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International Workshop on Agents Applied in Health Care

International Workshop on Agents and Multi-Agent Systems for AAL and e-Health

A2HC 2017, AHEALTH 2017: Agents and Multi-Agent Systems for Health Care pp 3–24Cite as

Agent-Based Systems for Telerehabilitation: Strengths, Limitations and Future Challenges

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10685))

Abstract

Telerehabilitation in older adults is most needed in the patient environments, rather than in formal ambulatories or hospitals. Supporting such practices brings significant advantages to patients, their family, formal and informal caregivers, clinicians, and researchers. Several techniques and technologies have been developed aiming at facilitating and enhancing the effectiveness of telerehabilitation. This paper gives a quick overview of the state of the art, investigating video-based, wearable, robotic, distributed, and gamified telerehabilitation solutions. In particular, agent-based solutions are analyzed and discussed addressing strength, limitations, and future challenges. Elaborating on functional requirements expressed by professional physiotherapists and researchers, the need for extending multi-agent systems (MAS) peculiarities at the sensing level in wearable solutions establishes new research challenges.

Employed in cyber-physical scenarios with users-sensors and sensors-sensors interactions, MAS are requested to handle timing constraints, scarcity of resources and new communication means, which are crucial for providing real-time feedback and coaching.

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Notes

  1. 1.

    First phase after a surgical intervention on the knee. It is considered over when the patient is able to passively perform a \(90^\circ \) extension.

References

  1. Calvaresi, D., Cesarini, D., Sernani, P., Marinoni, M., Dragoni, A.F., Sturm, A.: Exploring the ambient assisted living domain: a systematic review. J. Ambient Intell. Humanized Comput. 8(2), 239–257 (2017). https://doi.org/10.1007/s12652-016-0374-3

  2. Cesarini, D., Calvaresi, D., Marinoni, M., Buonocunto, P., Buttazzo, G.: Simplifying tele-rehabilitation devices for their practical use in non-clinical environments. In: Ortuño, F., Rojas, I. (eds.) IWBBIO 2015. LNCS, vol. 9044, pp. 479–490. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16480-9_47

    Google Scholar 

  3. Hailey, D., Roine, R., Ohinmaa, A., Dennett, L.: Evidence of benefit from telerehabilitation in routine care: a systematic review. J. Telemedicine Telecare 17(6), 281–287 (2011)

    Article  Google Scholar 

  4. Fasola, J., Mataric, M.: A socially assistive robot exercise coach for the elderly. Journal of Human-Robot Interaction 2(2), 3–32 (2013)

    Article  Google Scholar 

  5. Obdržálek, Š., Kurillo, G., Ofli, F., Bajcsy, R., Seto, E., Jimison, H., Pavel, M.: Accuracy and robustness of kinect pose estimation in the context of coaching of elderly population. In: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1188–1193. IEEE (2012)

    Google Scholar 

  6. Rodriguez, A.C., Roda, C., González, P., Navarro, E.: Contextualizing tasks in tele-rehabilitation systems for older people. In: Cleland, I., Guerrero, L., Bravo, J. (eds.) IWAAL 2015. LNCS, vol. 9455, pp. 29–41. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26410-3_4

    Chapter  Google Scholar 

  7. Calvaresi, D., Cesarini, D., Marinoni, M., Buonocunto, P., Bandinelli, S., Buttazzo, G.: Non-intrusive patient monitoring for supporting general practitioners in following diseases evolution. In: Ortuño, F., Rojas, I. (eds.) IWBBIO 2015. LNCS, vol. 9044, pp. 491–501. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16480-9_48

    Google Scholar 

  8. Mozaffarian, D., Benjamin, E.J., Go, A.S., Arnett, D.K., Blaha, M.J., Cushman, M., Das, S.R., de Ferranti, S., Després, J.-P., Fullerton, H.J., et al.: Executive summary: Heart disease and stroke statistics-2016 update: a report from the american heart association. Circulation 133(4), 447 (2016)

    Article  Google Scholar 

  9. Kairy, D., Lehoux, P., Vincent, C., Visintin, M.: A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disabil. Rehabil. 31(6), 427–447 (2009)

    Article  Google Scholar 

  10. Mutingi, M., Mbohwa, C.: Developing multi-agent systems for mhealth drug delivery. In: Adibi, S. (ed.) Mobile Health. SSB, vol. 5, pp. 671–683. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-12817-7_29

    Google Scholar 

  11. Morreale, P.A.: Wireless sensor network applications in urban telehealth. In: 21st International Conference on Advanced Information Networking and Applications Workshops, 2007, AINAW 2007, vol. 2, pp. 810–814. IEEE (2007)

    Google Scholar 

  12. Li, K.F.: Smart home technology for telemedicine and emergency management. J. Ambient Intell. Humaniz. Comput. 4(5), 535–546 (2013)

    Article  Google Scholar 

  13. Bergmann, J.H.M., McGregor, A.H.: Body-worn sensor design: what do patients and clinicians want? Ann. Biomed. Eng. 39(9), 2299–2312 (2011)

    Article  Google Scholar 

  14. Akdoğan, E., Taçgın, E., Arif Adli, M.: Knee rehabilitation using an intelligent robotic system. J. Intell. Manuf. 20(2), 195–202 (2009)

    Article  Google Scholar 

  15. Chen, J., Zhang, X., Li, R.: A novel design approach for lower limb rehabilitation training robot. In: 2013 IEEE International Conference on Automation Science and Engineering (CASE), pp. 554–557. IEEE (2013)

    Google Scholar 

  16. de Abreu, P.F., Werneck, V.M.B., da Costa, R.M.E.M., de Carvalho, L.A.V.: Employing multi-agents in 3-d game for cognitive stimulation. In: XIII Symposium on Virtual Reality, pp. 73–78. IEEE (2011)

    Google Scholar 

  17. Iarlori, S., Ferracuti, F., Giantomassi, A., Longhi, S.: Rgbd camera monitoring system for Alzheimer’s disease assessment using recurrent neural networks with parametric bias action recognition. IFAC Proc. Volumes 47(3), 3863–3868 (2014)

    Article  Google Scholar 

  18. Fraile, J.A., Bajo, J., Corchado, J.M., Abraham, A.: Applying wearable solutions in dependent environments. IEEE Trans. Inform. Technol. Biomed. 14(6), 1459–1467 (2010)

    Article  Google Scholar 

  19. Smith, S.T., Talaei-Khoei, A., Ray, M., Ray, P.: Agent-based monitoring of functional rehabilitation using video games. In: Brahnam, S., Jain, L.C. (eds.) Advanced Computational Intelligence Paradigms in Healthcare 5, vol. 326, pp. 113–141. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16095-0_7

    Chapter  Google Scholar 

  20. Cesarini, D., Buonocunto, P., Marinoni, P., Buttazzo, G.: A telerehabilitation framework for lower-limb functional recovery. In: International Conference on Body Area Networks, BodyNets 2014, London, UK. IEEE Computer Society (2014)

    Google Scholar 

  21. Cesarini, D., Calvaresi, D., Farnesi, C., Taddei, D., Frediani, S., Ungerechts, B.E., Hermann, T.: Mediation: an embedded system for auditory feedback of hand-water interaction while swimming. Procedia Eng. 147, 324–329 (2016)

    Article  Google Scholar 

  22. Ungerechts, B., Cesarini, D., Wiebel, V., Hermann, T.: Ears drive hands: sonification of liquid effects induced by aquatic space activities contributes to cognitive representation (2015)

    Google Scholar 

  23. Adibi, S.: Mobile Health: A Technology Road Map, vol. 5. Springer, Berlin (2015). https://doi.org/10.1007/978-3-319-12817-7

    Google Scholar 

  24. Vourvopoulos, A., Liarokapis, F.: Evaluation of commercial brain-computer interfaces in real and virtual world environment: a pilot study. Comput. Electr. Eng. 40(2), 714–729 (2014)

    Article  Google Scholar 

  25. Eriksson, J., Mataric, M.J., Winstein, C.: Hands-off assistive robotics for post-stroke arm rehabilitation. In: Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR 2005), pp. 21–24 (2005)

    Google Scholar 

  26. Jacobs, A., Timmermans, A., Michielsen, M., Plaetse, M.V., Markopoulos, P.: Contrast: gamification of arm-hand training for stroke survivors. In: CHI 2013 Extended Abstracts on Human Factors in Computing Systems, pp. 415–420. ACM (2013)

    Google Scholar 

  27. Miranda, P., Aguilar, J.: A prototype of a multiagents system for a telemedicine environment. Eng. Intell. Syst. Electr. Eng. Commun. 11(1), 3–8 (2003)

    Google Scholar 

  28. Bergenti, F., Poggi, A.: Multi-agent systems for the application and employing of e-health services. In: Cruz-Cunha, M.M., Tavares, A.J., Simoes, R. (eds.) Handbook of Research on Developments in E-Health and Telemedicine: Technological and Social Perspectives, pp. 247–264. IGI Global (2010)

    Google Scholar 

  29. Roda, C., Rodríguez, A., López-Jaquero, V., González, P., Navarro, E.: A multi-agent system in ambient intelligence for the physical rehabilitation of older people. In: Bajo, J., Hernández, J.Z., Mathieu, P., Campbell, A., Fernández-Caballero, A., Moreno, M.N., Julián, V., Alonso-Betanzos, A., Jiménez-López, M.D., Botti, V. (eds.) Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability. AISC, vol. 372, pp. 113–123. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19629-9_13

    Chapter  Google Scholar 

  30. Mesa, I., Sanchez, E., Diaz, J., Toro, C., Artetxe, A.: Gocardio: a novel approach for mobility in cardiac monitoring. InImpact: J. Innov. Impact 6(1), 110 (2016)

    Google Scholar 

  31. Teruel, M.A., Navarro, E., González, P.: Towards an awareness interpretation for physical and cognitive rehabilitation systems. In: García, C.R., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds.) UCAmI 2016. LNCS, vol. 10069, pp. 121–132. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48746-5_13

    Chapter  Google Scholar 

  32. Felisberto, F., Costa, N., Fdez-Riverola, F., Pereira, A.: Unobstructive body area networks (ban) for efficient movement monitoring. Sensors 12(9), 12473–12488 (2012)

    Article  Google Scholar 

  33. Rohling, M.L., Faust, M.E., Beverly, B., Demakis, G.: Effectiveness of cognitive rehabilitation following acquired brain injury: a meta-analytic re-examination of cicerone et al’.s (2000, 2005) systematic reviews. Neuropsychology 23(1), 20 (2009)

    Article  Google Scholar 

  34. Roda, C., Rodríguez, A.C., López-Jaquero, V., Navarro, E., González, P.: A multi-agent system for acquired brain injury rehabilitation in ambient intelligence environments. Neurocomputing 231, 11–18 (2017). https://doi.org/10.1016/j.neucom.2016.04.066

    Article  Google Scholar 

  35. Li, C., Rusák, Z., Horváth, I., Ji, L.: Validation of the reasoning of an entry-level cyber-physical stroke rehabilitation system equipped with engagement enhancing capabilities. Eng. Appl. Artif. Intell. 56, 185–199 (2016)

    Article  Google Scholar 

  36. Su, C.-J., Peng, C.W.: Multi-agent ontology-based web 2.0 platform for medical rehabilitation. Expert Syst. Appl. 39(12), 10311–10323 (2012)

    Article  Google Scholar 

  37. Brugués, A., Bromuri, S., Barry, M., Del Toro, Ó.J., Mazurkiewicz, M.R., Kardas, P., Pegueroles, J., Schumacher, M.: Processing diabetes mellitus composite events in magpie. J. Med. Syst. 40(2), 1–15 (2016)

    Article  Google Scholar 

  38. Liao, J., Hu, C., Guan, G., Meng, M.Q.-H.: An extensible telemonitoring architecture based on mobile agent method. In: 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1537–1542. IEEE (2009)

    Google Scholar 

  39. Lai, J.C.K., Woo, J., Hui, E., Chan, W.M.: Telerehabilitation a new model for community-based stroke rehabilitation. J. Telemedicine Telecare 10(4), 199–205 (2004)

    Article  Google Scholar 

  40. Amatya, B., Galea, M.P., Kesselring, J., Khan, F.: Effectiveness of telerehabilitation interventions in persons with multiple sclerosis: a systematic review. Multiple Sclerosis Relat. Disord. 4(4), 358–369 (2015)

    Article  Google Scholar 

  41. Beny, L., Griesmar, R.: Device for producing continuous passive motion. US Patent 6,325,770, 4 December 2001

    Google Scholar 

  42. Schein, R.M., Schmeler, M.R., Saptono, A., Brienza, D.: Patient satisfaction with telerehabilitation assessments for wheeled mobility and seating. Assistive Technol. 22(4), 215–222 (2010)

    Article  Google Scholar 

  43. Calvaresi, D., Sernani, P., Marinoni, M., Claudi, A., Balsini, A., Dragoni, A.F., Buttazzo, G.: A framework based on real-time OS and multi-agents for intelligent autonomous robot competitions. In: 2016 11th IEEE Symposium on Industrial Embedded Systems (SIES), pp. 1–10, May 2016

    Google Scholar 

  44. Bellifemine, F.L., Caire, G., Greenwood, D.: Developing multi-agent systems with JADE, vol. 7. Wiley, Chichester (2007)

    Book  Google Scholar 

  45. ACL Fipa. Fipa acl message structure specification. Foundation for Intelligent Physical Agents (2002). http://www.fipa.org/specs/fipa00061/SC00061G.html. 30 June 2004

  46. Evidence. Erika enterprise rtos. http://www.evidence.eu.com. Accessed September 2017

  47. Calvaresi, D., Marinoni, M., Sturm, A., Schumacher, M., Buttazzo, G.: The challenge of real-time multi-agent systems for enabling IoT and CPS. In: Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence (WI 2017), August 2017

    Google Scholar 

  48. JADE - Programmer Manual. http://jade.tilab.com/doc/programmersguide.pdf. Accessed 15 May 2017

  49. Buttazzo, G.: Hard real-time computing systems: predictable scheduling algorithms and applications, vol. 24. Springer Science & Business Media, Berlin (2011). https://doi.org/10.1007/978-1-4614-0676-1

    MATH  Google Scholar 

  50. Pardo-Castellote, G.: Omg data-distribution service: architectural overview. In: Distributed Computing Systems Workshops, pp. 200–206. IEEE (2003)

    Google Scholar 

  51. Gomez, C., Oller, J., Paradells, J.: Overview and evaluation of bluetooth low energy: an emerging low-power wireless technology. Sensors 12(9), 11734–11753 (2012)

    Article  Google Scholar 

  52. Alliance, Z., et al.: Zigbee specification (2006)

    Google Scholar 

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Acknowledgements

The authors wish to thank the contribution of the COST Action IC1303 - Architectures, Algorithms and Platforms for Enhanced Living Environments (AAPELE).

Author information

Authors and Affiliations

  1. Scuola Superiore Sant’Anna, Pisa, Italy

    Davide Calvaresi, Mauro Marinoni & Giorgio Buttazzo

  2. University of Applied Sciences Western Switzerland, Sierre, Switzerland

    Davide Calvaresi & Michael Schumacher

  3. Università Politecnica delle Marche, Ancona, Italy

    Roger Hilfiker & Aldo F. Dragoni

Authors
  1. Davide Calvaresi
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  2. Michael Schumacher
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  3. Mauro Marinoni
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  4. Roger Hilfiker
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  5. Aldo F. Dragoni
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  6. Giorgio Buttazzo
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Corresponding author

Correspondence to Davide Calvaresi .

Editor information

Editors and Affiliations

  1. University of Bologna, Cesena, Italy

    Sara Montagna

  2. University of Coimbra, Coimbra, Portugal

    Pedro Henriques Abreu

  3. Université de Sherbrooke, Sherbrooke, Québec, Canada

    Sylvain Giroux

  4. University of Applied Sciences of Western Switzerland, Delémont, Switzerland

    Michael Ignaz Schumacher

A Questionnaire

A Questionnaire

  1. (1)

    Which human joints and limbs are your (physiotherapists’) primary interest?

  2. (2)

    What are the most typical causes/conditions? (e.g., pre-post-surgical, post-stroke, or just aging-related)

Concerning the joint-limbs, you mentioned in the first question:

  1. (3)

    How are they treated along the four phases (acute, subacute, chronic, and maintenance)?

  2. (4)

    Which body parts are involved in the rehabilitation practices?

  3. (5)

    Which body parts must be (or should be) monitored?

Concerning the previous answers:

  1. (6)

    Generally, and in your department, which are the most performed/required rehabilitative practices? (e.g., per body part - type & n. Of test)

  2. (7)

    Are they more frequently performed in ambulatory/hospital or a home/home-like environment?

  3. (8)

    In such practices, what is possible to observe? (e.g., extension, flexion, n. of repetitions, punctual accuracy)

  4. (9)

    In such practices, what is not possible to observe? (e.g., pain, fatigue, accurate evolution trend)

  5. (10)

    In such practices, what should and what shouldn’t the patient do? (e.g., regarding position, execution-speed)

  6. (11)

    What are the most common errors typically performed by the patients? (e.g., compensation)

  7. (12)

    What are the most common errors typically performed by the physiotherapists? (e.g., misreadings)

  8. (13)

    What are the (human) patient limits (what should they perceive or understand, but cannot)?

  9. (14)

    What are the (human) physiotherapist limits (what would you like, but you cannot perceive or understand)?

  10. (15)

    Concerning the technological research, what do you feel is missing and needs to be implemented?

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Calvaresi, D., Schumacher, M., Marinoni, M., Hilfiker, R., Dragoni, A.F., Buttazzo, G. (2017). Agent-Based Systems for Telerehabilitation: Strengths, Limitations and Future Challenges. In: Montagna, S., Abreu, P., Giroux, S., Schumacher, M. (eds) Agents and Multi-Agent Systems for Health Care. A2HC AHEALTH 2017 2017. Lecture Notes in Computer Science(), vol 10685. Springer, Cham. https://doi.org/10.1007/978-3-319-70887-4_1

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