Synchronisation of wearable inertial measurement units based on magnetometer data
-
Andreas Spilz
und
Michael Munz
Abstract
Objectives
Synchronisation of wireless inertial measurement units in human movement analysis is often achieved using event-based synchronisation techniques. However, these techniques lack precise event generation and accuracy. An inaccurate synchronisation could lead to large errors in motion estimation and reconstruction and therefore wrong analysis outputs.
Methods
We propose a novel event-based synchronisation technique based on a magnetic field, which allows sub-sample accuracy. A setup featuring Shimmer3 inertial measurement units is designed to test the approach.
Results
The proposed technique shows to be able to synchronise with a maximum offset of below 2.6 ms with sensors measuring at 100 Hz. The investigated parameters suggest a required synchronisation time of 8 s.
Conclusions
The results indicate a reliable event generation and detection for synchronisation of wireless inertial measurement units. Further research should investigate the temperature changes that the sensors are exposed to during human motion analysis and their influence on the internal time measurement of the sensors. In addition, the approach should be tested using inertial measurement units from different manufacturers to investigate an identified constant offset in the accuracy measurements.
Funding source: German Federal Ministry for Economic Affairs and Climate Actions (BMWK)
Award Identifier / Grant number: 16KN073527
-
Research funding: The results presented were obtained as part of a project funded by the German Federal Ministry for Economic Affairs and Climate Actions (BMWK).
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: Authors state no conflict of interest.
-
Informed consent: Not applicable.
-
Ethical approval: Not applicable.
References
1. Weygers, I, Kok, M, Konings, M, Hallez, H, Vroey, H, Claeys, K. Inertial sensor-based lower limb joint kinematics: a methodological systematic review. Sensors 2020;20:673. https://doi.org/10.3390/s20030673.Suche in Google Scholar PubMed PubMed Central
2. Vienne-Jumeau, A, Quijoux, F, Vidal, PP, Ricard, D. Wearable inertial sensors provide reliable biomarkers of disease severity in multiple sclerosis: a systematic review and meta-analysis. Ann Phys Rehabil Med 2020;63:138–47. https://doi.org/10.1016/j.rehab.2019.07.004.Suche in Google Scholar PubMed
3. Poitras, I, Dupuis, F, Bielmann, M, Campeau-Lecours, A, Mercier, C, Bouyer, LJ, et al.. Validity and reliability of wearable sensors for joint angle estimation: a systematic review. Sensors 2019;19:1555. https://doi.org/10.3390/s19071555.Suche in Google Scholar PubMed PubMed Central
4. O’Reilly, M, Caulfield, B, Ward, T, Johnston, W, Doherty, C. Wearable inertial sensor systems for lower limb exercise detection and evaluation: a systematic review. Sports Med 2018;48:1221–46. https://doi.org/10.1007/s40279-018-0878-4.Suche in Google Scholar PubMed
5. Ghislieri, M, Gastaldi, L, Pastorelli, S, Tadano, S, Agostini, V. Wearable inertial sensors to assess standing balance: a systematic review. Sensors 2019;19:4075. https://doi.org/10.3390/s19194075.Suche in Google Scholar PubMed PubMed Central
6. Tirado-Andrés, F, Araujo, A. Performance of clock sources and their influence on time synchronization in wireless sensor networks. Int J Distributed Sens Netw 2019;15. https://doi.org/10.1177/1550147719879372.Suche in Google Scholar
7. Elson, J, Girod, L, Estrin, D. Fine-grained network time synchronization using reference broadcasts. ACM SIGOPS – Oper Syst Rev 2002;36:147–63. https://doi.org/10.1145/844128.844143.Suche in Google Scholar
8. Ganeriwal, S, Kumar, R, Srivastava, MB. Timing-sync protocol for sensor networks. In: Proc first int conf embed networked sens syst (SenSys03). Los Angeles, USA: ACM; 2003.10.21236/ADA479052Suche in Google Scholar
9. Maróti, M, Kusy, B, Simon, G, Lédeczi, Á. The flooding time synchronization protocol. In: Proc 2nd int conf embed networked sens syst – sensys ‘04; 2004:39–49 pp.10.1145/1031495.1031501Suche in Google Scholar
10. Zhou, L, Fischer, E, Tunca, C, Brahms, CM, Ersoy, C, Granacher, U, et al.. How we found our IMU: guidelines to IMU selection and a comparison of seven IMUs for pervasive healthcare applications. Sensors 2020;20:4090. https://doi.org/10.3390/s20154090.Suche in Google Scholar PubMed PubMed Central
11. Sivrikaya, F, Yener, B. Time synchronization in sensor networks: a survey. IEEE Network 2004;18:45–50. https://doi.org/10.1109/mnet.2004.1316761.Suche in Google Scholar
12. Ringwald, M, Romer, K. Practical time synchronization for bluetooth scatternets. In: 2007 int conf broadband commun networks syst broadnets ‘07; 2007:337–45 pp.10.1109/BROADNETS.2007.4550453Suche in Google Scholar
13. Bannach, D, Amft, O, Lukowicz, P. Automatic event-based synchronization of multimodal data streams from wearable and ambient sensors. In: Smart sensing and context. 4th European conference, EuroSSC 2009. Guildford, UK, Sep 16–18, 2009.10.1007/978-3-642-04471-7_11Suche in Google Scholar
14. Gao, Y, Long, Y, Guan, Y, Basu, A, Baggaley, J, Ploetz, T. Towards reliable, automated general movement assessment for perinatal stroke screening in infants using wearable accelerometers. Proc ACM Interact Mob Wearable Ubiquitous Technol 2019;3:1–22. https://doi.org/10.1145/3314399.Suche in Google Scholar
15. Rietveld, T, Vegter, RJK, van der Slikke, RMA, Hoekstra, AE, van der Woude, LHV, Groot, S. Wheelchair mobility performance of elite wheelchair tennis players during four field tests: inter-trial reliability and construct validity. PLoS One 2019;14:e0217514. https://doi.org/10.1371/journal.pone.0217514.Suche in Google Scholar PubMed PubMed Central
16. Paraschiakos, S, Cachucho, R, Moed, M, van Heemst, D, Mooijaart, S, Slagboom, EP, et al.. Activity recognition using wearable sensors for tracking the elderly. User Model User Adapt 2020;30:567–605. https://doi.org/10.1007/s11257-020-09268-2.Suche in Google Scholar
17. Witchel, HJ, Oberndorfer, C, Needham, R, Healy, A, Klucken, J. Thigh-derived inertial sensor metrics to assess the sit-to-stand and stand-to-sit transitions in the timed up and go (TUG) task for quantifying mobility impairment in multiple sclerosis. Front Neurol 2018;9. https://doi.org/10.3389/fneur.2018.00684.Suche in Google Scholar PubMed PubMed Central
18. Kim, S, Nussbaum, MA. Performance evaluation of a wearable inertial motion capture system for capturing physical exposures during manual material handling tasks. Ergonomics 2013;56:314–26. https://doi.org/10.1080/00140139.2012.742932.Suche in Google Scholar PubMed
19. Chen, S, Brantley, JS, Kim, T, Ridenour, SA, Lach, J. Characterising and minimising sources of error in inertial body sensor networks. Int J Autonom Adapt Commun Syst 2013;6:253. https://doi.org/10.1504/ijaacs.2013.054828.Suche in Google Scholar
20. Configuring Systems for High Accuracy. Microsoft docs. Microsoft; 2018. Available from: https://docs.microsoft.com/en-us/windows-server/networking/windows-time-service/configuring-systems-for-high-accuracy [Accessed 17 Mar 2021].Suche in Google Scholar
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Review
- A review: strategies to reduce infection in tantalum and its derivative applied to implants
- Research Articles
- Biomechanical analysis of different fixed dental restorations on short implants: a finite element study
- Highly sensitive temperature sensor using one-dimensional Bragg Reflector for biomedical applications
- Synchronisation of wearable inertial measurement units based on magnetometer data
- Multiple ECG segments denoising autoencoder model
- Heart sound classification based on equal scale frequency cepstral coefficients and deep learning
- Towards a versatile mental workload modeling using neurometric indices
- An improved multi-source domain adaptation network for inter-subject mental fatigue detection based on DANN
Artikel in diesem Heft
- Frontmatter
- Review
- A review: strategies to reduce infection in tantalum and its derivative applied to implants
- Research Articles
- Biomechanical analysis of different fixed dental restorations on short implants: a finite element study
- Highly sensitive temperature sensor using one-dimensional Bragg Reflector for biomedical applications
- Synchronisation of wearable inertial measurement units based on magnetometer data
- Multiple ECG segments denoising autoencoder model
- Heart sound classification based on equal scale frequency cepstral coefficients and deep learning
- Towards a versatile mental workload modeling using neurometric indices
- An improved multi-source domain adaptation network for inter-subject mental fatigue detection based on DANN
