Actigraphic Measurement of the Upper Limbs for the Prediction of Ischemic Stroke Prognosis: An Observational Study

Abstract

Background: It is often challenging to formulate a reliable prognosis for patients with acute ischemic stroke. The most accepted prognostic factors may not be sufficient to predict the recovery process. In this view, describing the evolution of motor deficits over time via sensors might be useful for strengthening the prognostic model. Our aim was to assess whether an actigraphic-based parameter (Asymmetry Rate Index for the 24 h period (AR2_24 h)) obtained in the acute stroke phase could be a predictor of a 90 d prognosis. Methods: In this observational study, we recorded and analyzed the 24 h upper limb movement asymmetry of 20 consecutive patients with acute ischemic stroke during their stay in a stroke unit. We recorded the motor activity of both arms using two programmable actigraphic systems positioned on patients’ wrists. We clinically evaluated the stroke patients by NIHSS in the acute phase and then assessed them across 90 days using the modified Rankin Scale (mRS). Results: We found that the AR2_24 h parameter positively correlates with the 90 d mRS (r = 0.69, p < 0.001). Moreover, we found that an AR2_24 h > 32% predicts a poorer outcome (90 d mRS > 2), with sensitivity = 100% and specificity = 89%. Conclusions: Sensor-based parameters might provide useful information for predicting ischemic stroke prognosis in the acute phase.

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ].…”

“…Variability of arm movement as reported in three studies [ 25 , 33 , 38 ] is also used to asses the quality of upper limb movement. Acceleration variability is usually calculated as the standard deviation of the acceleration norm , per 1 min epoch [ 33 ] or over the entire monitoring period [ 25 ].…”

“…Acceleration variability is usually calculated as the standard deviation of the acceleration norm , per 1 min epoch [ 33 ] or over the entire monitoring period [ 25 ]. Additionally, the norm of the standard deviation of the acceleration vector components , is used as another measure of acceleration variability that may be more sensitive to rotation movements [ 33 , 38 ]. Variation Ratio , both a variability and a symmetry outcome, is calculated over the total recording period [ 25 ], or for every 24 h [ 33 ] as the magnitude of AUL acceleration variability relative to the magnitude of UUL acceleration variability.…”

“…Sixteen studies compared sensor-based movement measures with clinical assessment tools [ 9 , 10 , 19 , 22 , 24 , 25 , 26 , 27 , 28 , 33 , 34 , 35 , 36 , 38 , 40 , 42 ]. All studies used Pearson or Spearman correlation tests to determine the relationships between sensor-based measures and clinical assessment scale scores, assuming a significance level of α = 0.05.…”