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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Variables Results Age, years a In our study, the recording of FMA using Kinect was conducted in the hospital with the supervision of a therapist. Assessing upper extremity motor function in practice of virtual activities of daily living. One occupational therapist with two-year experience in the FMA test did the evaluations. Measurements of acute cerebral mryer Neurorehabil Neural Repair ; FMA scoring rugl Kinect has potential as valid assessment tool for motor function after stroke in the home-based rehabilitation setting.

Retrieved from ” meyerr Experimental data for each assessment were collected from 41 subjects. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Jerky scores during the motion for flexion synergy in FMA were used for analysis. This may be useful in the setting of unsupervised home-based rehabilitation.

Duration is the length of the clipped data. 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.

Among the 33 items for UE evaluation, 13 were selected for Kinect motion data recording: Automated assessment of upper extremity movement impairment due to stroke. Classifications for impairment severity have been proposed based on FMA Total motor scores out of points: Demographic and clinical characteristics are summarized in Table 1.


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It takes approximately minutes to administer the total FMA. Functional tasks are not incorporated into the evaluation. Functional assessment tools are essential to monitor recovery and provide current function-based brunsntrom.

Fugl-Meyer Assessment of sensorimotor function

But, many items place a time burden on the assessor and patients. Authors have also no competing interests relating to employment, consultancy, patents, products in development or modified products along with this patent. Although we used the data from 41 stroke patients with various motor impairments, decrease of the imbalance by collecting more data sets and adoption of the above techniques could help increase prediction accuracies.

Physiopedia is not a substitute for professional advice or expert medical services from a qualified healthcare provider. Gait quality assessment using self-organising artificial neural networks.

Fugl-Meyer Assessment of sensorimotor function – Wikipedia

Furthermore, use of a cloud computing system with machine learning ability, such as Microsoft Azure ML, Amazon Machine Learning or IBM Watson Analytics, will facilitate develop of a prediction model capable of self-learning whenever new patient data is uploaded, and to predict FMA score using the model in the absence of a specialist. Kinect is a relatively inexpensive depth-sensing camera and no additional space and devices are required.

Jerk t is an 18 dimensional vector because subject motion data has 18 variables six joint x three dimension. If the resolution for the hand during full-body tracking with Kinect is increased in the future, the prediction accuracy for items including information on forearm rotation are expected to improve and the FMA items excluded in this study can be added.

The Fugl-Meyer scale has only three levels of assessment for each item. The movement of the joint center was used for the Jerky motion analysis. The content on or accessible through Physiopedia is for informational purposes only.

To properly classify motion patterns, features must be extracted from the captured motion data, which contains the positional information of every upper limb joint.

Fugl-Meyer Assessment of Motor Recovery after Stroke – Physiopedia

Thirteen of 33 items were selected for upper extremity motor FMA. The Fugl-Meyer assessment of motor recovery after stroke: Support Center Support Center. Development and validation of a short form of brunnsyrom Fugl-Meyer motor scale in patients with stroke.


Movement Therapy in Hemiplegia: Outpatient rehabilitation among stroke survivors—21 States and the District of Columbia, Results Characteristics of the patients Among 44 patients who agreed to participate, 41 completed the FMA.

Therefore, different numbers of principal components were used to achieve the best accuracy for each assessment item.

One is the occlusion of the body part during tracking by Kinect. Therefore, a majority of patients get an intermediate score in most items, and remain tedt for a long time.

Data were stored sequentially with time for the UE joint positions comprising 31 variables including time, and positions of the head, shoulder center, shoulder, elbow, wrist and hand. Neurorehabilitation and Neural Repair.

The five domains assessed by Fugl-Meyer scale are:. One of the solutions for the occlusion problem is using multiple Kinect Sensors, but this may be associated with increased cost. Views Read Edit View history. A supervised learning approach for imbalanced data sets. 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.

Fugl-Meyer was particularly influenced by the paper authored by Thomas Twitchell, titled The Restoration of Motor Functioning Following Hemiplegia in Man [8] and observations on post-stroke patients by Signe Brunnstrom. Contents Editors Categories Share Cite. To match the coordinates of both arms for machine learning, the right side data was mirrored to the left side based on the sagittal plane of the subject.

A home-based virtual rehabilitation system could be a useful alternative for conventional rehabilitation to overcome barriers for outpatient rehabilitation in stroke patients, considering its low cost and greater accessibility.

Introduction Stroke is a leading cause of disabilities worldwide[ 1 ] and hemiplegia is the most common impairment after stroke, [ 2 ] resulting in upper extremity UE dysfunction.