A Rehabilitation System for Post-operative Heart Surgery

Supervised exercise programs are an important aspect of the rehabilitation process of patients after heart surgery. A large number of factors must be taken into account before implementing a rehabilitation program. These mainly consist in the patient’s cognitive and physical capabilities after the operation and the expectations of recovery. A rehabilitation program should also be designed in relation to the stage of the healing process, with the therapist selecting the best sequence of exercises while taking into account the most appropriate effort level for the patient. This paper describes a customizable rehabilitation system for the early post-operative period, useful for the performance of an assessment of the patients, through an evaluation of their cognitive and motor abilities, and for a dynamic personalization of the therapy sessions focused on patient needs.

[1]  Flora Amato,et al.  Pattern-based orchestration and automatic verification of composite cloud services , 2016, Comput. Electr. Eng..

[2]  Huosheng Hu,et al.  SMART Rehabilitation: Implementation of ICT Platform to Support Home-Based Stroke Rehabilitation , 2007, HCI.

[3]  S Battersby,et al.  A low cost virtual reality system for home based rehabilitation of the arm following stroke: a randomised controlled feasibility trial , 2016, Clinical rehabilitation.

[4]  Maria Frucci,et al.  Touchless Target Selection Techniques for Wearable Augmented Reality Systems , 2015 .

[5]  Azrulhizam Shapi'i,et al.  A Game System for Cognitive Rehabilitation , 2015, BioMed research international.

[6]  Begoña García Zapirain,et al.  Kinect-based virtual game for motor and cognitive rehabilitation: a pilot study for older adults , 2014, PervasiveHealth.

[7]  Ashish S Shah,et al.  Lung injury and acute respiratory distress syndrome after cardiac surgery. , 2013, The Annals of thoracic surgery.

[8]  Shuyu Li,et al.  KINECT-BASED SKELETON-MATCHING FEEDBACK FOR MOTOR REHABILITATION: TRANSIENT PERFORMANCE EFFECT OF SHOULDER TRAINING , 2016 .

[9]  Le Li,et al.  Mechanism of Kinect-based virtual reality training for motor functional recovery of upper limbs after subacute stroke , 2013, Neural regeneration research.

[10]  Luigi Gallo,et al.  SmartCARE - An ICT Platform in the Domain of Stroke Pathology to Manage Rehabilitation Treatment and Telemonitoring at Home , 2016, IIMSS.

[11]  Giuseppe De Pietro,et al.  An Evolved eHealth Monitoring System for a Nuclear Medicine Department , 2011, 2011 Developments in E-systems Engineering.

[12]  Pedro Miguel Moreira,et al.  Natural user interfaces in serious games for rehabilitation , 2011, 6th Iberian Conference on Information Systems and Technologies (CISTI 2011).

[13]  Flora Amato,et al.  Exploiting Cloud and Workflow Patterns for the Analysis of Composite Cloud Services , 2017, Future Gener. Comput. Syst..

[14]  E. Hietanen,et al.  Cardiovascular responses to static exercise. , 1984, Scandinavian journal of work, environment & health.

[15]  Hossein Mousavi Hondori,et al.  A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation , 2014, Journal of medical engineering.

[16]  K Wildenthal,et al.  Static (isometric) exercise and the heart: physiological and clinical considerations. , 1974, Annual review of medicine.

[17]  Yelena Bogdanova,et al.  Computerized Cognitive Rehabilitation of Attention and Executive Function in Acquired Brain Injury: A Systematic Review , 2016, The Journal of head trauma rehabilitation.

[18]  Gennaro Della Vecchia,et al.  An infrastructure for smart hospitals , 2010, Multimedia Tools and Applications.

[19]  Ernesto Damiani,et al.  Comparative evaluation of methods for filtering Kinect depth data , 2014, Multimedia Tools and Applications.

[20]  Flora Amato,et al.  Semantic processing of multimedia data for e-government applications , 2016, J. Vis. Lang. Comput..

[21]  Flora Amato,et al.  A model driven approach to data privacy verification in E-Health systems , 2015, Trans. Data Priv..