Dynamic Modeling of the Limb and the Passive Vibration Absorber System With the Aim of Suppressing the Rest Tremor of The Hand

Document Type : Article

Authors

1 1Department of Mechanical Engineering, University of Tabriz, Tabriz, Iran.

2 Department of Mechatronics Engineering, University of Tabriz, Tabriz, Iran.

Abstract

Hand tremor, a prevalent movement disorder, significantly impairs daily activities and quality of life. This paper investigates a passive vibration absorber system to suppress the hand tremor. An integrated dynamical model is developed, combining a 5-degree-of-freedom (DoF) multibody representation of the forearm and hand with a 2-DoF absorber system. The biomechanical model features three DoFs at the wrist and two at the elbow. The dynamic analysis employs a two-stage methodology. First, inverse dynamics calculates the stimulatory joint torques causing tremor, based on predefined oscillatory trajectories. To address the practical challenge of sensor drift in tremor measurement—a key limitation when using gyroscopes/accelerometers with Kalman filters—an innovative method based on Fourier expansion is introduced. This enhances the accuracy of estimation comparing traditional ones. Subsequently, forward dynamics simulations are performed with the calculated torques applied to the model integrated with the passive absorbers (masses connected via spring-damper elements). Simulation results demonstrate that this system significantly reduces tremor vibrations, particularly in the flexion/extension axes of the elbow and wrist. The model provides a robust foundation for optimizing the design of effective, non-invasive wearable devices for tremor suppression.

Keywords

Main Subjects

References

1. Bhatia, K.P., Bain, P., Bajaj, N., Elble, R.J., Hallett, M., Louis, E.D., Raethjen, J., Stamelou, M., Testa, C.M., Deuschl, G. and Tremor Task Force of the International Parkinson and Movement Disorder Society, 2018. Consensus statement on the classification of tremors from the task force on tremor of the International Parkinson and Movement Disorder Society. Movement Disorders, 33(1), pp.75-87. https://doi.org/10.1002/mds.27121
2. Rana, A. Q. and Chou, K. L., 2015. Essential Tremor In Clinical Practice, Springer, Berlin, Germany.
3. Alty, J.E. and Kempster, P.A., 2011. A practical guide to the differential diagnosis of tremor. Postgraduate Medical Journal, 87(1031), pp.623-629. https://doi.org/10.1136/pgmj.2009.089623
4. Shahtalebi, S., Atashzar, S.F., Samotus, O., Patel, R.V., Jog, M.S. and Mohammadi, A., 2020. PHTNet: Characterization and deep mining of involuntary pathological hand tremor using recurrent neural network models. Scientific Reports, 10(1), p.2195. https://doi.org/10.1038/s41598-020-58912-9
5. Jankovic, J. and STANLEY, F., 1980. Physiologic and pathologic tremors: diagnosis, mechanism, and management. Annals Of Internal Medicine, 93(3), pp.460-465.​ https://doi.org/10.7326/0003-4819-93-3-460
6. Louis, E.D. and Ferreira, J.J., 2010. How common is the most common adult movement disorder? Update on the worldwide prevalence of essential tremor. Movement Disorders, 25(5), pp.534-541. https://doi.org/10.1002/mds.22838
7. Ou, Z., Pan, J., Tang, S., Duan, D., Yu, D., Nong, H. and Wang, Z., 2021. Global trends in the incidence, prevalence, and years lived with disability of Parkinson's disease in 204 countries/territories from 1990 to 2019. Frontiers In Public Health, 9, p.776847. https://doi.org/10.3389/fpubh.2021.776847
8. Dorsey, E.R., Elbaz, A., Nichols, E., Abbasi, N., Abd-Allah, F., Abdelalim, A., Adsuar, J.C., Ansha, M.G., Brayne, C., Choi, J.Y.J. and Collado-Mateo, D., 2018. Global, regional, and national burden of Parkinson's disease, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology, 17(11), pp.939-953. http://dx.doi.org/10.1016/S1474-4422(18)30295-3
9. Davidson, A.D. and Charles, S.K., 2017. Fundamental principles of tremor propagation in the upper limb. Annals of Biomedical Engineering, 45, pp.1133-1147.https://doi.org/10.1007/s10439-016-1765-5
10. O’Connor, R.J. and Kini, M.U., 2011. Non-pharmacological and non-surgical interventions for tremor: a systematic review. Parkinsonism & Related Disorders, 17(7), pp.509-515.https://doi.org/10.1016/j.parkreldis.2010.12.016
11. Mo, J. and Priefer, R., 2021. Medical devices for tremor suppression: current status and future directions. Biosensors, 11(4), p.99. https://doi.org/10.3390/bios11040099​
12. Damen, J.A., 2016. Author’s reply to Woodward. BMJ, 354. https://doi.org/10.1136/bmj.i4485
13. Elias, W.J. and Shah, B.B., 2014. Tremor. Jama, 311(9) pp.948-954.  https://doi.org/10.1001/jama.2014.1397
14. Mohammadi, M., Zolfagharian, A., Bodaghi, M., Xiang, Y. and Kouzani, A.Z., 2022. 4D printing of soft orthoses for tremor suppression. Bio-Design and Manufacturing, 5(4), pp.786-807.​ https://doi.org/10.1007/s42242-022-00199-y
15. Kotovsky, J. and Rosen, M.J., 1998. A wearable tremor-suppression orthosis. Journal Of Rehabilitation Research And Development, 35(4), pp.373-387.​ PMID: 10220215
16. Hashemi, S.M., Golnaraghi, M.F. and Patla, A.E., 2004. Tuned vibration absorber for suppression of rest tremor in Parkinson's disease. Medical and Biological Engineering and Computing, 42, pp.61-70.​https://doi.org/10.1007/BF02351012
17. Rocon, E., Ruiz, A.F., Pons, J.L., Belda-Lois, J.M. and Sánchez-Lacuesta, J.J., 2005, April. Rehabilitation robotics: a wearable exo-skeleton for tremor assessment and suppression. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation (pp. 2271-2276). IEEE.​ https://doi.org/10.1109/ROBOT.2005.1570451
18. Rocon, E., Belda-Lois, J.M., Ruiz, A.F., Manto, M., Moreno, J.C. and Pons, J.L., 2007. Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression. IEEE Transactions On Neural Systems And Rehabilitation Engineering, 15(3), pp.367-378. https://doi.org/10.1109/TNSRE.2007.903917
19. Fromme, N.P., Camenzind, M., Riener, R. and Rossi, R.M., 2019. Need for mechanically and ergonomically enhanced tremor-suppression orthoses for the upper limb: a systematic review. Journal Of Neuroengineering And Rehabilitation, 16, pp.1-15. https://doi.org/10.1186/s12984-019-0543-7
20. Case, D., Taheri, B. and Richer, E., 2011. Design and characterization of a small-scale magnetorheological damper for tremor suppression. IEEE/ASME Transactions on Mechatronics, 18(1), pp.96-03. https://doi.org/10.1109/TMECH.2011.2151204
21. Case, D., Taheri, B. and Richer, E., 2013. Dynamical modeling and experimental study of a small-scale magnetorheological damper. IEEE/ASME Transactions on Mechatronics, 19(3), pp.1015-1024. https://doi.org/10.1109/TMECH.2013.2265701
22. Zahedi, A., Zhang, B., Yi, A. and Zhang, D., 2021. A soft exoskeleton for tremor suppression equipped with flexible semiactive actuator. Soft Robotics, 8(4), pp.432-447.​ https://doi.org/10.1089/soro.2019.0194
23. Zulkefli, A.M., Muthalif, A.G., Nordin, D.N. and Syam, T.M., 2019. Intelligent glove for suppression of resting tremor in Parkinson’s disease. Vibroengineering PROCEDIA, 29, pp.176-181.​http://dx.doi.org/10.21595/vp.2019.21078
24. Buki, E., Katz, R., Zacksenhouse, M. and Schlesinger, I., 2018. Vib-bracelet: a passive absorber for attenuating forearm tremor. Medical & Biological Engineering & Computing, 56, pp.923-930. https://doi.org/10.1007/s11517-017-1742-7
25. Rudraraju, S. and Nguyen, T., 2018. Wearable tremor reduction device (TRD) for human hands and arms. In Proceedings of the 2018 Design of Medical Devices Conference. ASME.​ https://doi.org/10.1115/DMD2018-6918%20
26. Ginsberg, J. H., 1998. Advanced Engineering Dynamics, 2nd Edn., Cambridge University Press, Cambridge, UK.
27. Rao, S. S., 2019. Mechanical Vibrations, 6th Edn., Pearson Prentice Hall, London, UK.
28. Noorani, S., Ghanbari, A. and Jafarizadeh, M., 2014. Walking stability on a slope for a planar 3-link biped robot via orbital stabilization upon a zero dynamic manifold. Sharif J. of Mechanical Engineering, 30.3 (2.2), pp.83-95. [In Persian]. https://sjme.journals.sharif.edu/article_6292.html
29. Kalman, R. E., 1960. A new approach to linear filtering and prediction problems, Journal of Basic Engineering, 82 (1), pp.35-45. https://doi.org/10.1115/1.3662552
30. Ogata, K., 2020. Modern Control Engineering, 5th Edn., pp. 648-650, Prentice Hall, New Jersey, USA.
31. Becker, B. C., MacLachlan, R. A. and Riviere, C. N., 2011. State estimation and feedforward tremor suppression for a handheld micromanipulator with a Kalman filter. In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5160-5165. IEEE. https://doi.org/10.1109/IROS.2011.6094935
32. Štebe, G., Krapež, P., Podobnik, J. and Kogoj, D., 2021. Trajectory tracking of an oscillating movement with a low-cost IMU in geodetic surveying applications. Measurement, 176, pp.109207.   https://doi.org/10.1016/j.measurement.2021.109207
33. Ommatmohammadi, M., Noorani, S. and Sadeghi, M. H., 2014. A novel drift-robust method for position estimation based on linear Kalman filter. J. of Mechanical Engineering University of Tabriz, 54 (4), pp 11-18. [In Persian]. https://doi.org/10.22034/jmeut.2024.61212.3399.
34. Rincón Ruiz, C. and Alencastre, J., 2023. Analytical modelling of a dynamic vibration absorber for Parkinson disease. In Engineering for a Changing World: Proceedings; 60th ISC, Technische Universität Ilmenau, http://dx.doi.org/10.22032/dbt.58878

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