Research on Biomedical Engineering
http://www.rbejournal.periodikos.com.br/article/doi/10.1590/2446-4740.03017
Research on Biomedical Engineering
Original article

Peripheral device to quantify grip and pinch capacity of children

Karoline de Paula Bischof, Alessandro Pereira da Silva, Willian Molizane Almeida Motta, André Roberto Fernandes da Silva, Antônio Vinícius Morais, Terigi Augusto Scardovelli, Hélio Martucci Neto, Ana Lúcia Manrique, Silvia Regina Matos da Silva Boschi

Abstract

Introduction: Grip and pinch movements are important to perform daily activities and to manipulate objects. In this paper we describe the development and evaluation of a peripheral device to quantify cylindrical grip, pulp‑to‑pulp pinch, pulp-to-side pinch strength and range of motion of children.

Methods: Three objects were selected: a door handle, a switch, and a key, which were instrumented with force sensing resistors to analyse the strength. Potentiometers were used to verify the range of motion and micro switches to assure the correct position of the fingers during the movement execution. Thirty volunteers (8.77 ± 1.28), both male and female,
were selected to test the peripheral device functionality.

Results: The results determined the minimum necessary strength values for the object activation and maximum displacement, in which the values are 2.5N, 40°; 2.7N, 55°; and 2.8N, 100%, for door handle object, key object, and switch object, respectively. In the functionally tests, volunteers have shown a superior strength for activating each object and 73.33% of them have completed the range movement in the key object, 86.67% in the switch object, and 93.33% in the door handle object.

Conclusion: The developed peripheral device enabled the measurement of range and static and dynamic strength
of grip and pinch movements of children.

Keywords

Strength, Range of motion, Grip, Pinch, Device

References

Boschi SRMS, Frère AF. Grip and pinch capability assessment system for children. Med Eng Phys. 2013; 35(5):626-35. http://dx.doi.org/10.1016/j.medengphy.2012.07.008. PMid:22951038.

Bouwsema H, Van Der Sluis CK, Bongers RM. Effect of feedback during virtual training of grip force control with a myoelectric prosthesis. PLoS One. 2014; 9(5):1-15. http://dx.doi.org/10.1371/journal.pone.0098301. PMid:24865570.

Butterfield SA, Lehnhard RA, Loovis EM, Saucier D. Grip strength performances by 5- to 19-year-olds. Percept Mot Skills. 2009; 109(2):362-70. http://dx.doi.org/10.2466/pms.109.2.362- 370. PMid:20037989.

Canuto G, Scardovelli TA, Boschi SRMS, Lopes-Martins RAB, Silva AP. Dinamômetro eletrônico para medição da força em pacientes com mobilidade reduzida. In: Proceedings of the VII Latin American Congress on Biomedical Engineering (CLAIB); 2016 Oct 26-28; Bucaramanga, Colombia. Colombia: CLAIB; 2016. p. 1-4.

Dimbwadyo-Terrer I, Trincado-Alonso F, Reyes-Guzmán ADL, Aznar MA, Alcubilla C, Pérez-Nombela S, et al. Upper limb rehabilitation after spinal cord injury: a treatment based on a data glove and an immersive virtual reality environment. Disabil Rehabil Assist Technol. 2016; 11(6):1-6. http://dx.doi.org/10.3109/17483107.2015.1027293. PMid:26181226.

Dovat L, Lambercy O, Gassert R, Maeder T, Milner T, Leong TC, Burdet E. HandCARE: a cable-actuated rehabilitation system to train hand function after stroke. IEEE Trans Neural Syst Rehabil Eng. 2008; 16(6):582-91. http://dx.doi.org/10.1109/TNSRE.2008.2010347. PMid:19144590.

Duff SV, Aaron DH, Gogola GR, Valero-Cuevas FJ. Innovative evaluation of dexterity in pediatrics. J Hand Ther. 2015; 28(2):144-9. http://dx.doi.org/10.1016/j.jht.2015.01.004. PMid:25835255.

Friedman N, Chan V, Reinkensmeyer AN, Beroukhim A, Zambrano GJ, Bachman M, Reinkensmeyer DJ. Retraining and assessing hand movement after stroke using the MusicGlove: comparison with conventional hand therapy and isometric grip training. J Neuroeng Rehabil. 2014; 11:76. PMid:24885076.

Hasegawa Y, Ariyama T, Kamibayashi K. Pinching force accuracy affected by thumb sensation in human force augmentation. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems; 2012 Oct 7-12; Vilamoura, Portugal. USA: IEEE Computer Society; 2012. p. 3943-8. http://dx.doi.org/10.1109/IROS.2012.6386081.

Heo P, Kim J. Power-assistive finger exoskeleton with a palmar opening at the fingerpad. IEEE Trans Biomed Eng. 2014; 61(11):2688-97. http://dx.doi.org/10.1109/TBME.2014.2325948. PMid:24860025.

Hilton CL, Goloff SE, Altaras O, Josman N. Review of instrument development and testing studies for children and youth. Am J Occup Ther. 2013; 67(3):e30-54. http://dx.doi.org/10.5014/ajot.2013.007831. PMid:23597698.

Interlink Electronics [internet]. Westlake Village; 2017 [cited 2017 June 8]. Available from: http://interlinkelectronics.com/

Kar SS, Ramalingam A. Is 30 the magic number? Issues in sample size estimation. NJCM. 2013; 4(1):175-9.

Lin DCY, Chang J-H, Shieh S-J, Tsai FHJ, Lee YL. Prediction of hand strength by hand injury severity scoring system in hand injured patients. Disabil Rehabil. 2012; 34(5):423-8. http://dx.doi.org/10.3109/09638288.2011.607550. PMid:21967094.

Monteiro CBM, Jakabi CM, Palma GCS, Torriani-Pasin C, Meira CM. Motor learning in children with cerebral palsy. Rev Bras Cresc e Desenv Hum. 2010; 20(3):11-23.

Nowak DA, Glasauer S, Hermsdörfer J. Force control in object manipulation: a model for the study of sensorimotor control strategies. Neurosci Biobehav Rev. 2013; 37(8):1578-86. http://dx.doi.org/10.1016/j.neubiorev.2013.06.003. PMid:23791788.

Scardovelli TA, Frère AF. The design and evaluation of a peripheral device for use with a computer game intended for children with motor disabilities. Comput Methods Programs Biomed. 2015; 118(1):44-58. http://dx.doi.org/10.1016/j.cmpb.2014.10.002. PMid:25459524.

Schieber MH, Santello M. Hand function: peripheral and central constraints on performance. J Appl Physiol. 2004; 96(6):2293- 300. http://dx.doi.org/10.1152/japplphysiol.01063.2003. PMid:15133016.

Schrama PP, Stenneberg MS, Lucas C, Van Trijffel E. Intraexaminer reliability of hand-held dynamometry in the upper extremity: a systematic review. Arch Phys Med Rehabil. 2014; 95(12):2444-69. http://dx.doi.org/10.1016/j.apmr.2014.05.019. PMid:24909587.

Strohrmann C, Labruyère R, Gerber CN, Van Hedel HJ, Arnrich B, Tröster G. Monitoring motor capacity changes of children during rehabilitation using body worn sensors. J Neuroeng Rehabil. 2013; 10:83. PMid:23899401.

Touvet F, Roby-Brami A, Maier MA, Eskiizmirliler S. Grasp: Combined contribution of object properties and task constraints on hand and finger posture. Exp Brain Res. 2014; 232(10):3055-67. http://dx.doi.org/10.1007/s00221-014-3990- 1. PMid:24888535.

Wang H, Hsu C, Chiu D, Tsai S. Using augmented reality gaming system to enhance hand rehabilitation. In: Proceedings of the 2nd International Conference on Education Technology and Computer; 2010 June 22-24; Shanghai, China. USA: IEEE Computer Society; 2010. p. 243- 6.

Zhang D, Shen Y, Ong SK, Nee AYC. An affordable augmented reality based rehabilitation system for hand motions. In: Proceedings of the International Conference on Cyberworlds; 2010 Oct 20-22; Washington. USA: IEEE Computer Society; 2010. p. 346-53. http://dx.doi.org/10.1109/CW.2010.31.

 

5b2b779c0e88258e1bc6d923 rbejournal Articles
Links & Downloads

Res. Biomed. Eng.

Share this page
Page Sections