Abstract.
This article proposes an innovative Smartphone-based architecture designed to assess, monitor, improve and train sensorimotor abilities at home. This system comprises inertial sensors to measure orientations, calculation units to analyze sensorimotor control abilities, visual, auditory and somatosensory systems to provide biofeedback to the user, screen display and headphones to provide test and/or training exercises instructions, and wireless connection to transmit data. We present two mobile applications, namely “iBalance” and “iProprio”, to illustrate concrete realization of such architecture in the case of at-home autonomous assessment and rehabilitation programs for balance and proprioceptive abilities. Our findings suggest that the present architecture system, which does not involve dedicated and specialized equipment, but which is entirely embedded on a Smartphone, could be a suitable solution for Ambient Assisted Living technologies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Islam, N., Want, R.: Smartphones: Past, Present, and Future. IEEE Pervasive Comput. 4, 89–92 (2014)
Gartner, Inc. (NYSE: IT), http://www.gartner.com/newsroom/id/2944819
Krishna, S., Boren, S.A., Balas, E.A.: Healthcare via cell phones: a systematic review. Telemed. J. E-Health. 15(3), 231–240 (2009)
Klasnja, P., Pratt, W.: Healthcare in the pocket: Mapping the space of mobile-phone health interventions. J. Biomed. Inform. 45(1), 184–198 (2012)
Swan, M.: Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Publ. Health. 6(2), 492–525 (2009)
Arif, M., Bilal, M., Kattan, A., Ahamed, S.I.: Better Physical Activity Classification using Smartphone Acceleration Sensor. J. Med. Syst. 38(9), 1–10 (2014)
Mitchell, E., Monaghan, D., O’Connor, N.E.: Classification of sporting activities using smartphone accelerometers. Sensors. 13(4), 5317–5337 (2013)
Habib, M.A., Mohktar, M.S., Kamaruzzaman, S.B., Lim, K.S., Pin, T.M., Ibrahim, F.: Smartphone-based solutions for fall detection and prevention: challenges and open issues. Sensors. 14(4), 7181–7208 (2014)
Lee, B.C., Kim, J., Chen, S., Sienko, K.H.: Cell phone based balance trainer. J.Neuroeng. Rehabil. 9(10) (2012)
Algar, L., Valdes, K.: Using smartphone applications as hand therapy interventions. J. Hand. Ther. 27, 254–257 (2014)
Zhu, R., Zhou, Z.: A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. IEEE Trans. Neural Syst. Rehabil. Eng 12(2), 295–302 (2004)
Timmermans, A., Saini, P., Willmann, R. D., Lanfermann, G., te Vrugt, J., Winter, S.: Home stroke rehabilitation for the upper limbs. In: Engineering in Medicine and Biology Society, EMBS 2007. 29th Annual International Conference of the IEEE, pp. 4015–4018. IEEE Press, Lyon (2007)
Giorgino, T., Tormene, P., Maggioni, G., Pistarini, C., Quaglini, S.: Wireless support to poststroke rehabilitation: myheart’s neurological rehabilitation concept. IEEE. T. Inf. Technol. B. 13(6), 1012–1018 (2009)
Valedo Therapy. (HOCOMA), http://www.valedotherapy.com/
Shin, S.H., du Ro, H., Lee, O.S., Oh, J.H., Kim, S.H.: Within-day reliability of shoulder range of motion measurement with a smartphone. Man. Ther. 17, 298–304 (2012)
Tousignant-Laflamme, Y., Boutin, N., Dion, A.M., Vallée, C.A.: Reliability and criterion validity of two applications of the iPhone to measure cervical range of motion in healthy participants. J Neuroeng Rehabil. 10, 69 (2013)
Jenny, J.Y.: Measurement of the knee flexion angle with a smartphone-application is precise and accurate. J Arthroplasty. 28, 784–787 (2013)
Peters, F.M., Greeff, R., Goldstein, N., Frey, C.T.: Improving acetabular cup orientation in total hip arthroplasty by using smartphone technology. J. Arthroplasty. 27(7), 1324–1330 (2012)
Jones, A., Sealey, R., Crowe, M., Gordon, S.: Concurrent validity and reliability of the Simple Goniometer iPhone app compared with the Universal Goniometer. Physiother. Theory. Pract. 0, 1–5 (2014)
Ockendon, M., Gilbert, R.E.: Validation of a novel smartphone accelerometer-based knee goniometer. J Knee Surg. 25, 341–345 (2012)
Franko, O.I., Bray, C., Newton, P.O.: Validation of a scoliometer smartphone app to assess scoliosis. J Pediatr Orthop. 32, 72–75 (2012)
Ege, T., Kose, O., Koca, K., Demiralp, B., Basbozkurt, M.: Use of the iPhone for radiographic evaluation of hallux valgus. Skeletal Radiol. 42, 269–273 (2013)
Ferriero, G., Sartorio, F., Foti, C., Primavera, D., Brigatti, E., Vercelli, S.: Reliability of a new application for smartphones (DrGoniometer) for elbow angle measurement. PM R. 3, 1153–1154 (2011)
Mitchell, K., Gutierrez, S.B., Sutton, S., Morton, S., Morgenthaler, A.: Reliability and validity of goniometric iPhone applications for the assessment of active shoulder external rotation. Physiother. Theory. Pract. 0, 1–5 (2014)
Milani, P., Coccetta, C.A., Rabini, A., Sciarra, T., Massazza, G., Ferriero, G.: A Review of Mobile Smartphone Applications for Body Position Measurement in Rehabilitation: A Focus on Goniometric Tools. PM&R. 6(11), 1038–1104 (2014)
Vuillerme, M., Fleury, A., Franco, C., Mourcou, Q., Diot, B.: Procédé et système pour la mesure, le suivi, le contrôle et la correction d’un mouvement ou d’une posture d’un utilisateur, Patent FR-1461233, 20/11/2014
Franco, C., Fleury, A., Guméry, P.Y., Diot, B., Demongeot, J., Vuillerme, N.: iBalance-ABF: a smartphone-based audio-biofeedback balance system. IEEE T. Bio-Med. Eng. 60(1), 211–215 (2013)
Mourcou, Q., Fleury, A., Dupuy, P., Diot, B., Franco, C., Vuillerme, N.: Wegoto: A Smartphone-based approach to assess and improve accessibility for wheelchair users. In: Engineering in Medicine and Biology Society (EMBC), 35th Annual International Conference of the IEEE, pp. 1194-1197. IEEE Press, Osaka (2013)
Lonn, J., Crenshaw, A.G., Djupsjobacka, M., Johansson, H.: Reliability of position sense testing assessed with a fully automated system. Clin. Physiol. 20, 30–37 (2000)
Bennell, K., Wee, E., Crossley, K., Stillman, B., Hodges, P.: Effects of experimentally-induced anterior knee pain on knee joint position sense in healthy individuals. J. Orthop. Res. 23, 46–53 (2005)
Rialle, V., Vuillerme, N., Franco, A.: Outline of a general framework for assessing e-health and gerontechnology applications: Axiological and diachronic dimensions. Gerontechnology 9(2), 245 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mourcou, Q., Fleury, A., Franco, C., Diot, B., Vuillerme, N. (2015). Smartphone-Based System for Sensorimotor Control Assessment, Monitoring, Improving and Training at Home. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-19312-0_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19311-3
Online ISBN: 978-3-319-19312-0
eBook Packages: Computer ScienceComputer Science (R0)