# Bilateral Elimination Rule-Based Finite Class Bayesian Inference System for Circular and Linear Walking Prediction

## TL;DR

This study introduces a new system that accurately predicts transitions between circular and linear walking using motion data from inertial sensors.

## Contribution

The novel BER-FC-BesIS system uses bilateral motion data and Bayesian inference to predict walking activity transitions with high accuracy.

## Key findings

- The system predicts left and right lower limb walking activities with mean times of 119.32 ms and 113.75 ms.
- Prediction accuracy of BER-FC-BesIS reaches 93.98%.
- The system's mean time difference between predicted and real walking transitions is under 15 ms for both limbs.

## Abstract

Objective: The prediction of upcoming circular walking during linear walking is important for the usability and safety of the interaction between a lower limb assistive device and the wearer. This study aims to build a bilateral elimination rule-based finite class Bayesian inference system (BER-FC-BesIS) with the ability to predict the transition between circular walking and linear walking using inertial measurement units. Methods: Bilateral motion data of the human body were used to improve the recognition and prediction accuracy of BER-FC-BesIS. Results: The mean predicted time of BER-FC-BesIS in predicting the left and right lower limbs’ upcoming steady walking activities is 119.32 ± 9.71 ms and 113.75 ± 11.83 ms, respectively. The mean time differences between the predicted time and the real time of BER-FC-BesIS in the left and right lower limbs’ prediction are 14.22 ± 3.74 ms and 13.59 ± 4.92 ms, respectively. The prediction accuracy of BER-FC-BesIS is 93.98%. Conclusion: Upcoming steady walking activities (e.g., linear walking and circular walking) can be accurately predicted by BER-FC-BesIS innovatively. Significance: This study could be helpful and instructional to improve the lower limb assistive devices’ capabilities of walking activity prediction with emphasis on non-linear walking activities in daily living.