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Lower extremity angle measurement with accelerometers--error and sensitivity analysis.

A T Willemsen1, C Frigo, H B Boom

  • 1Department of Electrical Engineering, University of Twente, Enschede, The Netherlands.

IEEE Transactions on Bio-Medical Engineering
|December 1, 1991
PubMed
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This study assessed accelerometers for functional neuromuscular stimulation (FNS) feedback in paraplegic locomotion restoration. Model assumptions, particularly rigid-body errors at high frequencies, significantly impacted angle assessment accuracy.

Area of Science:

  • Biomechanics
  • Rehabilitation Engineering
  • Control Systems

Background:

  • Functional neuromuscular stimulation (FNS) aims to restore locomotion for paraplegic individuals.
  • Closed-loop control systems are crucial for enhancing FNS effectiveness.
  • Accelerometers offer potential for real-time feedback parameter assessment in FNS.

Purpose of the Study:

  • To evaluate and assess the accuracy of using accelerometers for lower extremity angle assessment in FNS.
  • To perform an error and sensitivity analysis of accelerometer-based angle assessment using healthy subject data.
  • To identify dominant error sources impacting the reliability of accelerometer-based locomotion feedback.

Main Methods:

  • Utilized accelerometers for lower extremity angle assessment in healthy subjects.

Related Experiment Videos

  • Conducted error and sensitivity analysis considering reference systems, accelerometer performance, and model assumptions.
  • Employed the Elite video motion analysis system for data acquisition and comparison.
  • Calculated errors based on rigid-body assumptions, accelerometer fixation, and 2D walking pattern models.

    • Main Results:

    • Model assumptions, especially rigid-body approximations, were the most significant error source.
    • High-frequency vibrations (>10 Hz) led to errors exceeding one radian due to rigid-body assumption violations.
    • Low-frequency errors (<5 Hz) were influenced by imperfect accelerometer fixation and non-hinge knee joints (+/- 0.03 rad).
    • A 2D walking pattern assumption introduced an error of +/- 0.04 rad.

    Conclusions:

    • Accelerometer-based angle assessment for FNS requires careful consideration of model assumptions for accurate locomotion feedback.
    • Rigid-body and 2D motion assumptions introduce significant errors, particularly at higher frequencies.
    • Total computed low-frequency errors are comparable to experimental differences, highlighting the need for model refinement.