Feasibility of employing AHRS algorithms in the real-time estimation of sensor orientation using low-cost and low sampling rate wearable sensors in IoT application

In this paper, the feasibility of using wearable wireless low-cost motion trackers equipped with magnetic/inertial sensors in daily human activities was investigated. Five previously introduced attitude estimation algorithms were chosen and implemented in Windows IoT environment. A Texas Instrument CC2650STK wireless sensor was utilized to capture the raw magnetic/inertial data. The raw data was streamed to a DragonBoard 410c single board computer in real-time via Bluetooth low energy with the low sampling frequency. The sensor attitude was estimated using the attitude estimation algorithms continuously. A Shimmer 3 AHRS system was used as a golden standard, and the orientation of the Shimmer 3 was acquired using the Shimmer Consensys PRO 1.5 software. The experimental test showed poor agreement between the estimated and reference orientations and that the calculated orientation was dependent on an initial calibration. Based on the preliminary results and the current limitations in the wearable motion trackers, we may conclude that a precise estimation of a rigid body angle may not be achieved using wearable motion trackers in daily activities and other clinical applications.

I. Introduction

Attitude determination can be achieved using an attitude and heading reference system (AHRS). The AHRS systems are providing roll, pitch and yaw information of a rigid body by employing three-dimension sensors. The corresponding orientation of the system can easily be visualized based on the earth gravity and magnetic field of the environment.