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Published on: December 14, 2011
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Trunk Posture from Randomly Oriented Accelerometers
Aidan R W Friederich1,2, Musa L Audu1,2, Ronald J Triolo1,2
1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Sensors (Basel, Switzerland)
|October 14, 2022
Summary
This study presents a novel method for calibrating randomly oriented accelerometers to measure trunk orientation in individuals with spinal cord injuries (SCI). This technique is crucial for developing effective feedback control systems for functional neuromuscular stimulation.
Area of Science:
- Biomedical Engineering
- Neuroprosthetics
- Rehabilitation Technology
Background:
- Functional neuromuscular stimulation (FNS) can improve daily function in individuals with spinal cord injuries (SCI) by enhancing seated stability.
- A fully implanted networked neuroprosthesis (NNP) utilizes trunk-mounted accelerometers for real-time feedback control.
- Accurate sensor orientation is typically assumed, but NNP modules have unknown positions and orientations due to surgical constraints.
Purpose of the Study:
- To develop and validate a method for calibrating multiple, randomly oriented accelerometers.
- To fuse signals from these sensors into a reliable measure of trunk orientation.
- To enable feedback control systems for trunk stabilization in individuals with SCI using NNP technology.
Main Methods:
- Six accelerometers were attached to the trunks of six individuals with SCI in random orientations.
- A calibration method was developed to determine trunk orientation from these sensors without prior knowledge of their anatomical relationships.
- Validation was performed using an optical motion capture system and a handheld goniometer.
Main Results:
- Calibration using optical motion capture yielded Root Mean Square Errors (RMSE) below 5° and correlation coefficients above 0.97.
- Calibration using a handheld goniometer resulted in RMSE of 7° and correlation coefficients above 0.93.
- The method successfully obtained trunk orientation from a network of sensors with unknown relationships to body axes.
Conclusions:
- The developed calibration method accurately determines trunk orientation from randomly placed accelerometers.
- This technique is essential for designing effective feedback control systems for trunk stabilization in SCI patients using NNP.
- The findings support the integration of this calibration method into future NNP-based rehabilitation technologies.
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