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Online Estimation of Elbow Joint Angle Using Upper Arm Acceleration: A Movement Partitioning Approach.

M Farokhzadi1, A Maleki1,2, A Fallah1

  • 1Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran.

Journal of Biomedical Physics & Engineering
|October 31, 2017
PubMed
Summary

This study developed an online method to estimate elbow angles from shoulder data for Functional Electrical Stimulation (FES) systems. The approach improves control for C5/C6 spinal cord injury patients during daily activities.

Keywords:
Activities of Daily Living (ADL)Hierarchical StructureMovement PhasesAngle Estimation

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Neuroscience

Background:

  • Functional Electrical Stimulation (FES) systems require accurate joint angle estimation for effective control.
  • Elbow-shoulder synergies are crucial for understanding upper limb movement in individuals with spinal cord injury (SCI).
  • Assisting C5/C6 SCI patients necessitates reliable methods for estimating elbow joint movement.

Purpose of the Study:

  • To develop an online method for estimating elbow flexion/extension angles using upper arm acceleration signals.
  • To implement a hierarchical approach incorporating 'movement phases' for structured and efficient angle estimation.
  • To enhance FES control systems through accurate and real-time joint angle prediction.

Main Methods:

  • A three-level hierarchical structure involving clustering, Hidden Markov Models (HMMs) for recognition, and neural networks for angle estimation.
  • Partitioning of Activities of Daily Living (ADLs) into distinct movement phases.
  • Utilizing upper arm acceleration data and incorporating varied object locations to improve neural network generalization.

Main Results:

  • Achieved a cross-correlation coefficient (K) of 90.25% and Normalized Root Mean Squared Error (NRMSE) of 13.64% for estimated elbow angles.
  • A post-processing technique improved results to K = 91.19% and NRMSE = 12.83%, addressing discontinuity intervals.
  • Demonstrated the effectiveness of the 'movement phases' approach for online estimation.

Conclusions:

  • The proposed online estimation method is valuable for FES control systems, particularly for C5/C6 SCI patients.
  • The hierarchical structure and 'movement phases' approach provide an efficient and structured method for joint angle estimation.
  • The study highlights the potential of using upper arm acceleration for real-time elbow angle tracking in rehabilitation applications.