Inertial Sensor-based System Research Articles

Height Compensation Using Ground Inclination Estimation in Inertial Sensor-Based Pedestrian Navigation

In an inertial sensor-based pedestrian navigation system, the position is estimated by double integrating external acceleration. A new algorithm is proposed to reduce z axis position (height) error. When a foot is on the ground, a foot angle is estimated using accelerometer output. Using a foot angle, the inclination angle of a road is estimated. Using this road inclination angle, height difference of one walking step is estimated and this estimation is used to reduce height error. Through walking experiments on roads with different inclination angles, the usefulness of the proposed algorithm is verified.

Inertial Sensor-Based Indoor Pedestrian Localization with Minimum 802.15.4a Configuration

Available techniques for indoor object locating systems, such as inertial sensor-based system or radio fingerprinting, hardly satisfy both cost-effectiveness and accuracy. In particular, inertial sensor-based locating systems are often supplemented with radio signals to improve localization accuracy. A radio-assisted localization system is still costly due to the infrastructure requirements and management overheads. In this paper, we propose a low-cost and yet accurate indoor pedestrian localization scheme with a small number of radio beacons whose location information is unknown. Our scheme applies the Simultaneous Location and Mapping (SLAM) technique used in robotics to mobile device, which is equipped with both inertial sensors and the IEEE802.15.4a Chirp Spread Spectrum (CSS) radio, to obtain accurate locations of pedestrians in indoor environment. The proposed system is validated with real implementations. The experiment results show approximately 1.5 m mean error observed during 276 m of pedestrian moving in a 380 m2 indoor environment with five position-unknown beacons.

Measurement of Lower Limb Joint Kinematics using Inertial Sensors During Stair Ascent and Descent in Healthy Older Adults and Stroke Survivors

This study validated the feasibility of inertial sensors in estimating lower limb joint kinematics during stair ambulation in healthy older adults and stroke survivors. Three dimensional motion data were collected using an inertial sensor-based system from 9 persons with stroke and 9 healthy older adults as they ascended and descended a staircase at a self-selected pace. The measured joint angles were compared with a laboratory-based motion capture system by computing differences in range of motion (RoM), grand mean error, standard deviation, and coefficients of multiple correlations. For stroke survivors, differences in RoM measurements between these two systems were determined to be 3.3 ± 8.1°, while the highest correlations were found in the estimation of sagittal plane joint angles after offset correction. Results suggest that the inertial sensor system is suitable for estimating major joint angles in healthy older adults as well as the RoM for stroke survivors. New calibration procedures are necessary for applying the technology to a stroke population.