4. Current Clinical Gait Evaluation 10m Walk with Stopwatch Timing Step Length Step Time Gait Speed Subjective Observation from Clinicians Limitations Low precision Incapable of capturing of subtle gait improvement Short-term Subjected to fluctuations in gait performance Incapable of capturing gradual gait improvement 4

5. Qualitative Patient Response 5 Maximal Response Gait Performance Longitudinal Timeline (days) NPH Group Individual NPH Other Dementia Groups HVLP Current observation time window

6. Platform and Data Collection 6 6 Suspected NPH Subjects 4 are diagnosed as NPH, 2 are not Inertial Sensor Nodes on Waist, Wrists, Lower Limbs Validation Shunting record and following-up studies TEMPO 3.1 System 6 DOF motion sensing a wrist watch form factor Developed by the INERTIA Team Inertial Body Sensor Networks (BSNs) Emerging Research on Gait Analysis using Inertial BSNs Less Invasive and More Wearable Potential for continuous longitudinal analysis

7. Gait Feature Extraction -- Temporal Gait Features Stride Time Standard Deviation Average Double Stance Time Neither Feature Separates the NPH Group and non-NPH Group 7

8. NPH Subject after HVLP Healthy Subject Gait Feature Extraction -- via Nonlinear Analysis 8 Different Diverging Rates of Different Gaits Lyapunov Exponent (LyE) NPH Subject before HVLP

9. Results: Nonlinear Gait Feature 9 Lyapunov Exponent  Gait Stability

10. Future Work Larger Size Study Clinical Interface in Development Visualization of the data Interpretation of the data Longer-term Monitoring 10

11. 11 Maximal Response Gait Performance Longitudinal Timeline (days) NPH Group Individual NPH Other Dementia Groups HVLP Future Observation time window Future Work

12. Conclusion Pilot Study Real system deployment on real subjects Advanced Signal Processing with Domain Knowledge Identifying and extracting relevant features Providing separability to aid clinical decision Exemplification 12

13. Thanks!