title: Wireless accelerometry is feasible in acute monitoring of upper limb motor recovery after ischemic stroke.
abstract: BACKGROUND
  Clinical deterioration in the acute stage of ischemic stroke powerfully predicts outcome and may serve as a marker for urgent intervention. However, accurate monitoring of acute stroke patients is hampered by the lack of validated continuous monitoring devices. We sought to assess the use of wireless accelerometry in this setting, hypothesizing that stroke patients would have a greater difference in movement between upper limbs than controls and that the magnitude of correlation between upper limb movements would be negatively associated with the National Institutes of Health Stroke Scale (NIHSS) score.
  
  
  METHODS
  In this pilot study, 20 patients with acute ischemic stroke and unilateral upper limb weakness and 10 controls were recruited from a comprehensive stroke centre. All subjects were fitted with two 3-axis accelerometers and underwent 24 h of continuous accelerometry recording of upper limb movements and repeat NIHSS assessments. The intra-class correlation coefficient (ICC), assessing the similarity (or otherwise) of spontaneous movements in each arm was calculated. The association between NIHSS (total and motor subset scores) and the magnitude of ICC was estimated by Spearman's rank correlation, receiver-operating characteristic curve analysis was performed and the optimal diagnostic threshold value of ICC was calculated.
  
  
  RESULTS
  The magnitude of the ICC was significantly associated with the baseline NIHSS score (p = 0.02) and non-significantly associated with the baseline NIHSS motor score (p = 0.08). At the optimal diagnostic threshold of ICC magnitude = 0.7, wireless accelerometry distinguished patients from controls with a sensitivity of 0.95, a specificity of 0.6 and a diagnostic odds ratio of 28.5.
  
  
  CONCLUSIONS
  The wireless accelerometry system successfully detects a motor deficit in the setting of acute ischemic stroke, accurately differentiating patients from controls, and correlates well with the baseline NIHSS score. Its use is feasible in the acute stroke setting. Overall, it shows promise as a diagnostic tool to continuously monitor acute stroke patients but requires validation in a larger trial.
authors.affiliation: Melbourne Brain Centre, University of Melbourne and Melbourne Health, Parkville, Vic., Australia.
authors.forename: Campbell
authors.initials: C
authors.lastname: Le Heron
authors.forename: Kun
authors.initials: K
authors.lastname: Fang
authors.forename: Jayavardhana
authors.initials: J
authors.lastname: Gubbi
authors.forename: Leonid
authors.initials: L
authors.lastname: Churilov
authors.forename: Marimuthu
authors.initials: M
authors.lastname: Palaniswami
authors.forename: Stephen
authors.initials: S
authors.lastname: Davis
authors.forename: Bernard
authors.initials: B
authors.lastname: Yan
mesh_terms: D061725:Accelerometry; D000368:Aged; D000369:Aged, 80 and over; D001132:Arm / Q000503:physiopathology*; D002545:Brain Ischemia / Q000175:diagnosis* / Q000503:physiopathology / Q000534:rehabilitation; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement / Q000502:physiology; D010865:Pilot Projects; D012372:ROC Curve; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis / Q000503:physiopathology*; D000071939:Stroke Rehabilitation; D059015:Wireless Technology