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An Open and Extensible Data Acquisition and Processing Platform for Rehabilitation Applications

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Advanced Technologies, Systems, and Applications III (IAT 2018)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 59))

Abstract

Recently we witnessed a great deal of progress in the field of medicine, as well as treatments that improve the patient therapy and care. However, physiotherapy and rehabilitation fields still face the challenges of treating patients in remote regions. Considering that, developing a data acquisition and processing platform that collects data of rehabilitation movements at home can play a key role in the success of a patient’s recovery process. The designed system is composed of three main parts: wearable sensor capable of collecting movement data with 3 axial accelerometer, gyroscope and magnetometer sensors, central hub for processing and a cloud system which is used as a link between the therapist and patient. The system was tested for purpose of monitoring rehabilitation exercises usually done during recovery from an elbow fracture. Experimental results have shown that the system presented in this paper gives successful results for rehabilitation applications.

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References

  1. O’Sullivan, S.B., Schmitz, T.J., Fulk, G.: Physical rehabilitation. FA Davis (2013)

    Google Scholar 

  2. Theodoros, D., Russell, T., Latifi, R.: Telerehabilitation: current perspectives. Stud. Health Technol. Inform. 131, 191–210 (2008)

    Google Scholar 

  3. Castro, H., Cha, E., Provance, P.G.: Home-based physical telerehabilitation in patients with multiple sclerosis: A pilot study. J. Rehabil. Res. Dev. 45(9), 1361 (2008)

    Article  Google Scholar 

  4. Thiers, A., Orteye, A., Orlowski, K., Schrader, T.: Technology in physical therapy. In Proceedings of the International Joint Conference on Biomedical Engineering Systems and Technologies, vol. 5, pp. 500–505. SCITEPRESS-Science and Technology Publications, Lda, March 2014

    Google Scholar 

  5. Levene, T., Steele, R.: The Quantified self and physical therapy: the application of motion sensing technologies. In: Proceedings of the International Conference on Compute and Data Analysis, pp. 263–267. ACM, May 2017

    Google Scholar 

  6. Patel, S., Park, H., Bonato, P., Chan, L., Rodgers, M.: A review of wearable sensors and systems with application in rehabilitation. J. Neuroeng. Rehabil. 9(1), 21 (2012)

    Article  Google Scholar 

  7. Hadjidj, A., Souil, M., Bouabdallah, A., Challal, Y., Owen, H.: Wireless sensor networks for rehabilitation applications: challenges and opportunities. J. Netw. Comput. Appl. 36(1), 1–15 (2013)

    Article  Google Scholar 

  8. Zhou, H., Hu, H.: Human motion tracking for rehabilitation—a survey. Biomed. Sig. Process. Control 3(1), 1–18 (2008)

    Article  Google Scholar 

  9. Caporuscio, M., Weyns, D., Andersson, J., Axelsson, C., Petersson, G.: IoT-enabled physical telerehabilitation platform. In: 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), pp. 112–119. IEEE, April 2017

    Google Scholar 

  10. Bilic, D., Uzunovic, T., Golubovic, E., Ustundag, B.C.: Internet of things-based system for physical rehabilitation monitoring. In: 2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT), Sarajevo, Bosnia and Herzegovina, pp. 1–6 (2017)

    Google Scholar 

  11. Dobkin, B.H.: A rehabilitation-internet-of-things in the home to augment motor skills and exercise training. Neurorehabil. Neural Repair 31(3), 217–227 (2017)

    Article  Google Scholar 

  12. Maksimović, M., Vujović, V.: Internet of things based e-health systems: ideas, expectations and concerns. In: Handbook of Large-Scale Distributed Computing in Smart Healthcare, pp. 241–280. Springer, Cham (2017)

    Google Scholar 

  13. Sevcenco, A.M., Li, K.F.: Motion tracking and learning in telerehabilitation applications. In: 2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA), pp. 420–427. IEEE, November 2012

    Google Scholar 

  14. Moffet, H., Tousignant, M., Nadeau, S., Mérette, C., Boissy, P., Corriveau, H., Marquis, F., Cabana, F., Belzile, É.L., Ranger, P., Dimentberg, R.: Patient satisfaction with in-home telerehabilitation after total knee arthroplasty: results from a randomized controlled trial. Telemed. e-Health 23(2), 80–87 (2017)

    Article  Google Scholar 

  15. Liu, L., Miguel Cruz, A., Rios Rincon, A., Buttar, V., Ranson, Q., Goertzen, D.: What factors determine therapists’ acceptance of new technologies for rehabilitation–a study using the Unified Theory of Acceptance and Use of Technology (UTAUT). Disabil. Rehabil. 37(5), 447–455 (2015)

    Article  Google Scholar 

  16. Agostini, M., Moja, L., Banzi, R., Pistotti, V., Tonin, P., Venneri, A., Turolla, A.: Telerehabilitation and recovery of motor function: a systematic review and meta-analysis. J. Telemed. Telecare 21(4), 202–213 (2015)

    Article  Google Scholar 

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

    Article  Google Scholar 

  18. Han, S.L., Xie, M.J., Chien, C.C., Cheng, Y.C., Tsao, C.W.: Using MEMS-based inertial sensor with ankle foot orthosis for telerehabilitation and its clinical evaluation in brain injuries and total knee replacement patients. Microsyst. Technol. 22(3), 625–634 (2016)

    Article  Google Scholar 

  19. Meijer, H.A., Graafland, M., Goslings, J.C., Schijven, M.P.: A systematic review on the effect of serious games and wearable technology used in rehabilitation of patients with traumatic bone and soft tissue injuries. Archives of physical medicine and rehabilitation (2017)

    Google Scholar 

  20. Goncu-Berk, G., Topcuoglu, N.: A healthcare wearable for chronic pain management. Design of a smart glove for rheumatoid arthritis. Des. J. 20(Suppl. 1), S1978–S1988 (2017)

    Google Scholar 

  21. Tran, V., Lam, M.K., Amon, K.L., Brunner, M., Hines, M., Penman, M., Lowe, R., Togher, L.: Interdisciplinary eHealth for the care of people living with traumatic brain injury: a systematic review. Brain Injury 31(13–14), 1701–1710 (2017)

    Article  Google Scholar 

  22. Dobkin, B.H.: Rehabilitation strategies for restorative approaches after stroke and neurotrauma. In: Translational Neuroscience, pp. 539–553. Springer, Boston (2016)

    Google Scholar 

  23. https://github.com/inovatink/ws-hardware

  24. Lim, C.K., Chen, I.M., Luo, Z., Yeo, S.H.: A low cost wearable wireless sensing system for upper limb home rehabilitation. In: 2010 IEEE Conference on Robotics Automation and Mechatronics (RAM), pp. 1–8. IEEE, June 2010

    Google Scholar 

  25. Roggen, D., Pouryazdan, A., Ciliberto, M., BlueSense: designing an extensible platform for wearable motion sensing, sensor research and IoT applications. In: International Conference on Embedded Wireless Systems and Networks (2017)

    Google Scholar 

  26. González-Villanueva, L., Cagnoni, S., Ascari, L.: Design of a wearable sensing system for human motion monitoring in physical rehabilitation. Sensors 13(6), 7735–7755 (2013)

    Article  Google Scholar 

  27. Macedo, P., Afonso, J.A., Alexandre Rocha, L., Simões, R.: A telerehabilitation system based on wireless motion capture sensors. In: PhyCS (2014)

    Google Scholar 

  28. https://www.invensense.com/wp-content/uploads/2015/02/PS-MPU-9250A-01-v1.1.pdf

  29. https://cdn-shop.adafruit.com/product-files/2772/atmel-42181-sam-d21_datasheet.pdf

  30. http://ww1.microchip.com/downloads/en/DeviceDoc/50002466B.pdf

  31. https://github.com/inovatink/ws-hardware/blob/master/ws_v2_schematic.pdf

  32. https://www.mikroe.com/click

  33. https://www.github.com/inovatink/ws-hardware/blob/master/ws_v2_external_pinout.png

  34. https://github.com/inovatink/ws-hardware/tree/master/3D%20Drawings

  35. https://www.arduino.cc/en/main/software

  36. https://github.com/inovatink/ws-firmware-v1

  37. https://github.com/getsenic/gatt-python

  38. https://github.com/inovatink/ws-rpi3-hub

  39. https://www.summitmedicalgroup.com/library/adult_health/sma_radial_head_fracture_exercises/. Accessed 17 Apr 2018

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Acknowledgments

Authors would like to acknowledge Inovatink (www.inovatink.com) for providing material and operational support in realization of this project.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

    Sehrizada Sahinovic, Amina Dzebo & Tarik Uzunovic

  2. Department of Computer Engineering, Istanbul Technical University, Istanbul, Turkey

    Baris Can Ustundag

  3. Inovatink, Istanbul, Turkey

    Edin Golubovic

Authors
  1. Sehrizada Sahinovic
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  2. Amina Dzebo
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  3. Baris Can Ustundag
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  4. Edin Golubovic
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  5. Tarik Uzunovic
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Corresponding author

Correspondence to Sehrizada Sahinovic .

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Editors and Affiliations

  1. Faculty of Electrical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

    Samir Avdaković

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Sahinovic, S., Dzebo, A., Ustundag, B.C., Golubovic, E., Uzunovic, T. (2019). An Open and Extensible Data Acquisition and Processing Platform for Rehabilitation Applications. In: Avdaković, S. (eds) Advanced Technologies, Systems, and Applications III. IAT 2018. Lecture Notes in Networks and Systems, vol 59. Springer, Cham. https://doi.org/10.1007/978-3-030-02574-8_32

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