Speed-Interactive Treadmill Training Using Smartphone-Based Motion Tracking Technology Improves Gait in Stroke Patients

2017 ◽  
Vol 49 (6) ◽  
pp. 675-685 ◽  
Author(s):  
Junyoung Lee ◽  
Kyeongjin Lee ◽  
Changho Song
Keyword(s):  
Motion Tracking ◽  
Treadmill Training ◽  
Stroke Patients ◽  
Tracking Technology

Poster 82 Robot-Assisted Treadmill Training during Rehabilitation of Stroke Patients

2011 ◽  
Vol 92 (10) ◽  
pp. 1716
Author(s):  
Michiel van Nunen ◽  
Karin Gerrits ◽  
Thomas Janssen ◽  
Arnold de Haan
Keyword(s):  
Treadmill Training ◽  
Stroke Patients ◽  
Robot Assisted

scholarly journals Design and Analysis of Cloud Upper Limb Rehabilitation System Based on Motion Tracking for Post-Stroke Patients

2019 ◽  
Vol 9 (8) ◽  
pp. 1620 ◽  
Author(s):  
Bai ◽  
Song ◽  
Li
Keyword(s):  
Upper Limb ◽  
Motion Tracking ◽  
Stroke Patients ◽  
Mean Velocity ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Post Stroke ◽  
Reachable Workspace ◽  
Rehabilitation System ◽  
Limb Rehabilitation

In order to improve the convenience and practicability of home rehabilitation training for post-stroke patients, this paper presents a cloud-based upper limb rehabilitation system based on motion tracking. A 3-dimensional reachable workspace virtual game (3D-RWVG) was developed to achieve meaningful home rehabilitation training. Five movements were selected as the criteria for rehabilitation assessment. Analysis was undertaken of the upper limb performance parameters: relative surface area (RSA), mean velocity (MV), logarithm of dimensionless jerk (LJ) and logarithm of curvature (LC). A two-headed convolutional neural network (TCNN) model was established for the assessment. The experiment was carried out in the hospital. The results show that the RSA, MV, LC and LJ could reflect the upper limb motor function intuitively from the graphs. The accuracy of the TCNN models is 92.6%, 80%, 89.5%, 85.1% and 87.5%, respectively. A therapist could check patient training and assessment information through the cloud database and make a diagnosis. The system can realize home rehabilitation training and assessment without the supervision of a therapist, and has the potential to become an effective home rehabilitation system.

Robot-assisted Treadmill Training During Rehabilitation of Stroke Patients

2010 ◽  
Vol 42 ◽  
pp. 733
Author(s):  
Michiel van Nunen ◽  
Thomas W. Janssen ◽  
Manin H. Konijnenbelt ◽  
Arnold de Haan ◽  
Karin H. Gerrits
Keyword(s):  
Treadmill Training ◽  
Stroke Patients ◽  
Robot Assisted
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