Objective: To evaluate the reliability of technological devices for phenotype definition and rehabilitative treatment tailoring of patients affected by Functional Movement Disorders (FMDs)
Background: FMDs may present with a combination of phenotypes such as tremor, dystonia, weakness or postural/ gait disorders; however, their characterization is still incomplete and difficult: we aimed to describe and cluster FMDs phenotypic patterns with the aid of a technological approach including augmented or immersive virtual reality (AR/IVR), in the setting of an intensive rehabilitation program
Method: A dynamic and comprehensive database of all FMD patients from our centers were set up. It uses multiple assessment tools, including the Simplified FMDs Rating Scale (S-FMDRS) and the Clinical Global Impression (CGI). We performed an individualized instrumental assessment in relation to the main patient’s disorder, including Kinematic Analysis of gait (optoelectronic systems, multi-sensor instrumented treadmill) or upper limbs function, Instrumental Analysis of the Articulation of the Voice, and Balance assessment through AR/IVR systems
Results: Starting from 2021, 64 patients have been recruited (74%F/26%M; mean age 46.7±15.5 Y), according to Gupta e Lang 2009 criteria. 7.8 % (n=5) had a neurological diagnosis (mainly parkinsonism or dystonia), while 92.2 % (n=59) had no neurological comorbidity. 39.1% (n=25) presented gait disorders (akinesia, ataxia or dyssynergia), 28.1% (n=18) fixed or mobile limb dystonia, 9.4% (n=6) oromandibular dystonia, 14.1% (n=9) hyposthenic/dysfunctional hemi-syndrome, 20.3% (n=13) mono- or para-paresis and 7.8% (n=5) tremor. 67.2 % of the patients (n=43) performed movement analysis. 14.1 % of the patients (n=9) did not obtain benefits from the rehabilitation, while 86.0 % (n=55) obtained a temporary or definitive benefit, 15 among them obtained a full recovery or a dramatic reduction of symptoms. Technical assessments strongly eased the clinical decoding of patients’ FMDs improving the individual rehabilitation project
Conclusion: Instrumental assessment and technological rehabilitation may pave the way to a deeper understanding of neural mechanisms behind FMDs, permitting also the identification of homogeneous groups of patients and of reliable predictors of outcome, in order to develop more specific rehabilitation programs
To cite this abstract in AMA style:A. Torquati, G. Fidenzi, LG. Santilio, AE. Elia, N. Golfré Andreasi, G. Devigili, R. Cilia, F. Cosignani, BNG. Conti, P. Amami, S. Piacentini, S. Prioni, R. Eleopra, LM. Romito. Technological Approach to Phenotypical Characterization of Functional Movement Disorders [abstract]. Mov Disord. 2023; 38 (suppl 1). https://www.mdsabstracts.org/abstract/technological-approach-to-phenotypical-characterization-of-functional-movement-disorders/. Accessed September 25, 2023.
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MDS Abstracts - https://www.mdsabstracts.org/abstract/technological-approach-to-phenotypical-characterization-of-functional-movement-disorders/