Maxence Bobin
ABSTRACT
This paper presents a solution to monitor and guide stroke patients during Activities of the Daily Living. It consists of a self-content smart glass that the patient can use to drink at different times of the day (water, coffee, etc.). The smart glass embeds a series of sensors that track in a transparent way the patients activity in everyday life (glass orientation, liquid level, target reaching and tremors). This solution allows therapists to monitor and analyze easily the Activities of the Daily Living of the patient in order to adapt the weekly rehabilitation sessions with suitable exercises. In addition, the smart glass embeds visual displays aimed at providing gestural guidance information when the patient do not use properly the glass. The paper presents the first prototype of the smart glass by highlighting the methodology adopted to design the software and hardware components of the platform.
- Craig Anderson, Sally Rubenach, Cliona Ni Mhurchu, Michael Clark, Carol Spencer, and Adrian Winsor. 2000. Home or hospital for stroke rehabilitation? Results of a randomized controlled trial I: Health outcomes at 6 months. Stroke 31, 5 (2000), 1024--1031.Google Scholar
Cross Ref
- Irene Aprile, Marco Rabuffetti, Luca Padua, Enrica Di Sipio, Chiara Simbolotti, and Maurizio Ferrarin. 2014. Kinematic analysis of the upper limb motor strategies in stroke patients as a tool towards advanced neurorehabilitation strategies: a preliminary study. BioMed research international 2014 (2014).Google Scholar
- Naveen Bagalkot, Elena Nazzi, and Tomas Sokoler. 2010. Facilitating continuity: exploring the role of digital technology in physical rehabilitation. In Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries. ACM, 42--51. Google ScholarDigital Library
- Janet H Carr, Roberta B Shepherd, Lena Nordholm, and Denise Lynne. 1985. Investigation of a new motor assessment scale for stroke patients. Physical therapy 65, 2 (1985), 175--180.Google Scholar
- Sophie Dethy, André Luxen, Luc M Bidaut, and Serge Goldman. 1993. Hemibody tremor related to stroke. Stroke 24, 12 (1993), 2094--2096.Google ScholarCross Ref
- A Ferbert and M Gerwig. 1993. Tremor due to stroke. Movement disorders 8, 2 (1993), 179--182.Google Scholar
- Axel R Fugl-Meyer, L Jääskö, Ingegerd Leyman, Sigyn Olsson, and Solveig Steglind. 1974. The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scandinavian journal of rehabilitation medicine 7, 1 (1974), 13--31.Google Scholar
- George D Fulk and Edward Sazonov. 2011. Using sensors to measure activity in people with stroke. Topics in stroke rehabilitation 18, 6 (2011), 746--757.Google Scholar
- B Gialanella, R Santoro, and C Ferlucci. 2013. Predicting outcome after stroke: the role of basic activities of daily living predicting outcome after stroke. European journal of physical and rehabilitation medicine 49, 5 (2013), 629--637.Google Scholar
- Alexandra Handley, Pippa Medcalf, Kate Hellier, and Dipankar Dutta. 2009. Movement disorders after stroke. Age and ageing 38, 3 (2009), 260--266.Google Scholar
- M Iosa, G Morone, A Fusco, M Bragoni, P Coiro, M Multari, V Venturiero, D De Angelis, L Pratesi, and S Paolucci. 2012. Seven capital devices for the future of stroke rehabilitation. Stroke research and treatment 2012 (2012).Google Scholar
- Anthony Kim and MF Golnaraghi. 2004. A quaternion-based orientation estimation algorithm using an inertial measurement unit. In Position Location and Navigation Symposium, 2004. PLANS 2004. IEEE, 268--272.Google ScholarCross Ref
- Jong Sung Kim. 1992. Delayed onset hand tremor caused by cerebral infarction. Stroke 23, 2 (1992), 292--294.Google ScholarCross Ref
- Jong S Kim. 2001. Delayed onset mixed involuntary movements after thalamic stroke. Brain 124, 2 (2001), 299--309.Google ScholarCross Ref
- S. Lehericy, S. Grand, P. Pollak, F. Poupon, J-F Le Bas, P. Limousin, P. Jedynak, C. Marsault, Y. Agid, and M. Vidailhet. 2001. Clinical characteristics and topography of lesions in movement disorders due to thalamic lesions. Neurology 57, 6 (2001), 1055--1066.Google ScholarCross Ref
- Margit Alt Murphy, Carin Willén, and Katharina S Sunnerhagen. 2011. Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass. Neurorehabilitation and neural repair 25, 1 (2011), 71--80.Google Scholar
- World Health Organization. 2002. World Health Report. Report. (2002). Retrieved December 29, 2015 from http://www.who.int/whr/2002/en/.Google Scholar
- Shanta Pandian and Kamal Narayan Arya. 2014. Stroke-related motor outcome measures: Do they quantify the neurophysiological aspects of upper extremity recovery? Journal of bodywork and movement therapies 18, 3 (2014), 412--423.Google ScholarCross Ref
- Jose A Rios and Elecia White. 2002. Fusion filter algorithm enhancements for a MEMS GPS/IMU. Crossbow Technology, Inc (2002), 1--12.Google Scholar
- Luisa Sartori, Elisa Straulino, Umberto Castiello, and Alessio Avenanti. 2011. How objects are grasped: the interplay between affordances and end-goals. PloS one 6, 9 (2011), e25203.Google ScholarCross Ref
- Kathryn A Sawner, Jeanne M LaVigne, and Signe Brunnstrom. 1992. Brunnstrom's movement therapy in hemiplegia: a neurophysiological approach. Lippincott.Google Scholar
- Juliana Schroeder and Ayelet Fishbach. 2015. How to motivate yourself and others? Intended and unintended consequences. Research in Organizational Behavior 35 (2015), 123--141.Google ScholarCross Ref
- Sharon Smaga. 2003a. ESSENTIAL TREMOR. American Family Physician 68, 8 (2003).Google Scholar
- Sharon Smaga. 2003b. Tremor-Problem-Oriented Diagnosis. American Family Physician 68 (2003), 1545--1552.Google Scholar
- Annick AA Timmermans, Henk AM Seelen, Richard D Willmann, Wilbert Bakx, Boris De Ruyter, Gerd Lanfermann, and Herman Kingma. 2009. Arm and hand skills: training preferences after stroke. Disability and rehabilitation 31, 16 (2009), 1344--1352.Google Scholar
Index Terms
- SyMPATHy: smart glass for monitoring and guiding stroke patients in a home-based context
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