3D-calibration of the IMU

Avrutov, V. V.; Aksonenko, P. M.; Hénaff, Patrick; Ciarletta, Laurent

doi:10.1109/elnano.2017.7939782

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…The orientation of the PP of the index finger measured by the opto-electronic system and by the IMU is shown in Figure 7, where roll, pitch and yaw angles are the extrinsic rotation of the x-axis, y-axis and z-axis of the index PP frame relative to the index PP frame defined in the neutral posture. As expected, the main rotation is around the x-axis (of 30 deg maximum), whereas the yaw angle is limited; indeed, the metacarpophalangeal joint has only two degrees of freedom: flexion and extension and ulnar/radial deviation [31]. The summary of the results reported in Table 1 shows the reliability of the IMU measurements, which are comparable to the ones obtained by the opto-electronic system as highlighted by the RMSE value.…”

Section: Resultssupporting

confidence: 72%

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Validation of a modular and wearable system for tracking fingers movements

et al. 2020

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<p class="Abstract">Supervising manual operations performed by workers in industrial environments is crucial in a smart factory. Indeed, the production of products with superior quality, at higher throughput rates and reduced costs with the support of the Industry 4.0 enabling technologies is based on the strict control of all the resources inside the factory, including workers. This paper shows a protocol for validating a new wearable system for tracking finger movements. The wearable system consists of two measuring modules worn on the thumb and on the index measuring flexion and extension of the proximal interphalangeal (PIP) joint by a stretch sensor and rotation of the proximal phalanx (PP) by an inertial measurement unit. An optical system is used to validate the system by capturing specific finger movements. Four movements that simulate typical tasks and gestures, such as grasp and pinch, were performed to validate the proposed system. The maximum root-mean-square error is 3.7 deg for the roll angle of PP. The resistance changes of the stretch sensors with respect to flexion and extension of PIP joint is 0.47 Ohm/deg. The results are useful for the data interpretation when the system is adopted for monitoring finger movements and gestures.</p>

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Section: Resultssupporting

confidence: 72%

“…A male subject wore the measuring system on the thumb and the index finger of his right hand. The IMUs were calibrated according to the standard calibration procedures (an example is reported in [31]). The relationship between the strain and the resistance change of the stretch sensor is reported in [29] and [32].…”

Section: Methodsmentioning

confidence: 99%

Validation of a modular and wearable system for tracking fingers movements

et al. 2020

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“…However, due to factors such as mechanical processing technology and installation structure [3], MEMS-IMUs are subject to measurement errors, referred to as device errors. The MEMS-IMU calculates the position and attitude information of the carrier by integrating the three-axis acceleration and the three-axis gyroscope.…”

Section: Introductionmentioning

confidence: 99%

Calibration method of strapdown inertial measurement unit based on two-axis turntable

Liu,

Gao,

Zhan

et al. 2024

J. Phys.: Conf. Ser.

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This paper analyzes the causes and effects of error in the Strapdown Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU), utilizing a sensor calibration method based on a two-axis turntable. By considering deterministic errors such as sensor bias, scale factor, and non-orthogonality of the sensitive axis, an error model was established to assess their impact on measurement accuracy. An expression was provided to represent the relationship between sensor data collection and external input stimuli, storing the error parameters of the accelerometer and the gyroscope separately in parameter matrices. The error parameter matrix between input and output quantities was fitted using the least squares method, and error compensation was completed in conjunction with the error model. By comparing the original data with the error-compensated data, the calibration results were obtained. This improved the consistency of the measurements from the sensitive axes to the stimulus source, reduced the zero bias error of each sensitive axis, and enhanced the positioning accuracy of the Strapdown MEMS-IMU.

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