Abstract
A lot of attention has been paid to wearable inertial sensors regarded as an alternative solution for outdoor human motion tracking. Relevant joint angles can only be calculated from anatomical orientations, but they are negatively impacted by soft tissue artifact (STA) defined as skin motion with respect to the underlying bone; the accuracy of measured joint angle during movement is affected by the ongoing misalignment of the sensor. In this work, a new sensor-to-segment calibration using inertial measurement units is proposed. Inspired by the multiple calibration for a cluster of skin markers, it consists in performing first multiple static postures of the upper limb in all anatomical planes. The movements that affect sensor alignment are identified then alignment differences between sensors and segment frames are calculated for each posture and linearly interpolated. Experimental measurements were carried out on a mechanical model and on a subject who performed different movements of right elbow and shoulder. Multiple calibration showed significant improvement in joint angle measurement on the mechanical model as well as on human joint angle comparing to those obtained from attached sensors after technical calibration. During shoulder internal-external rotation, the maximal error value decreased more than 50% after correction.

Elbow flexion-extension joint angle values obtained from IMUs are well-corrected after applying multiple calibration procedure. Though shoulder internal-external rotation joint angle is more affected by soft tissue artifact, multiple calibration procedure improves the angle values obtained from IMUs.











Similar content being viewed by others
Abbreviations
- \( {p}_i^0 \) :
-
Segment i orientation at neutral posture 0
- \( {q}_i^0 \) :
-
Sensor i frame orientation at neutral posture 0
- \( {\overset{\sim }{q}}_1^0 \) :
-
Rotation of IMU1 at posture 0 to align with gravity
- \( {p}_i^j \) :
-
Segment i orientation at posture j
- \( {q}_i^j \) :
-
Sensor i orientation at posture j
- \( \tilde{p}_{i}^j \) :
-
90° rotation about a given axis of the segment i at posture j
- \( \tilde{q}_{i}^j \) :
-
Alignment difference between \( {q}_i^j \) and \( {p}_i^j \)
- \( {\overline {\overset{\sim }{q}}}_i^{\mathbf{u},\alpha } \) :
-
Mean value of all alignment differences \( \tilde{q}_{i}^j\kern0.24em \) calculated for each segment i at all postures j resulting either from the rotation of the joint angle α = 0° or 90° about the axis u and presenting the same segment frame orientation
- \( {\overline {\overset{\sim }{q}}}_i^{\mathbf{u},}\left(\theta \right) \) :
-
Alignment correction during movement and obtained by linear interpolation
- \( {\overline {\overset{\sim }{q}}}_i^{\mathbf{u},},\mathbf{v}\left({\theta}_1,{\theta}_2\right) \) :
-
Alignment correction during movement and obtained by bilinear interpolation
- p i :
-
Corrected segment frame orientation
References
Rowe PJ, Myles CM, Hillmann SJ, Hazlewood ME (2001) Validation of flexible electrogoniometry as a measure of joint kinematics. Physiotherapy 87:479–488. https://doi.org/10.1016/S0031-9406(05)60695-5
Alvarez D, Alvarez JC, Gonzalez RC, Lopez AM (2015) Upper limb joint angle measurement in occupational health. Comput Meth Biomech Biomed Eng 19:159–170. https://doi.org/10.1080/10255842.2014.997718
Robert-Lachaine X, Mecheri H, Larue C, Plamondon A (2017) Validation of inertial measurement units with an optoelectronic system for whole-body motion analysis. Med Biol Eng Comput 55:609–619. https://doi.org/10.1007/s11517-016-1537-2
Bouvier B, Duprey S, Claudon L, Dumas R, Savescu A (2015) Upper limb kinematics using inertial and magnetic sensors: comparison of sensor-to-segment calibrations. Sensors 15:18813–18833. https://doi.org/10.3390/s150818813
Bolink SAAN, Naisas H, Senden R, Essers H, Heyligers IC, Meijer K, Grimm B (2016) Validity of an inertial measurement unit to assess pelvic orientation angles during gait, sit-stand transfers, and step-up transfers: comparison with an optoelectronic motion capture system. Med Eng Phys 38:225–231. https://doi.org/10.1016/j.medengphy.2015.11.009
Cappozzo A, Della Croce U, Leardini A, Chiari L (2005) Human movement analysis using stereophotogrammetry part 1: theorical background. Gait Posture 21:186–196. https://doi.org/10.1016/j.gaitpost.2004.01.010
Cappello A, Cappozzo A, La Palombara PF, Lucchetti L, Leardini A (1997) Multiple anatomical landmark calibration for optimal bone pose estimation. Hum Movement Sci 16:259–274. https://doi.org/10.1016/S0167-9457(96)00055-3
Qureshi U, Golnaraghi F (2017) An algorithm for the in field calibration of a MEMS IMU. IEEE Sensors J 17:7479–7486. https://doi.org/10.1109/JSEN.2017.2751572
Kopacik A, Kajanek P, Liptak I (2016) Systematic error elimination using additive measurements and combination of two low cost ISMs. IEEE Sensors J 16:6239–6248. https://doi.org/10.1109/JSEN.2016.2581200
Cutti AG, Giovanardi A, Rocchi L, Davalli A, Sacchetti R (2008) Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors. Med Biol Eng Comput 46:169–178. https://doi.org/10.1007/s11517-007-0296-5
Vargas–Valencia LS, Elias A, Rocon E, Bastos–Filho T, Frizera A (2016) An IMU–to–body alignment method applied to human gait analysis. Sensors 12:2090–2107. https://doi.org/10.3390/s16122090
de Vries WHK, Veeger HEJ, Cutti AG, Baten C, Van der Helm FCT (2010) Functionally interpretable local coordinate systems for the upper extremity using inertial & magnetic measurement systems. J Biomech 43:1983–1988. https://doi.org/10.1016/j.jbiomech.2010.03.007
Robert-Lachaine X, Mecheri H, Larue C, Plamondon A (2017) Accuracy and repeatability of single-pose calibration of inertial measurement units for whole-body motion analysis. Gait Posture 54:80–86. https://doi.org/10.1016/j.gaitpost.2017.02.029
Lach E (2016) Evaluation of automatic calibration method for motion tracking using magnetic and inertial sensors. In: Piętka E, Badura P, Kawa J, Wieclawek W (eds) Information technologies in medicine. ITiB 2016. Advances in Intelligent Systems and Computing, vol 472. Springer, Cham. https://doi.org/10.1007/978-3-319-39904-1_30
Camomilla V, Bonci T, Dumas R, Cheze L, Cappozzo A (2015) A model of the soft tissue artefact rigid component. J Biomech 48:1752–1759. https://doi.org/10.1016/j.jbiomech.2015.05.007
Blache Y, Dumas R, Lundberg A, Begon M (2017) Main component of soft tissue artifact of the upper-limbs with respect to different functional, daily life and sports movements. J Biomech 62:39–46. https://doi.org/10.1016/j.jbiomech.2016.10.019
Cutti AG, Cappello A, Davalli A (2006) In vivo validation of a new technique that compensates for soft tissue artefact in the upper-arm: preliminary results. Clin Biomech 21:S13–S19. https://doi.org/10.1016/j.clinbiomech.2005.09.018
Cutti AG, Paolini G, Troncossi M, Cappello A, Davalli A (2005) Soft tissue artefact assessment in humeral axial rotation. Gait Posture 21:341–349. https://doi.org/10.1016/j.gaitpost.2004.04.001
Cappello A, Stagni R, Fantozzi S, Leardini A (2005) Soft tissue artifact compensation in knee kinematics by double anatomical landmark calibration: performance of a novel method during selected motor tasks. IEEE Trans on Biomed Eng 52:992–998. https://doi.org/10.1109/TBME.2005.846728
Meng D, Shoepe T, Vejarano G (2016) Accuracy improvement on the measurement of human-joint angles. IEEE J Biomed Health Informatics 20:498–507. https://doi.org/10.1109/JBHI.2015.2394467
Camomilla V, Dumas R, Cappozzo A (2017) Human movement analysis: the soft tissue artefact issue. J Biomech 62:1–4. https://doi.org/10.1016/j.jbiomech.2017.09.001
Brochard S, Lempereur M, Rémy-Néris O (2011) Double calibration: an accurate, reliable and easy-to-use method for 3D scapular motion analysis. J Biomech 44:751–754. https://doi.org/10.1016/j.jbiomech.2010.11.017
Ricci L, Formica D, Sparaci L, Lasorsa FR, Taffoni F, Tamilia E, Guglielmelli E (2014) A new calibration methodology for thorax and upper limbs motion capture in children using magneto and inertial sensors. Sensors 14:1057–1072. https://doi.org/10.3390/s140101057
Prayudi I, Kim D (2012) Design and implementation of IMU-based human arm motion capture system, in Proc. IEEE International Conference on Mechatronics and Automation. https://doi.org/10.1109/ICMA.2012.6283221
Miezal M, Taetz B, Bleser G (2016) On inertial body tracking in the presence of model calibration errors. Sensors. 16. https://doi.org/10.3390/s16071132
Taetz B, Bleser G, Miezal M (2016) Towards self-calibrating inertial body motion capture, in Proc. IEEE 19th International Conference on Information Fusion (FUSION):1751–1759
Muller P, Begin MA, Schauer T, Seel T (2016) Alignment-free, self-calibrating elbow angles measurement using inertial sensors. IEEE J Biomed Health Informatics 21:312–319. https://doi.org/10.1109/JBHI.2016.2639537
Palermo E, Rossi S, Marini F, Patane F, Cappa P (2014) Experimental evaluation of accuracy and repeatability of a novel body-to-sensor calibration procedure for inertial sensor-based gait analysis. Measurement 52:145–155. https://doi.org/10.1016/j.measurement.2014.03.004
Luinge HJ, Veltink PH, Baten CTM (2007) Ambulatory measurement of arm orientation. J Biomech 40:78–85. https://doi.org/10.1016/j.jbiomech.2005.11.011
Ligorio G, Zanotto D, Sabatini AM, Agrawal SK (2017) A novel functional calibration method for real-time elbow joint angles estimation with magnetic-inertial sensors. J Biomech 54:106–110. https://doi.org/10.1016/j.jbiomech.2017.01.024
Wu G, Van der Helm FCT, Veeger HEJ et al (2005) ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—part II: shoulder, elbow, wrist and hand. J Biomech 38:981–992. https://doi.org/10.1016/j.jbiomech.2004.05.042
Lin Z, Xiong Y, Dai H, Xia X (2017) An experimental performance evaluation of the orientation accuracy of four nine-axis MEMS motion sensors. in Proc. IEEE 5th International Conference on Enterprise Systems ICES:185–189. https://doi.org/10.1109/ES.2017.37
Bosch Sensortech (2016) Datasheet BNO055 intelligent 9-axis absolute orientation sensor. Available via https://ae-bst.resource.bosch.com/media/_tech/media/datasheets/BST-BNO055-DS000.pdf. Accessed 15 Jun 2019
Cooper RA, Boninger ML, Shimada SD, Lawrence BM (1999) Glenohumeral joint kinematics and kinetics for three coordinate system representations during wheelchair propulsion. American J Phys Med Rehabil 78:435–446
Cao L, Masuda T, Morita S (2007) Compensation for the effect of soft tissue artefact on humeral axial rotation angle. J Med Dent Sci 54:1–7. https://doi.org/10.11480/jmds.540101
Cereatti A, Bonci T, Akbarshahi M, Aminian K, Barre A et al (2017) Standardization proposal of soft tissue artefact description for data sharing in human motion measurements. J Biomech 62:5–13. https://doi.org/10.1016/j.jbiomech.2017.02.004
Donati M, Camomilla V, Vannozzi G, Cappozzo A (2007) Enhanced anatomical calibration in human movement analysis. Gait Posture 26:179–185. https://doi.org/10.1016/j.gaitpost.2007.04.009
Picerno P, Cereatti A, Cappozzo A (2008) Joint kinematics estimate using wearable inertial and magnetic sensing modules. Gait Posture 28:588–595. https://doi.org/10.1016/j.gaitpost.2008.04.003
Cappozzo A, Catani F, Leardini A, Benedetti MG, Croce UD (1996) Position and orientation in space of bones during movement: experimental artefacts. Clin Biomech 11:90–100. https://doi.org/10.1016/0268-0033(95)00046-1
Barre A, Aissaoui R, Aminian K, Dumas R (2017) Assessment of the lower limb soft tissue artefact at marker-cluster level with a high-density marker set during walking. J Biomech 62:21–26. https://doi.org/10.1016/j.jbiomech.2017.04.036
Andersen MS, Damsgaard M, Rasmussen J, Ramsey DK, Benoit DL (2012) A linear soft tissue artefact model for human movement analysis: proof of concept using in vivo data. Gait Posture 35:606–611. https://doi.org/10.1016/j.gaitpost.2011.11.032
Bonci T, Camomilla V, Dumas R, Cheze L, Cappozzo A (2014) A soft tissue artefact model driven by proximal and distal joint kinematics. J Biomech 47:2354–2361. https://doi.org/10.1016/j.jbiomech.2014.04.029
Begon M, Andersen MS, Dumas R (2018) Multibody kinematics optimization for the estimation of upper and lower limb human joint kinematics: a systematized methodologycal review. J Biomech Eng 140:0308011–0308011. https://doi.org/10.1115/1.4038741
Camomilla V, Bonci T, Cappozzo A (2017) Soft tissue displacement over pelvic anatomical landmarks during 3-D hip movements. J Biomech 62:14–20. https://doi.org/10.1016/j.jbiomech.2017.01.013
Bonnet V, Richard V, Camomilla V, Venture G, Cappozzo A, Dumas R (2017) Joint kinematics estimation using a multi-body kinematics optimisation and an extended Kalman filter, and embedding a soft tissue artefact model. J Biomech 62:148–155. https://doi.org/10.1016/j.jbiomech.2017.04.033
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOC 74.5 kb)
Rights and permissions
About this article
Cite this article
Zabat, M., Ababou, A., Ababou, N. et al. IMU-based sensor-to-segment multiple calibration for upper limb joint angle measurement—a proof of concept. Med Biol Eng Comput 57, 2449–2460 (2019). https://doi.org/10.1007/s11517-019-02033-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-019-02033-7