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A Bio-cooperative Robotic System to Ensure Ergonomic Postures During Upper Limb Rehabilitation in Occupational Contexts

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Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) (IEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 826))

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Abstract

Inappropriate work conditions represent the main cause for upper limb musculoskeletal disorders in many working professions. In this context, robotics and novel technologies might represent a new frontier of devices able to treat musculoskeletal disorders. This paper aims at proposing and preliminary testing a bio-cooperative robotic platform for upper limb rehabilitation composed of a redundant anthropomorphic manipulator, an active arm gravity support and a multimodal interface. With the proposed platform it is possible to extract performance and muscular fatigue indicators and accordingly adapt the level of assistance, provided by the anthropomorphic robot arm, and of arm support. Furthermore, it was verified if the use of the proposed platform allowed subjects to execute highly controlled movements while maintaining an ergonomic posture able to limit the trunk compensatory movements during reaching. A preliminary study on 8 healthy subjects was carried out and the Rapid Upper Limb Assessment test was adopted to assess the subject’s upperlimb posture during the rehabilitation task. The obtained results are encouraging for extending the study for rehabilitation in occupational contexts of patients with upper limb musculoskeletal pathologies.

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References

  1. Hämäläinen P, Saarela KL, Takala J (2009) Global trend according to estimated number of occupational accidents and fatal work-related diseases at region and country level. J Saf Res 40(2):125–139

    Article  Google Scholar 

  2. Dembe AE, Erickson JB, Delbos R (2004) Predictors of work-related injuries and illnesses: national survey findings. J Occup Environ Hyg 1(8):542–550

    Article  Google Scholar 

  3. Hakim RM, Tunis BG, Ross MD (2017) Rehabilitation robotics for the upper extremity: review with new directions for orthopaedic disorders. Disabil Rehabil Assist Technol 12(8):765–771

    Article  Google Scholar 

  4. Wang Q, Markopoulos P, Yu B, Chen W, Timmermans A (2017) Interactivewearable systems for upper body rehabilitation: a systematic review. J Neuroeng Rehabil 14(1):20

    Article  Google Scholar 

  5. Schwickert L, Klenk J, Stahler A, Lindemann U (2011) Robotic-assisted rehabilitation of proximal humerus fractures in virtual environments. Zeitschrift für Gerotologie und Geriatrie 44:387–392. https://doi.org/10.1007/s00391-011-0258-2

    Article  Google Scholar 

  6. Padilla-Castaneda MA, Sotgiu E, Frisoli A, Bergamasco M, Orsini P, Martiradonna A, Olivieri S, Mazzinghi G, Laddaga C (2013) A virtual reality system for robotic-assisted orthopedic rehabilitation of forearm and elbow fractures. In: IEEE/RSJ international conference on intelligent robots and systems

    Google Scholar 

  7. Simonetti D, Zollo L, Papaleo E, Carpino G, Guglielmelli E (2016) Multi-modal adaptive interfaces for 3D robot-mediated upper limb neurorehabilitation: an overview of bio-cooperative systems. Robot Auton Syst 85:62–72

    Google Scholar 

  8. Cirstea MC, Levin MF (2000) Compensatory strategies for reaching in stroke. Brain 123(5):940–953

    Article  Google Scholar 

  9. Harvey RL (2014) Stroke recovery and rehabilitation. Demos Medical Publishing, New York

    Google Scholar 

  10. Alankus G, Kelleher C (2012) Reducing compensatory motions in video games for stroke rehabilitation. In: Proceedings of the ACM annual conference on human factors computing system (CHI), pp 2049–2058

    Google Scholar 

  11. Zhi YX, Lukasik M, Li MH, Dolatabadi E, Wang RH, Taati B (2017) Automatic detection of compensation during robotic stroke rehabilitation therapy. Rehabilitation devices and systems

    Google Scholar 

  12. Wong MY, Wong MS (2009) Measurement of postural change in trunk movements using three sensor modules. IEEE Trans Instrum Meas 58(8):2737–2742

    Article  Google Scholar 

  13. Maduri A, Wilson SE (2009) Lumbar position sense with extreme lumbar angle. J Electromyogr Kinesiol 19(4):607–613

    Article  Google Scholar 

  14. Papaleo E, Zollo L, Spedaliere L, Guglielmelli E (2013) Patient-tailored adaptive robotic system for upper-limb rehabilitation. In: 2013 IEEE international conference on robotics and automation (ICRA), pp 3860–3865. IEEE

    Google Scholar 

  15. Papaleo E, Zollo L, Garcia-Aracil N, Badesa F, Morales R, Mazzoleni S et al (2015) Upper-limb kinematic reconstruction during stroke robot-aided therapy. In: Medical & Biological Engineering & Computing, pp 815–828. Springer

    Google Scholar 

  16. Hermens HJ et al (1999) European recommendations for surface electromyography. Roessingh Res Dev 8(2):13–54

    Google Scholar 

  17. McAtamney L, Corlett EN (1993) RULA: a survey method for the investigation of work-related upper limb disorders. Appl Ergon 24(2):91–99

    Google Scholar 

  18. Lauretti C, Davalli A, Sacchetti R, Guglielmelli E, Zollo L (2016) Fusion of M-IMU and EMG signals for the control of trans-humeral prostheses. In: IEEERAS/EMBS international conference on biomedical robotics and biomechatronics

    Google Scholar 

  19. Lauretti C et al (2017) Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots. In: 2017 international conference on rehabilitation robotics (ICORR). IEEE

    Google Scholar 

Download references

Acknowledgement

This work was supported partly by the Italian Institute for Labour Accidents (INAIL) with the RehabRobo@work (CUP: C82F17000040001), PCR 1/2 (CUP: E57B16000160005) and PPR AS 1/3 (CUP: E57B16000160005) projects and partly by the European Project H2020/AIDE: Adaptive Multimodal Interfaces to Assist Disabled People in Daily Activities (CUP: J42I15000030006).

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Correspondence to F. Scotto di Luzio .

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Scotto di Luzio, F. et al. (2019). A Bio-cooperative Robotic System to Ensure Ergonomic Postures During Upper Limb Rehabilitation in Occupational Contexts. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 826. Springer, Cham. https://doi.org/10.1007/978-3-319-96065-4_37

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