The Fugl-Meyer Assessment (FMA) is a stroke-specific, performance-based following stroke and integrates Brunnstrom’s stages of motor recovery (Gladstone et al. This method of assessment reduces the time required to perform the test. The Fugl-Meyer Assessment (FMA) is a stroke-specific, performance-based NOTE: *The authors have no direct financial interest in any tools, tests or. program were developed for the total Fugl-Meyer motor and sensory assessments; inter-rater reliability was . CRC; and (3) competency testing in which videotapes were submit- . Brunnstrom, a person recovering from hemiparetic stroke.
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Assessing the degree of jerky motion using Kinect motion data The evaluation of the movement impairment in this study is based on the integrated squared jerk. The FMA scoring system using Kinect is valid and provides additional quantitative measures of motion smoothness in stroke patients. Acute treatment and long-term management of stroke in developing countries.
FMA score was calculated using principal component analysis and artificial neural network learning from the saved motion data.
Fugl-Meyer Assessment of sensorimotor function – Wikipedia
Traditional Brunnstrom recovery phase reveals the recovery of teet movement and emergence from synergistic movements. Movement Therapy in Hemiplegia: However, reflex activity is measured using 2 points only, with a score of 0 or 2 for absence and presence of reflex respectively. Data were saved in text file format.
Stroke is a leading cause of disabilities worldwide[ 1 ] and hemiplegia is the most common impairment after stroke, [ 2 ] resulting in brunsntrom extremity UE dysfunction. The purchase cost continues to decrease and camera performance continues to increase. An identical ANN structure i.
Acquisition of more patient data may increase the accuracy of this tool.
Fugl-Meyer Assessment FMA scale is an index to assess the sensorimotor impairment in individuals who have had stroke. One is the occlusion of the body mryer during tracking by Kinect. Contents Editors Fuhl Share Cite. Wearable sensors such as smart watches or wrist bands providing positional information can also be applied to solve the occlusion problem in our system.
This may be associated with barriers including costs, travel and limited use of public transportation due to disabilities.
Thus, the dimensions of input data depended on the assessments. Archived from the original on 24 September Most items in the UE motor domain are based on patient motion, although reflex or resistance has to be measured in a few items.
Fugl-Meyer Assessment of Motor Recovery after Stroke
Microsoft kinect sensor and its effect. Assessment of upper limb motor function in patients with multiple sclerosis using the Virtual Peg Insertion Test: In this manner, 8- to fold cross validations for each FMA item were performed.
Scoring is based on direct observation of performance. FMA scoring based on pattern recognition from Kinect data To predict a FMA score for each assessment item, an artificial neural network ANN among various pattern recognition algorithms was adopted. In further work, web-based uploading system of FMA Kinect motion data and real Brubnstrom data in various area could help acquire more patient data.
The overall process of this cross validation is described in more detail in the S3 Appendix. Patients were excluded if they were younger than 18 years of age; had serious medical complications requiring intensive care, such as pneumonia, urinary tract infection, acute coronary syndrome, inability to provide written informed consent and any other conditions that might interfere with participation.
A and B are the results from y-direction hand movements from UE numbers 10 and 61 during the motion for the flexion synergy item in FMA.
The prediction target of each item score 0, 1 or 2 was evaluated by one therapist. Full body gait analysis with Kinect. This article has been cited by other articles in PMC. This is an open access article distributed under the terms of the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
For the left arm, as an example, left hand, left wrist, left elbow, left shoulder, shoulder center and head joint position data were extracted.
Virtual home-based rehabilitation is an emerging area in stroke rehabilitation.