Abstract
The lack of success of tele-monitoring systems in non-clinical environments is mainly due to the difficulty experienced by common users to deal with them. In particular, for achieving a correct operation, the user is required to take care of a number of annoying details, such as wearing them correctly, putting them in operation, using them in a proper way, and transferring the acquired data to the medical center. In spite of the many technological advances concerning miniaturization, energy consumption reduction, and the availability of mobile devices, many things are still missing to make these technologies simple enough to be really usable by a broad population, and in particular by elderly people. To bridge this gap between users and devices, a smart software layer could automatically manage configuration, calibration, and data transfer without requiring the intervention of a formal caregiver. This paper describes the key features that should be implemented to simplify the needed initial calibration phase of sensing systems and to support the patient with a multimodal feedback throughout the execution of the exercises. A simple mobile application is also presented as a demonstrator of the advantages of the proposed solution.
This work has been partially suported by Telecom Italia under the grant agreement POR CRO FSE 20072013, SISTAG, no. 16.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Blackburn, J., Ribeiro, E.: Human motion recognition using isomap and dynamic time warping. In: Elgammal, A., Rosenhahn, B., Klette, R. (eds.) Human Motion 2007. LNCS, vol. 4814, pp. 285–298. Springer, Heidelberg (2007)
Buonocunto, P., Marinoni, M.: Tracking limbs motion using a wireless network of inertial measurement units. In: Proceedings of the 9th IEEE International Symposium on Industrial Embedded Systems (SIES 2014), Pisa, Italy, June 18-20 (2014)
Calvaresi, D., Claudi, A., Dragoni, A.F., Yu, E., Accattoli, D., Sernani, P.: A goal-oriented requirements engineering approach for the ambient assisted living domain. In: Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments, p. 20. ACM (2014)
Cardinaux, F., Bhowmik, D., Abhayaratne, C., Hawley, M.S.: Video based technology for ambient assisted living: A review of the literature. Journal of Ambient Intelligence and Smart Environments 3(3), 253–269 (2011)
Cesarini, D., Buonocunto, P., Marinoni, M., Buttazzo, G.: A telerehabilitation framework for lower-limb functional recovery. In: International Conference on Body Area Networks, BodyNets2014, London, UK, IEEE Computer Society (2014)
Cesarini, D., Hermann, T., Ungerechts, B.: A real-time auditory biofeedback system for sports swimming. In: Proc. of the Int’l Conf. on Auditory Display 2014, Sonification for Sports and Performance Workshop, NY, US (June 22, 2014)
Chang, Y.-J., Chen, S.-F., Huang, J.-D.: A kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities. Research in Developmental Disabilities 32(6), 2566–2570 (2011)
de Blok, B.M., de Greef, M.H., ten Hacken, N.H., Sprenger, S.R., Postema, K., Wempe, J.B.: The effects of a lifestyle physical activity counseling program with feedback of a pedometer during pulmonary rehabilitation in patients with copd: A pilot study. Patient Education and Counseling 61(1), 48–55 (2006)
Dejnabadi, H., Jolles, B., Aminian, K.: A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes. IEEE Transactions on Biomedical Engineering 52(8), 1478–1484 (2005)
Fong, D.T.-P., Chan, Y.-Y.: The use of wearable inertial motion sensors in human lower limb biomechanics studies: A systematic review. Sensors 10(12), 11556–11565 (2010)
Gietzelt, M., Wolf, K.-H., Marschollek, M., Haux, R.: Automatic self-calibration of body worn triaxial-accelerometers for application in healthcare. In: Second International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2008, pp. 177–180. IEEE (2008)
Hadjidj, A., Souil, M., Bouabdallah, A., Challal, Y., Owen, H.: Wireless sensor networks for rehabilitation applications: Challenges and opportunities. Journal of Network and Computer Applications 36(1), 1–15 (2013)
Kim, J., Yang, S., Gerla, M.: Stroketrack: wireless inertial motion tracking of human arms for stroke telerehabilitation. In: Proceedings of the First ACM Workshop on Mobile Systems, Applications, and Services for Healthcare, p. 4. ACM (2011)
Pawar, P., Jones, V., Van Beijnum, B.-J.F., Hermens, H.: A framework for the comparison of mobile patient monitoring systems. Journal of Biomedical Informatics 45(3), 544–556 (2012)
Rodger, M., Young, W., Craig, C.: Synthesis of walking sounds for alleviating gait disturbances in parkinson’s disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering 22(3), 543–548 (2014)
Roosink, M., Robitaille, N., McFadyen, B.J., Hébert, L.J., Jackson, P.L., Bouyer, L.J., Mercier, C.: Real-time modulation of visual feedback on human full-body movements in a virtual mirror: development and proof-of-concept. Journal of NeuroEngineering and Rehabilitation 12(1), 2 (2015)
Seel, T., Schauer, T., Raisch, J.: Joint axis and position estimation from inertial measurement data by exploiting kinematic constraints. In: 2012 IEEE Int’l Conf. on Control Applications (October 2012)
Sienko, K.H., Balkwill, M.D., Oddsson, L.I., Wall, C.: The effect of vibrotactile feedback on postural sway during locomotor activities. Journal of Neuroengineering and Rehabilitation 10(1), 93 (2013)
Sigrist, R., Rauter, G., Riener, R., Wolf, P.: Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychonomic Bulletin & Review 20(1), 21–53 (2013)
Torres, A.V., Kluckner, V., Franinovic, K.: Development of a sonification method to enhance gait rehabilitation. In: 4th Interactive Sonification Workshop Proceedings of ISon (2013)
Weenk, D., Van Beijnum, B.-J.F., Baten, C.T., Hermens, H.J., Veltink, P.H.: Automatic identification of inertial sensor placement on human body segments during walking. Journal of Neuroengineering and Rehabilitation 10(1), 31 (2013)
Windolf, M., Götzen, N., Morlock, M.: Systematic accuracy and precision analysis of video motion capturing systems—exemplified on the Vicon-460 system. Journal of Biomechanics 41(12), 2776–2780 (2008)
Zijlstra, A., Mancini, M., Chiari, L., Zijlstra, W.: Biofeedback for training balance and mobility tasks in older populations: A systematic review. J. Neuroeng. Rehabil. 7(1), 58 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Cesarini, D., Calvaresi, D., Marinoni, M., Buonocunto, P., Buttazzo, G. (2015). Simplifying Tele-rehabilitation Devices for Their Practical Use in Non-clinical Environments. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2015. Lecture Notes in Computer Science(), vol 9044. Springer, Cham. https://doi.org/10.1007/978-3-319-16480-9_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-16480-9_47
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16479-3
Online ISBN: 978-3-319-16480-9
eBook Packages: Computer ScienceComputer Science (R0)