Trunk Posture from Randomly Oriented Accelerometers

Abstract

Feedback control of functional neuromuscular stimulation has the potential to improve daily function for individuals with spinal cord injuries (SCIs) by enhancing seated stability. Our fully implanted networked neuroprosthesis (NNP) can provide real-time feedback signals for controlling the trunk through accelerometers embedded in modules distributed throughout the trunk. Typically, inertial sensors are aligned with the relevant body segment. However, NNP implanted modules are placed according to surgical constraints and their precise locations and orientations are generally unknown. We have developed a method for calibrating multiple randomly oriented accelerometers and fusing their signals into a measure of trunk orientation. Six accelerometers were externally attached in random orientations to the trunks of six individuals with SCI. Calibration with an optical motion capture system resulted in RMSE below 5° and correlation coefficients above 0.97. Calibration with a handheld goniometer resulted in RMSE of 7° and correlation coefficients above 0.93. Our method can obtain trunk orientation from a network of sensors without a priori knowledge of their relationships to the body anatomical axes. The results of this study will be invaluable in the design of feedback control systems for stabilizing the trunk of individuals with SCI in combination with the NNP implanted technology.

Keywords: accelerometer; neuroprosthesis; sensor fusion; spinal cord injury.

Figure 1

Diagram of a distributed sensor system. The coordinate frames of these sensors are unknown relative to the body’s anatomical coordinate frame.

Figure 2

Locations of the 3-axis accelerometers and reflective markers on the subject. The body’s anatomical coordinate frame is shown in the right image. Pitch, roll, and yaw refer to trunk flexion and extension, lateral bending, and axial rotation about the x, y, and z anatomical axes, respectively.

Figure 3

Experimental procedure flowchart for both the motion caption and clinical calibration methods.

Figure 4

Overview of the sensor rotation and fusion process. Signals from each accelerometer are first rotated, then converted to pitch and roll angles. Finally, the pitch and roll angles from every sensor are fused into a single measure of trunk position.

Figure 5

Pitch and roll angles from all subjects S1 (a), S2 (b), S3 (c), S4 (d), S5 (e), and S6 (f) determined through sensor fusion optimized with motion capture.

Figure 6

Sensor weights for determining the pitch (a) and roll (b) angles from the weighted average equation. Values are separated by subject number and sensor number. Locations of the sensors are as followed: 1. right chest; 2. left chest; 3. right front abdomen; 4. left front abdomen; 5. right back abdomen; and 6. left back abdomen. These weights resulted from the motion capture calibration process.

Figure 7

Pitch and roll angles from all subjects S1 (a), S2 (b), S3 (c), S4 (d), S5 (e), and S6 (f) determined through sensor fusion optimized with motion capture.