Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm

El‐Gohary, Mahmoud; McNames, James

doi:10.1109/tbme.2015.2403368

Cited by 129 publications

(93 citation statements)

References 32 publications

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“…Our goal is to determine the feasibility of using the fused technologies to accurately estimating human movement. If successful, this may enable us to determine, for example, the feasibility of using this technology to more accurately estimate human joint angles [28, 29]. In this study, we assess the feasibility and evaluate the performance of the fused system and the algorithms through the use of an industrial robot arm with six degrees of freedom.…”

Section: Introductionmentioning

confidence: 99%

Inertial and time-of-arrival ranging sensor fusion

Vasilyev¹,

Pearson²,

El‐Gohary³

et al. 2017

Gait & Posture

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Wearable devices with embedded kinematic sensors including triaxial accelerometers, gyroscopes, and magnetometers are becoming widely used in applications for tracking human movement in domains that include sports, motion gaming, medicine, and wellness. The kinematic sensors can be used to estimate orientation, but can only estimate changes in position over short periods of time. We developed a prototype sensor that includes ultra wideband ranging sensors and kinematic sensors to determine the feasibility of fusing the two sensor technologies to estimate both orientation and position. We used a state space model and applied the unscented Kalman filter to fuse the sensor information. Our results demonstrate that it is possible to estimate orientation and position with less error than is possible with either sensor technology alone. In our experiment we obtained a position root mean square error of 5.2 cm and orientation error of 4.8° over a 15 minute recording.

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Section: Introductionmentioning

confidence: 99%

Inertial and time-of-arrival ranging sensor fusion

Vasilyev¹,

Pearson²,

El‐Gohary³

et al. 2017

Gait & Posture

Self Cite

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“…Here, we consider only the orientation estimation in a free segments model, without a kinematic chain model [19,39,40]. In this section, we present constructions of these three algorithms with the use of the introduced notations.…”

Section: Sensor’s Orientation Estimationmentioning

confidence: 99%

Inertial Motion Capture Costume Design Study

Szczęsna

Skurowski

Lach

et al. 2017

Sensors

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The paper describes a scalable, wearable multi-sensor system for motion capture based on inertial measurement units (IMUs). Such a unit is composed of accelerometer, gyroscope and magnetometer. The final quality of an obtained motion arises from all the individual parts of the described system. The proposed system is a sequence of the following stages: sensor data acquisition, sensor orientation estimation, system calibration, pose estimation and data visualisation. The construction of the system’s architecture with the dataflow programming paradigm makes it easy to add, remove and replace the data processing steps. The modular architecture of the system allows an effortless introduction of a new sensor orientation estimation algorithms. The original contribution of the paper is the design study of the individual components used in the motion capture system. The two key steps of the system design are explored in this paper: the evaluation of sensors and algorithms for the orientation estimation. The three chosen algorithms have been implemented and investigated as part of the experiment. Due to the fact that the selection of the sensor has a significant impact on the final result, the sensor evaluation process is also explained and tested. The experimental results confirmed that the choice of sensor and orientation estimation algorithm affect the quality of the final results.

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“…1 illustrates the overall structure. The lower limb exoskeleton degree of freedom and range of motion are shown in Table 1 [8].…”

Section: The Distribution Of Dofmentioning

confidence: 99%

Biomechanical design of escalading lower limb exoskeleton with novel linkage joints

Zhang¹,

Liu²,

Ma³

et al. 2017

THC

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Abstract. In this paper, an obstacle-surmounting-enabled lower limb exoskeleton with novel linkage joints that perfectly mimicked human motions was proposed. Currently, most lower exoskeletons that use linear actuators have a direct connection between the wearer and the controlled part. Compared to the existing joints, the novel linkage joint not only fitted better into compact chasis, but also provided greater torque when the joint was at a large bend angle. As a result, it extended the angle range of joint peak torque output. With any given power, torque was prioritized over rotational speed, because instead of rotational speed, sufficiency of torque is the premise for most joint actions. With insufficient torque, the exoskeleton will be a burden instead of enhancement to its wearer. With optimized distribution of torque among the joints, the novel linkage method may contribute to easier exoskeleton movements.

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Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm

Cited by 129 publications

References 32 publications

Inertial and time-of-arrival ranging sensor fusion

Inertial and time-of-arrival ranging sensor fusion

Inertial Motion Capture Costume Design Study

Biomechanical design of escalading lower limb exoskeleton with novel linkage joints

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