An Investigation into the Accuracy of Calculating upper Body Joint Angles Using MARG Sensors

We investigate magnetic, angular rate, and gravity (MARG) sensor modules for deriving shoulder, elbow and lumbar joint angles of the human body. We use three tri-axial MARG sensors, placed proximal to the wrist and elbow and centrally on the chest, and employ a quaternion-based Unscented Kalman Filter technique to estimate orientations from the sensor data, from which joint angles are calculated based on a simple model of the arm. Tests reveal that the method has the potential to accurately derive specific angles. When compared with a camera-based system, a root mean square difference error between 5° - 15° was observed

Wearable sensors for gait analysis

Systems based on inertial sensors are increasingly used in motion analysis due to their low cost, portability and wearability. However, since accuracy is crucial in clinical gait analysis, it is important to assess it in new systems. The aim of this study is to compare the performances of a magnetic and inertial sensors system (MIMUs) to a gold standard, the electromechanical system STEP32. Results shows that spatio-temporal parameters are accurately estimated by the MIMUs system. Joint kinematics does not reach the accuracy of the STEP32 system. In fact, although MIMUs measurements on the knee and hip joints are clinically acceptable, they are not yet reliable for the ankle joint

Wearable sensors for gait analysis: Comparison between a MIMUs system and a gold standard electromechanical system

Systems based on inertial sensors are increasingly used in motion analysis due to their low cost, portability and wearability. However, since accuracy is crucial in clinical gait analysis, it is important to assess it in new systems. The aim of this study is to compare the performances of a magnetic and inertial sensors system (MIMUs) to a gold standard, the electromechanical system STEP32. Results shows that spatio-temporal parameters are accurately estimated by the MIMUs system. Joint kinematics does not reach the accuracy of the STEP32 system. In fact, although MIMUs measurements on the knee and hip joints are clinically acceptable, they are not yet reliable for the ankle joint

Tracking of Human Joints Using Twist and Exponential Map

Motion tracking system in the home-based environment exhibits attractive advantages for stroke patients. Current methods suffer from incapability of accurately tracking movements with high degree of freedoms. Besides hardly meeting the predefined position during inertial sensor mounting also affects system\u27s performance. To tackle these challenges, a motion tracking system using twist and exponential map technology is developed in this paper. Firstly, a kinematic model for trunk and upper extremity is designed. Based on this model, twist and exponential map method which updates frames in their initial coordinates instead of transforming coordinates from one frame to another presents high efficiency and convenience in estimating joints\u27 position and orientation. In the experiment, multiple movements are tracked by both of inertial sensor system and optical tracking system. Their comparison verifies this system\u27s high accuracy

Evaluation of the Performances of Two Wearable Systems for Gait Analysis: A Pilot Study

Wearable sensor systems to perform human motion analysis are receiving increasing attention in different application fields. Among wearable sensors, inertial sensors have promising features. However, before they can be employed routinely in clinical applications, it is important to evaluate their reliability. Gait analysis was performed on one male volunteer: data were simultaneously collected with HGait System, based on magnetic and inertial measurement sensor units system, and with STEP32, a commercial electromechanical system already used in clinics. Spatio temporal parameters and joint kinematics in the sagittal plane obtained with H-Gait and STEP32 are compared. The MIMUs system provides a reliable estimation of spatiotemporal parameters, and acceptable hip and knee kinematic curves, while ankle joint measurements must be improved to be clinically useful

Calibration of miniature inertial and magnetic sensor units for robust attitude estimation

Attitude estimation from miniature inertial and magnetic sensors has been used in a wide variety of applications, ranging from virtual reality, underwater vehicles, handheld navigation devices, to biomotion analysis. However, appropriate sensor calibrations for accurate sensor measurements are essential to the performance of attitude estimation algorithms. In this paper, we present a robust sensor calibration method for accurate attitude estimation from three-axis accelerometers, gyroscopes, and magnetometer measurements. The proposed calibration method only requires a simple pan-tilt unit. A unified sensor model for inertial and magnetic sensors is used to convert the sensor readings to physical quantities in metric units. Based on the sensor model, a cost function is constructed, and a two-step iterative algorithm is then proposed to calibrate the inertial sensors. Due to the difficulties of acquiring the ground-truth of the Earth magnetic field, a simplified pseudomagnetometer calibration method is also presented based on an ellipsoid fitting algorithm. The calibration method is then applied to our sensor nodes, and the good performance of the orientation estimation has illustrated the effectiveness of the proposed sensor calibration method

UNRESTRAINED MEASUREMENT OF ARM MOTION BASED ON A WEARABLE WIRELESS SENSOR NETWORK

Techniques that could precisely monitor human motion are useful in applications such as rehabilitation, virtual reality, sports science, and surveillance. Most of the existing systems require wiring that restrains the natural movement. To overcome this limitation, a wearable wireless sensor network using accelerometers has been developed in this paper to determine the arm motion in the sagittal plane. The system provides unrestrained movements and improves its usability. The lightweight and compact size of the developed sensor node makes its attachment to the limb easy. Experimental results have shown that the system has good accuracy and response rate when compared with a goniometer