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Aiding Diagnosis of Normal Pressure Hydrocephalus with Enhanced Gait Feature Separability

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. Jeffery T. Barth , Donna K. Broshek , Jason R. Freeman,

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Aiding Diagnosis of Normal Pressure Hydrocephalus with Enhanced Gait Feature Separability

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  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 Jeffery T. Barth , Donna K. Broshek, Jason R. Freeman, Hillary L. Samples Department of Psychiatry and Neurobehavioral Sciences Bradford C. Bennett Motion Analysis and Motor Performance Lab Department of Orthopedic Surgery

  2. Normal Pressure Hydrocephalus(NPH) Surgical Implant Symptoms: Cognitive degradation Gait Disturbance Urinary Incontinence Excessive accumulation cerebrospinal fluid (CSF) Diagnosis? Treatment (Shunting) Pathology Drains CSF to Abdomen

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

  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

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

  6. Platform and Data Collection TEMPO 3.1 System 6 DOF motion sensing a wrist watch form factor Developed by the INERTIA Team • 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 • 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

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

  9. Results: Nonlinear Gait Feature 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

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

  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

  13. Thanks!

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