Hand Rehabilitation and Telemonitoring through Smart Toys

We describe here a platform for autonomous hand rehabilitation and telemonitoring of young patients. A toy embedding the electronics required to sense fingers pressure in different grasping modalities is the core element of this platform. The system has been realized following the user-centered design methodology taking into account stakeholder needs from start: clinicians require reliable measurements and the ability to get a picture remotely on rehabilitation progression; children have asked to interact with a pleasant and comfortable object that is easy to use, safe, and rewarding. These requirements are not antithetic, and considering both since the design phase has allowed the realization of a platform reliable to clinicians and keen to be used by young children.

[1]  Yurong Song,et al.  A Soft Robotic Glove for Hand Rehabilitation Using Pneumatic Actuators with Variable Stiffness , 2019, ICIRA.

[2]  Pier Luca Lanzi,et al.  Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames , 2016, Entertain. Comput..

[3]  Gian Franco Gensini,et al.  Value of Telemonitoring and Telemedicine in Heart Failure Management. , 2017, Cardiac failure review.

[4]  Linda Denehy,et al.  Validity of the Microsoft Kinect for assessment of postural control. , 2012, Gait & posture.

[5]  N. Alberto Borghese,et al.  A cloud-based platform for effective supervision of autonomous home rehabilitation through exer-games , 2018, 2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH).

[6]  Renato Mainetti,et al.  Hand Rehabilitation with Toys with Embedded Sensors , 2017 .

[7]  P. Langhorne,et al.  Does the Organization of Postacute Stroke Care Really Matter? , 2001, Stroke.

[8]  Arno H. A. Stienen,et al.  SCRIPT passive orthosis: design of interactive hand and wrist exoskeleton for rehabilitation at home after stroke , 2016, Autonomous Robots.

[9]  Won Hyuk Chang,et al.  Robot-assisted Therapy in Stroke Rehabilitation , 2013, Journal of stroke.

[10]  Pier Luca Lanzi,et al.  Intelligent Game Engine for Rehabilitation (IGER) , 2016, IEEE Transactions on Computational Intelligence and AI in Games.

[11]  Cecilia Sik-Lányi,et al.  Suitability of the Kinect Sensor and Leap Motion Controller—A Literature Review , 2019, Sensors.

[12]  W. Graham Richards,et al.  Art of electronics , 1983, Nature.

[13]  N. A. Borghese,et al.  Autocalibration of MEMS Accelerometer , 2006, 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings.

[14]  Martin J. Russell,et al.  Intelligent Assistive System Using Real-Time Action Recognition for Stroke Survivors , 2014, 2014 IEEE International Conference on Healthcare Informatics.

[15]  L. Richards,et al.  A Critical Review of Tools, Methods, and Clinical Utility for Grip Strength Measurement , 2017 .

[16]  Laehyun Kim,et al.  A rehabilitation device to improve the hand grasp function of stroke patients using a patient-driven approach , 2013, 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR).

[17]  D. Novák Using Leap Motion and Gamification to Facilitate and Encourage Rehabilitation for Hand Injuries : Leap Motion for Rehabilitation , 2015 .

[18]  David J. Hewson,et al.  Domo-Grip: functional evaluation and rehabilitation using grip force , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[19]  Jean-Yves Hogrel,et al.  Grip strength measured by high precision dynamometry in healthy subjects from 5 to 80 years , 2015, BMC Musculoskeletal Disorders.

[20]  N. A. Borghese,et al.  Videogame Based Neglect Rehabilitation: A Role for Spatial Remapping and Multisensory Integration? , 2013, Front. Hum. Neurosci..

[21]  R. Kizony,et al.  The use of the iPad for poststroke hand rehabilitation; A pilot study , 2013, 2013 International Conference on Virtual Rehabilitation (ICVR).

[22]  Jonas Beskow,et al.  Real-time labeling of non-rigid motion capture marker sets , 2017, Comput. Graph..

[23]  Pinhas Ben-Tzvi,et al.  Hand Rehabilitation Learning System With an Exoskeleton Robotic Glove , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[24]  Thomas Pintaric,et al.  SqueezeOrb: a low-cost pressure-sensitive user input device , 2008, VRST '08.

[25]  Markus Hessinger,et al.  An Anthropomorphic Soft Exosuit for Hand Rehabilitation , 2019, 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR).

[26]  Pier Paolo Valentini,et al.  Accuracy in fingertip tracking using Leap Motion Controller for interactive virtual applications , 2017 .

[27]  Manuel Pezzera,et al.  Approaches for increasing patient’s engagement and motivation in exer-games-based autonomous telerehabilitation , 2019, 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH).

[28]  H. Fardoun,et al.  Virtual Rehabilitation for Multiple Sclerosis Using a Kinect-Based System: Randomized Controlled Trial , 2014, JMIR serious games.

[29]  Rachel Proffitt,et al.  User-Centered Design of a Controller-Free Game for Hand Rehabilitation. , 2015, Games for health journal.

[30]  Christine L. MacKenzie,et al.  The Grasping Hand , 2011, The Grasping Hand.

[31]  Amy L. Parsons,et al.  Emotional Design: Why We Love (or Hate) Everyday Things , 2006 .

[32]  Andrew McDaid,et al.  Design and development of a glove for post-stroke hand rehabilitation , 2017, 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[33]  D. Norman Emotional design : why we love (or hate) everyday things , 2004 .

[34]  Khanjan Mehta,et al.  Leveraging design thinking to build sustainable mobile health systems , 2016, Journal of medical engineering & technology.

[35]  Brent Maundy,et al.  Strain Gauge Amplifier Circuits , 2013, IEEE Transactions on Instrumentation and Measurement.

[36]  Aray Kassenkhan,et al.  Gamification of Hand Rehabilitation Process Using Virtual Reality Tools: Using Leap Motion for Hand Rehabilitation , 2017, 2017 First IEEE International Conference on Robotic Computing (IRC).

[37]  Nancy Hazen,et al.  Action in Social Context: Perspectives On Early Development , 2013 .

[38]  P. Dario,et al.  Design and Development of a Sensorized Wireless Toy for Measuring Infants' Manual Actions , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Daniele Cafolla A personalized flexible exoskeleton for finger rehabilitation: a conceptual design , 2019 .

[40]  Dirk Reichardt,et al.  Digitizing the Hand Rehabilitation Using Serious Games Methodology with User-Centered Design Approach , 2016, 2016 International Conference on Computational Science and Computational Intelligence (CSCI).

[41]  Christian Krettek,et al.  Comparison of the Grip Strength Using the Martin-Vigorimeter and the JAMAR-Dynamometer: Establishment of Normal Values. , 2017, In vivo.

[42]  Rana Jaber,et al.  Design and validation of the Grip-ball for measurement of hand grip strength. , 2012, Medical engineering & physics.

[43]  Fu-Chan Wei,et al.  Thumb Reconstruction with Toe Transfer , 2010, Journal of Hand and Microsurgery.

[44]  P. Langhorne,et al.  Motor recovery after stroke: a systematic review , 2009, The Lancet Neurology.

[45]  Vukica Jovanovic,et al.  A Low-Cost Soft Robotic Hand Exoskeleton for Use in Therapy of Limited Hand–Motor Function , 2019, Applied Sciences.

[46]  Francesco Amenta,et al.  Telerehabilitation: Review of the State-of-the-Art and Areas of Application , 2017, JMIR rehabilitation and assistive technologies.

[47]  Kevin J Little,et al.  Congenital Anomalies of the Hand--Principles of Management. , 2016, The Orthopedic clinics of North America.

[48]  Carlos Eduardo Pereira,et al.  Load cells in force sensing analysis -- theory and a novel application , 2010, IEEE Instrumentation & Measurement Magazine.

[49]  Danielle Levac,et al.  A Tablet-Based Interactive Movement Tool for Pediatric Rehabilitation: Development and Preliminary Usability Evaluation , 2018, JMIR rehabilitation and assistive technologies.

[50]  Rafael Rieder,et al.  Motion Rehab AVE 3D: A VR-based exergame for post-stroke rehabilitation , 2017, Comput. Methods Programs Biomed..

[51]  Eling D. de Bruin,et al.  Rehabilitation at Home: A Comprehensive Technological Approach , 2014 .

[52]  Dan Mihai Ştefănescu Wheatstone Bridge - The Basic Circuit for Strain Gauge Force Transducers , 2011 .

[53]  Alberto Borboni,et al.  Gloreha - Hand robotic rehabilitation: design, mechanical model and experiments , 2016 .

[54]  S. Henderson,et al.  Motor skill development , 1985 .

[55]  Arantza Illarramendi,et al.  KiReS: A Kinect-based telerehabilitation system , 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013).