An Open and Extensible Data Acquisition and Processing Platform for Rehabilitation Applications

Recently we witnessed a great deal of progress in the field of medicine, as well as treatments that improve the patient therapy and care. However, physiotherapy and rehabilitation fields still face the challenges of treating patients in remote regions. Considering that, developing a data acquisition and processing platform that collects data of rehabilitation movements at home can play a key role in the success of a patient’s recovery process. The designed system is composed of three main parts: wearable sensor capable of collecting movement data with 3 axial accelerometer, gyroscope and magnetometer sensors, central hub for processing and a cloud system which is used as a link between the therapist and patient. The system was tested for purpose of monitoring rehabilitation exercises usually done during recovery from an elbow fracture. Experimental results have shown that the system presented in this paper gives successful results for rehabilitation applications.

[1]  Robert Steele,et al.  The Quantified Self and Physical Therapy: The Application of Motion Sensing Technologies , 2017, ICCDA '17.

[2]  Joseph Finkelstein,et al.  Home-based physical telerehabilitation in patients with multiple sclerosis: a pilot study. , 2008, Journal of rehabilitation research and development.

[3]  Daniel Roggen,et al.  Poster: BlueSense - Designing an extensible platform for wearable motion sensing, sensor research and IoT applications , 2018, EWSN.

[4]  Krestina L. Amon,et al.  Interdisciplinary eHealth for the care of people living with traumatic brain injury: A systematic review , 2017, Brain injury.

[5]  Andrea Turolla,et al.  Telerehabilitation and recovery of motor function: a systematic review and meta-analysis , 2015, Journal of telemedicine and telecare.

[6]  Antonio Miguel Cruz,et al.  What factors determine therapists’ acceptance of new technologies for rehabilitation – a study using the Unified Theory of Acceptance and Use of Technology (UTAUT) , 2015, Disability and rehabilitation.

[7]  Pedro Macedo,et al.  A Telerehabilitation System based on Wireless Motion Capture Sensors , 2014, PhyCS.

[8]  Kin Fun Li,et al.  Motion Tracking and Learning in Telerehabilitation Applications , 2012, 2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications.

[9]  Shyamal Patel,et al.  A review of wearable sensors and systems with application in rehabilitation , 2012, Journal of NeuroEngineering and Rehabilitation.

[10]  S. Nadeau,et al.  Patient Satisfaction with In-Home Telerehabilitation After Total Knee Arthroplasty: Results from a Randomized Controlled Trial. , 2017, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[11]  Yacine Challal,et al.  Wireless sensor networks for rehabilitation applications: Challenges and opportunities , 2013, J. Netw. Comput. Appl..

[12]  I-Ming Chen,et al.  A low cost wearable wireless sensing system for upper limb home rehabilitation , 2010, 2010 IEEE Conference on Robotics, Automation and Mechatronics.

[13]  Gozde Goncu-Berk,et al.  A Healthcare Wearable for Chronic Pain Management. Design of a Smart Glove for Rheumatoid Arthritis , 2017 .

[14]  Yu-Che Cheng,et al.  Using MEMS-based inertial sensor with ankle foot orthosis for telerehabilitation and its clinical evaluation in brain injuries and total knee replacement patients , 2016 .

[15]  Jesper Andersson,et al.  IoT-Enabled Physical Telerehabilitation Platform , 2017, 2017 IEEE International Conference on Software Architecture Workshops (ICSAW).

[16]  D. Theodoros,et al.  Telerehabilitation: current perspectives. , 2008, Studies in health technology and informatics.

[17]  Bruce H. Dobkin,et al.  A Rehabilitation-Internet-of-Things in the Home to Augment Motor Skills and Exercise Training , 2017, Neurorehabilitation and neural repair.

[18]  M. Schijven,et al.  Systematic Review on the Effects of Serious Games and Wearable Technology Used in Rehabilitation of Patients With Traumatic Bone and Soft Tissue Injuries. , 2017, Archives of physical medicine and rehabilitation.

[19]  Edin Golubovic,et al.  Internet of things-based system for physical rehabilitation monitoring , 2017, 2017 XXVI International Conference on Information, Communication and Automation Technologies (ICAT).

[20]  Vladimir Vujovic,et al.  Internet of Things Based E-health Systems: Ideas, Expectations and Concerns , 2017, Handbook of Large-Scale Distributed Computing in Smart Healthcare.

[21]  B. Dobkin Rehabilitation Strategies for Restorative Approaches After Stroke and Neurotrauma , 2016 .

[22]  Stefano Cagnoni,et al.  Design of a Wearable Sensing System for Human Motion Monitoring in Physical Rehabilitation , 2013, Sensors.

[23]  Huosheng Hu,et al.  Human motion tracking for rehabilitation - A survey , 2008, Biomed. Signal Process. Control..

[24]  A. Timmermans,et al.  Interactive wearable systems for upper body rehabilitation: a systematic review , 2017, Journal of NeuroEngineering and Rehabilitation.