This document presents a wearable body sensor network composed of two inertial modules placed on the upper limbs to assess shoulder range of motion in real-time. Each module contains an MCU, accelerometer, gyroscope and magnetometer. The sensors collect acceleration, velocity and magnetic data which is processed through a quaternion filter to minimize errors from sensor noise/drift and estimate shoulder movement without external devices.

1. A WEARABLE INERTIAL-SENSING-BASED BODY SENSOR
NETWORK FOR SHOULDER RANGE OF MOTION
ASSESSMENT
ABSTRACT:
This paper presents a wearable inertial-sensing-based body sensor network (BSN)
composed of two inertial modules that are placed on human upper limb for real-time human
motion capture applications. Each inertial module consists of an ARM-based 32-bit
microcontroller (MCU), a triaxial accelerometer, a triaxial gyroscope, and a triaxial
magnetometer. To estimate shoulder range of motion (ROM), the accelerations, angular
velocities, and magnetic signals are collected and processed by a quaternion-based
complementary nonlinear filter for minimizing the cumulative errors caused by the intrinsic
noise/drift of the inertial sensors. The proposed BSN is a cost-effective tool and can be used
anywhere without any external reference device for shoulder ROM. The sensor fusion
algorithm can reduce orientation error effectively and thus can assess shoulder joint motions
accurately.