Grasps Recognition and Evaluation of Stroke Patients for Supporting Rehabilitation Therapy

You will need to ask your doctor which of these options are available in their therapy department. Getting your hand working is one of the most difficult and if you are not given a stroke protocol for it then it is likely you will not recover it very well.
http://scholar.google.com/scholar_url?hl=en&q=http://downloads.hindawi.com/journals/bmri/aip/318016.pdf&sa=X&scisig=AAGBfm0I7DYEHilFRNZsk06OR1XSymlMEg&oi=scholaralrt
1 Adaptive Systems Research Group at the School of Computer Science, University of Hertfordshire,
Hatfield, Hertfordshire, AL10 9AB, UK (b.leon@herts.ac.uk, a.basteris@herts.ac.uk,
f.amirabdollahian2@herts.ac.uk)
2 IRCCS San Raffaele Pisana, Via di Val Cannuta 247, 00166 Roma, Italy
(francesco.infarinato@sanraffaele.it, patrizio.sale@gmail.com)
3Roessingh Research and Development, Roessinghsbleekweg 33b 7522 AH Enschede the
Netherlands(s.nijenhuis@rrd.nl,g.prange@rrd.nl)
Correspondence should be addressed to Beatriz Leon; b.leon@herts.ac.uk
Abstract— Stroke survivors often suffer severe impairments on their wrist and hand. Robot-mediated
rehabilitation techniques have been proposed as a way to enhance conventional therapy, based on intensive
repeated movements. Amongst the set of activities of daily living, grasping is one of the most recurrent. In
the context of home-based rehabilitation, our aim is to incorporate the detection of different grasps in the
machine-mediated rehabilitation framework so that they can be incorporated into interactive therapeutic
games. In this study, we developed and tested a method based on support vector machines for recognizing
various grasp postures wearing a passive exoskeleton for hand and wrist rehabilitation after stroke. The
experiment was conducted with ten healthy subjects and eight stroke patients performing the grasping
gestures. The method was tested in terms of accuracy and robustness with respect to inter-subjects'
variability and differences between different grasps. Our results show reliable recognition while also
indicating that the accuracy of recognition can be used to assess the ability of the patients to consistently
repeat the gestures. Additionally, a grasp quality measure was proposed to measure the capabilities of the
stroke patients to perform grasp postures in a similar way than healthy people. These two measures can be
potentially used as complementary measures to other upper limb motion tests.