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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Data used for analysis are available from S1 File. However, Fugl-Meyer test still holds good, possibly because it follows brunnstroj hierarchical scoring system based on the level of difficulty in performing the tasks. Scoring is based on direct observation of performance. Views Read Edit View history. Author information Article notes Copyright and License information Disclaimer.
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.
The primary objectives of this study were to investigate whether Kinect motion data could be used to predict FMA score and whether predicted scores correlated with those measured by an experienced therapist in hemiplegic stroke patients.
Categorical variables are presented as frequencies percentages. Angles and distances between two joints for example, hand-shoulder, hand-head and elbow-head are computed from the original position data.
A zero score fugp given for the item if the subject cannot do the task.
However, the collected score data displayed a skewed distribution for some assessments. One occupational therapist with two-year experience in the FMA test did the evaluations. 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.
Data were saved in text file format. As both normal tst and hemiplegic side data were collected for each subject, 82 motion data captures in total were used tdst train the ANN model.
Normalized jerky data based on jerky motion analysis is also used as an additional feature. Results Characteristics of the patients Among 44 patients who agreed to participate, 41 completed the FMA.
This indicates that the number of items used in FMA using Kinect could feasibly be decreased, which would decrease the burden on patients and caregivers during assessment.
InAxel Fugl-Meyer noted that it is difficult to quantify the efficacy of different rehabilitation strategies because of the lack of a numerical scoring system. Duration is the length of the clipped data.
S2 Appendix Dimensionality reduction.
Fugl-Meyer Assessment of Motor Recovery after Stroke
He and his colleagues developed an assessment scale to overcome this problem. For the left arm, as an example, left hand, left wrist, left elbow, left shoulder, shoulder center and head joint position data were extracted. One occupational therapist assessed the motor FMA while recording upper extremity motion with Kinect.
Log jerky scores between hemiplegic and non-hemiplegic side were compared using paired t-test. Virtual home-based brrunnstrom is an emerging area in stroke brunnsrrom. One of the solutions for the occlusion problem is using multiple Kinect Sensors, but this may be associated with increased cost. To properly classify motion patterns, features must be extracted from the captured motion data, which contains the positional information brunnstroom every upper limb joint.
Subject motion was recorded simultaneously by Kinect for all 13 items. Open in a separate window. Recovery of upper limb dexterity in patients more than 1 year after stroke: Kinect motion data were saved as a separate file, which is upper-limb joint data including time.
Experimental data for each assessment were collected from 41 subjects. Retrieved from ” https: Patients were recruited from December to February fuhl Although two studies using manipulating devices with virtual realities showed modest correlations with conventional assessment tool, additional costs and space are required.
Fugl-Meyer Assessment of sensorimotor function – Wikipedia
Authors have also no competing interests relating to employment, consultancy, patents, products in development or modified products along with this patent.
The other three patients were not removed from the study during the FMA but refused to do the test after enrollment. The total possible scale score is Movement Therapy in Hemiplegia: 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 Fugl-Meyer scale has only three levels of assessment for each item. Gait quality assessment using self-organising artificial neural networks.
Fugl-Meyer Assessment of sensorimotor function
Scandinavian Journal of Rehabilitation Medicine. Evaluation of upper extremity reachable workspace using Kinect camera.
The individual in Fig 1 provided written informed consent as outlined in the PLOS consent form fjgl publish the picture. Wearable sensors such as smart watches or wrist bands providing positional information can also be applied to solve the occlusion problem in our system.
Fugl-Meyer was particularly influenced by the paper authored by Thomas Twitchell, titled The Restoration of Motor Functioning Following Hemiplegia in Man  and observations on post-stroke patients by Signe Brunnstrom. Physiopedia is not a substitute for professional advice or expert medical services from a qualified healthcare provider.