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FiMec tremor stabilization spoon: design and active stabilization control of two DoF robotic eating devices for hand tremor patients

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Abstract

This article is about vibration-damping robotic eating devices designed for use by people who have difficulty in eating due to hand tremors due to neuromuscular system disorder. The robotic eating device has two degrees of freedom (DoF). It contains an active controller structure to absorb vibrations in the y- and z-directions. In the handle part of the robotic eating device, there are two DC motors placed on the y- and z-axis, a three-axis IMU inertia sensor, an embedded system board, and a power unit. To absorb the vibration measured from the IMU sensor, the position control of the two motors to which the spoon is connected is provided by PID controllers. The part of the spoon (the pit surface) where the food is placed is tried to be kept constant. To test the vibration-damping performance of the control method, the dynamic model of the spoon along the eating kinematic trajectory was simulated in the SimMechanics environment using vibration data from ten tremor patients. The results show that the stabilization method can absorb the vibration in the hand of the person in the range of 84–99.409% and successfully provide the stabilization of the spoon tip. This damping rate is promising for providing a healthy diet for hand tremor patients.

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Data availability

A synthesized eating kinematic trajectory dataset for patients can be transmitted if communication with the authors passes.

References

  1. NINDS Parkinson’s disease information (2021) focus on Parkinson’s disease research. Internet 2021:2020–2022

    Google Scholar 

  2. Fraiwan L, Amir S, Ahmed F, Halepota J (2018) Design of a stabilisation platform for Parkinson’s disease patient. J Med Eng Technol 42:43–51. https://doi.org/10.1080/03091902.2018.1430183

    Article  PubMed  Google Scholar 

  3. Pourfar MH, Louis ED (2006) Essential tremor. Curr Ther Neurol Dis, pp. 288–292. https://doi.org/10.1016/B9780323034326.500660

  4. ALS (2021) Understanding ALS. https://www.als.org/understanding-als

  5. Abbasi M, Afsharfard A, Arasteh R, Safaie J (2018) Design of a noninvasive and smart hand tremor attenuation system with active control: a simulation study. Med Biol Eng Comput 56:1315–1324. https://doi.org/10.1007/s11517-017-1769-9

    Article  PubMed  Google Scholar 

  6. Bhidayasiri R (2005) Differential diagnosis of common tremor syndromes. Postgrad Med J 81:756–762. https://doi.org/10.1136/pgmj.2005.032979

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Bhidayasiri R, Maytharakcheep S, Phumphid S, Maetzler W (2022) Improving functional disability in patients with tremor: a clinical perspective of the efficacies, considerations, and challenges of assistive technology. J Neurol Sci 435:120197. https://doi.org/10.1016/j.jns.2022.120197

    Article  PubMed  Google Scholar 

  8. Abbasi M, Afsharfard A (2018) Modeling and experimental study of a hand tremor suppression system. Mech Mach Theory 126:189–200. https://doi.org/10.1016/j.mechmachtheory.2018.04.009

    Article  Google Scholar 

  9. Case D, Taheri B, Richer E (2013) Design and characterization of a small-scale magnetorheological damper for tremor suppression. IEEE/ASME Trans Mechatronics 18:96–103. https://doi.org/10.1109/TMECH.2011.2151204

    Article  Google Scholar 

  10. Case D, Taheri B, Richer E (2013) Multiphysics modeling of magnetorheological dampers. Int J Multiphys 7:61–76. https://doi.org/10.1260/1750-9548.7.1.61

    Article  Google Scholar 

  11. Cavalcanti A, Amaral MF, Silva e Dutra FCM, Santos AVF, Licursi LA, Silveira ZC (2020) Adaptive eating device: performance and satisfaction of a person with Parkinson’s disease. Can J Occup Ther 87:211–220. https://doi.org/10.1177/0008417420925995

    Article  PubMed  Google Scholar 

  12. Nilsson MH, Iwarsson S, Thordardottir B, Haak M (2015) Barriers and facilitators for participation in people with Parkinson’s disease. J Parkinsons Dis 5:983–992. https://doi.org/10.3233/JPD-150631

    Article  PubMed  Google Scholar 

  13. Dai H, Lin H, Lueth TC (2015) Quantitative assessment of Parkinsonian bradykinesia based on an inertial measurement unit. Biomed Eng Online 14:1–13. https://doi.org/10.1186/s12938-015-0067-8

    Article  Google Scholar 

  14. Niazmand K, Tonn K, Kalaras A, Fietzek UM, Mehrkens JH, TC Lueth (2011) Quantitative evaluation of Parkinson’s disease using sensor based smart glove. Proc. - IEEE Symp. Comput. Med Syst, pp. 1–8, https://doi.org/10.1109/CBMS.2011.5999113

  15. Salarian A, Russmann H, Wider C, Burkhard PR, Vingerhoets FJG, Aminian K (2007) Quantification of tremor and bradykinesia in Parkinson’s disease using a novel ambulatory monitoring system. IEEE Trans Biomed Eng 54:313–322. https://doi.org/10.1109/TBME.2006.886670

    Article  PubMed  Google Scholar 

  16. Pierleoni P, Palma L, Belli A, Pernini L (2014) A real-time system to aid clinical classification and quantification of tremor in Parkinson’s disease. 2014 IEEE-EMBS Int Conf Biomed Heal Informatics. BHI 2014:113–116. https://doi.org/10.1109/BHI.2014.6864317

    Article  Google Scholar 

  17. Ohara E, Yano K, Horihata S, Aoki T, Nishimoto Y (2009) Tremor suppression control of meal-assist robot with adaptive filter. 2009 IEEE Int. Conf Rehabil Robot ICORR 2009:498–503. https://doi.org/10.1109/ICORR.2009.5209565

    Article  Google Scholar 

  18. Rahnavard M, Hashemi M, Farahmand F, Dizaji AF (2014) Designing a hand rest tremor dynamic vibration absorber using H2 optimization method. J Mech Sci Technol 28:1609–1614. https://doi.org/10.1007/s12206-014-0104-8

    Article  Google Scholar 

  19. Teixeira CJ, Bicho E, Rocha LA, Gago MF (2013) A self-tunable dynamic vibration absorber: Parkinson’s disease’s tremor suppression. 3rd Port Bioeng Meet ENBENG 2013 - B. Proc https://doi.org/10.1109/ENBENG.2013.6518440

  20. Taheri B, Case D, Richer E (2014) Robust controller for tremor suppression at musculoskeletal level in human wrist. IEEE Trans Neural Syst Rehabil Eng 22:379–388. https://doi.org/10.1109/TNSRE.2013.2295034

    Article  PubMed  Google Scholar 

  21. Zamanian AH, Richer E (2017) Adaptive disturbance rejection controller for pathological tremor suppression with permanent magnet linear motor. Proceedings of the ASME 2017 Dynamic System and Control Conference, pp. 1–7, https://doi.org/10.1115/DSCC2017-5151

  22. Herrnstadt G, Menon C (2016) Voluntary-driven elbow orthosis with speed-controlled tremor suppression. Front Bioeng Biotechnol 4:1–10. https://doi.org/10.3389/fbioe.2016.00029

    Article  Google Scholar 

  23. Huen D, Liu J, Lo B (2016) An integrated wearable robot for tremor suppression with context aware sensing, BSN 2016 - 13th Annu. Body Sens Networks Conf pp. 312–317, https://doi.org/10.1109/BSN.2016.7516280

  24. Rocon E, Belda-Lois JM, Ruiz AF, Manto M, Moreno JC, Pons JL (2007) Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression. IEEE Trans Neural Syst Rehabil Eng 15:367–378. https://doi.org/10.1109/TNSRE.2007.903917

    Article  CAS  PubMed  Google Scholar 

  25. Taheri B, Case D, Richer E (2014) Robust controller for tremor suppression at musculoskeletal level in human wrist. IEEE Trans Neural Syst Rehabil Eng 22(2):379–388. https://doi.org/10.1109/TNSRE.2013.2295034

    Article  PubMed  Google Scholar 

  26. Gyenne Technologies Co.: Arm vibration damping devices (2017) Google Pat. US2017/032.

  27. Lazarek M, Brzeski P, Perlikowski P (2018) Design and identification of parameters of tuned mass damper with inerter which enables changes of inertance. Mech Mach Theory 119:161–173. https://doi.org/10.1016/j.mechmachtheory.2017.09.004

    Article  Google Scholar 

  28. Satar RMA, As’Arryi A, Abdullah MF, Zain MZBM (2021) The development of cutlery tool to reduce Parkinson movement. IOP Conf Ser Mater Sci Eng 1062:1–7. https://doi.org/10.1088/1757-899X/1062/1/012001

    Article  Google Scholar 

  29. Pathak A, Redmond JA, Allen M, Chou KL (2014) A noninvasive handheld assistive device to accommodate essential tremor: a pilot study. Mov Disord 29:838–842. https://doi.org/10.1002/mds.25796

    Article  PubMed  Google Scholar 

  30. Skaramagkas V, Andrikopoulos G, Kefalopoulou Z, Polychronopoulos P (2021) A study on the essential and Parkinson’s arm tremor classification. Signals 2:201–224. https://doi.org/10.3390/signals2020016

    Article  Google Scholar 

  31. Krasovsky T, Weiss PL, Zuckerman O, Bar A, Keren-Capelovitch T, Friedman J (2020) Dataspoon: validation of an instrumented spoon for assessment of self-feeding. Sensors 20:1–11. https://doi.org/10.3390/s20072114

    Article  Google Scholar 

  32. Patwardhan A, Prakash A, Chittawadigi RG (2018) Kinematic analysis and development of simulation software for Nex Dexter Robotic Manipulator. Procedia Comput Sci 133:660–667. https://doi.org/10.1016/j.procs.2018.07.101

    Article  Google Scholar 

  33. Fernandes JJ, Selvakumar AA (2018) Kinematic and Dynamic Analysis of 3PUU parallel manipulator for medical applications. Procedia Comput Sci 133:604–611. https://doi.org/10.1016/j.procs.2018.07.091

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Mechatronics Engineering, Fırat University, Elazığ, Turkey

    Beyda Taşar, Alper K. Tanyıldızı & Oğuz Yakut

  2. Department of Mechanical Engineering, Adıyaman University, Adıyaman, Turkey

    Ahmet B. Tatar

Authors
  1. Beyda Taşar
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  2. Ahmet B. Tatar
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  3. Alper K. Tanyıldızı
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  4. Oğuz Yakut
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All authors contributed to the work. All authors read and approved the final manuscript.

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Correspondence to Ahmet B. Tatar.

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Taşar, B., Tatar, A.B., Tanyıldızı, A.K. et al. FiMec tremor stabilization spoon: design and active stabilization control of two DoF robotic eating devices for hand tremor patients. Med Biol Eng Comput 61, 2757–2768 (2023). https://doi.org/10.1007/s11517-023-02886-z

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