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Actigraphic measurement of the upper limbs movements in acute stroke patients

BACKGROUND: Stroke units provide patients with a multiparametric monitoring of vital functions, while no instruments are actually available for a continuous monitoring of patients motor performance. Our aim was to develop an actigraphic index able both to identify the paretic limb and continuously m...

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Detalles Bibliográficos
Autores principales: Iacovelli, Chiara, Caliandro, Pietro, Rabuffetti, Marco, Padua, Luca, Simbolotti, Chiara, Reale, Giuseppe, Ferrarin, Maurizio, Rossini, Paolo Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894254/
https://www.ncbi.nlm.nih.gov/pubmed/31801569
http://dx.doi.org/10.1186/s12984-019-0603-z
Descripción
Sumario:BACKGROUND: Stroke units provide patients with a multiparametric monitoring of vital functions, while no instruments are actually available for a continuous monitoring of patients motor performance. Our aim was to develop an actigraphic index able both to identify the paretic limb and continuously monitor the motor performance of stroke patients in the stroke unit environment. METHODS: Twenty consecutive acute stroke patients (mean age 69.2 years SD 10.1, 8 males and 12 females) and 17 bed-restrained patients (mean age 70.5 years SD 7.3, 7 males and 10 females) hospitalized for orthopedic diseases of the lower limbs, but not experiencing neurological symptoms, were enrolled. This last group represented our control group. The motor activity of arms was recorded for 24 h using two programmable actigraphic systems showing off as wrist-worn watches. The firmware segmented the acquisition in epochs of 1 minute and for each epoch calculates two motor activity indices: MA(e1) (Epoch-related Motor Activity index) and MA(e2) (Epoch-related Motor Activity index 2). MA(e1) is defined as the standard deviation of the acceleration module and MA(e2) as the module of the standard deviation of acceleration components. To describe the 24 h motor performance of each limb, we calculated the mean value of MA(e1) and MA(e2) (respectively MA(1_24h) and MA(2_24h)). Then we obtained two Asymmetry Rate Indices: AR(1_24h) and AR(2_24h) to show the motor activity prevalence. AR(1_24h) refers to the asymmetry index between the values of MA(e1) of both arms and AR(2_24h) to MA(e2) values. The stroke patients were clinically evaluated by NIHSS at the beginning (NIHSS(T0)) and at the end (NIHSS(T1)) of the 24 h actigraphic recordings. RESULTS: Both MA(1_24h) and MA(2_24h) indices were smaller in the paretic than in the unaffected arm (respectively p = 0.004 and p = 0.004). AR(2_24h) showed a better capability (95% of paretic arms correctly identified, Phi Coefficient: 0.903) to discriminate the laterality of the clinical deficit than AR(1_24h) (85% of paretic arms correctly identified, Phi Coefficient: 0,698). We also found that AR(1_24h) did not differ between the two groups of patients while AR(2_24h) was greater in stroke patients than in controls and positively correlated with NIHSS total scores (r: 0.714, p < 0.001 for NIHSS, IC95%: 0.42–0.90) and with the sub-score relative to the paretic upper limb (r: 0.812, p < 0.001, IC95%: 0.62–0.96). CONCLUSIONS: Our data show that actigraphic monitoring of upper limbs can detect the laterality of the motor deficit and measure the clinical severity. These findings suggest that the above described actigraphic system could implement the existing multiparametric monitoring in stroke units.