+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Design and Test of a Closed-Loop FES System for Supporting Function of the Hemiparetic Hand Based on Automatic Detection using the Microsoft Kinect sensor

Design and Test of a Closed-Loop FES System for Supporting Function of the Hemiparetic Hand Based on Automatic Detection using the Microsoft Kinect sensor

IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(8): 1249-1256

This paper describes the design of a FES system automatically controlled in a closed loop using a Microsoft Kinect sensor, for assisting both cylindrical grasping and hand opening. The feasibility of the system was evaluated in real-time in stroke patients with hand function deficits. A hand function exercise was designed in which the subjects performed an arm and hand exercise in sitting position. The subject had to grasp one of two differently sized cylindrical objects and move it forward or backwards in the sagittal plane. This exercise was performed with each cylinder with and without FES support. Results showed that the stroke patients were able to perform up to 29% more successful grasps when they were assisted by FES. Moreover, the hand grasp-and-hold and hold-and-release durations were shorter for the smaller of the two cylinders. FES was appropriately timed in more than 95% of all trials indicating successful closed loop FES control. Future studies should incorporate options for assisting forward reaching in order to target a larger group of stroke patients.

Please choose payment method:

(PDF emailed within 0-6 h: $19.90)

Accession: 057580334

Download citation: RISBibTeXText

PMID: 27810829

DOI: 10.1109/tnsre.2016.2622160

Related references

Design and test of an automated version of the modified Jebsen test of hand function using Microsoft Kinect. Journal of Neuroengineering and Rehabilitation 14(1): 38, 2017

Design and test of a Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during training of upper limb movement. Medical and Biological Engineering and Computing 55(11): 1927-1935, 2017

Design and test of a novel closed-loop system that exploits the nociceptive withdrawal reflex for swing-phase support of the hemiparetic gait. IEEE Transactions on Bio-Medical Engineering 58(4): 960-970, 2011

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor. Sensors 18(3):, 2018

Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor. Medical Engineering and Physics 59: 63-69, 2018

Statistical analysis-based error models for the Microsoft Kinect(TM) depth sensor. Sensors 14(9): 17430-17450, 2014

SU-E-J-158: A Prototype of a Real-Time Respiratory Motion Monitoring System Using Microsoft Kinect Sensor. Medical Physics 39(6part8): 3689, 2012

Feasibility of a Customized, In-Home, Game-Based Stroke Exercise Program Using the Microsoft Kinect® Sensor. International Journal of Telerehabilitation 7(2): 23-34, 2015

Development and evaluation of low cost game-based balance rehabilitation tool using the Microsoft Kinect sensor. Conference Proceedings 2011: 1831-1834, 2011

Retraining function in people with Parkinson's disease using the Microsoft kinect: game design and pilot testing. Journal of Neuroengineering and Rehabilitation 11: 60, 2014

Developing movement recognition application with the use of Shimmer sensor and Microsoft Kinect sensor. Studies in Health Technology and Informatics 217: 767-772, 2015

A depth-based fall detection system using a Kinect® sensor. Sensors 14(2): 2756-2775, 2014

An Egg Volume Measurement System Based on the Microsoft Kinect. Sensors 18(8):, 2018

Automatic measurement of physical mobility in Get-Up-and-Go Test using Kinect sensor. Conference Proceedings 2014: 3492-3495, 2014

Microsoft Kinect-based Continuous Performance Test: An Objective Attention Deficit Hyperactivity Disorder Assessment. Journal of Medical Internet Research 19(3): E79, 2017