Versione 5.0 (1,34 KB) da Marco Caruso
This repository contains the magneto-inertial signals from six MIMU and ground truth orientation + positions from 8 reflective markers
53 download
Aggiornato 28 apr 2021

This dataset provides the magneto-inertial signals from six MIMU (2 Xsens, 2 APDM, 2 Shimmer) and orientation from 8 reflective markers (VICON) at 3 different speeds (slow, medium, fast). Marker trajectories are provided. Proprietary orientations from MIMU vendors are also included. All data are synchronized at 100 Hz.

Xsens - MTx = XS1, XS2
APDM - Opal = AP1, AP2
Shimmer - Shimmer3 = SH1, SH2

For each MIMU dataset (XS1, XS2, AP1, AP2, SH1, SH2):
columns 1 = time vector (or packet counter vector)
columns 2:4 = accelerometer data (x,y,z) (m/s^2)
columns 5:7 = gyroscope data (x,y,z) (rad/s)
columns 8:10 = magnetometer data (x,y,z) (a.u.)
columns 11:14 = proprietary orientation
Mrks matrix contains the trajectories of the eight markers (mm). Please, refer to the figure for the labelling:
Mrks(:,1) # frame
Mrks(:,2:4) Mrk1
Mrks(:,5:7) Mrk4
Mrks(:,8:10) Mrk3
Mrks(:,11:13) Mrk5
Mrks(:,14:16) Mrk2
Mrks(:,17:19) M0
Mrks(:,20:22) Mx
Mrks(:,23:25) My

Rotations sequence are in the timeframe contained in indz (first rotation), indx (second rotation), indy (third rotation), and indarb (3D rotation).
Qs (q0, qx, qy, qz) is the orientation obtained by applying the SVD technique to eight marker position data [A. Cappozzo, A. Cappello, U. D. Croce, and F. Pensalfini, “Surface-marker cluster design criteria for 3-d bone movement reconstruction,” IEEE Trans. Biomed. Eng., vol. 44, no. 12, pp. 1165–1174, 1997]
wVicon is the angular velocity obtained by Qs [Chardonnens, J.; Favre, J.; Aminian, K. An effortless procedure to align the local frame of an inertial measurement unit to the local frame of another motion capture system. J. Biomech. 2012,45, 2297–300.]

When using this dataset, please cite: M. Caruso, A. M. Sabatini, M. Knaflitz, M. Gazzoni, U. D. Croce and A. Cereatti, "Orientation Estimation Through Magneto-Inertial Sensor Fusion: A Heuristic Approach for Suboptimal Parameters Tuning," in IEEE Sensors Journal, vol. 21, no. 3, pp. 3408-3419, 1 Feb.1, 2021, doi: 10.1109/JSEN.2020.3024806.


Marco Caruso - Politecnico di Torino

This dataset can be also found at: https://ieee-dataport.org/documents/mimuopticalsassaridataset

Cita come

Marco Caruso (2024). mimu_optical_dataset_caruso_sassari (https://github.com/marcocaruso/mimu_optical_dataset_caruso_sassari/releases/tag/v5.0), GitHub. Recuperato .

Compatibilità della release di MATLAB
Creato con R2021a
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux
Scopri di più su Optics in Help Center e MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Versione Pubblicato Note della release

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.