Physical inactivity after stroke: Incidence and early predictors based on 190 individuals in a 1-year follow-up of the Fall Study of Gothenburg.

OBJECTIVE: To determine the incidence of physical inactivity and factors prior to stroke and in acute stroke that are associated with physical inactivity 1 year after stroke Design: Prospective longitudinal cohort Patients: A total of 190 consecutively included individuals with acute stroke Methods: A follow-up questionnaire, relating to physical activity level using the Saltin-Grimby Physical Activity Scale, was sent to participants in The Fall Study of Gothenburg 1 year after stroke. Predictors of physical inactivity at baseline were identified using univariable and multivariable logistic regression analyses. RESULTS: Physical inactivity 1 year after stroke was reported by 70 (37%) of the 190 patients who answered the questionnaire and was associated with physical inactivity before the stroke, odds ratio (OR) 4.07 (95% confidence interval (95% CI) 1.69-9.80, p = 0.002); stroke severity (assessed by National Institutes of Health Stroke Scale (NIHSS), score 1-4), OR 2.65 (95% CI) 1.04-6.80, p = 0.042) and fear of falling in acute stroke, OR 2.37 (95% CI 1.01-5.60, p = 0.048). CONCLUSION: Almost 4 in 10 participants reported physical inactivity 1 year after stroke. Physical inactivity before the stroke, stroke severity and fear of falling in acute stroke are the 3 main factors that predict physical inactivity 1 year after stroke.

A multiple motion sensors index for motor state quantification in Parkinson's disease.

AIM: To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson's disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks. METHOD: Nineteen PD patients performed three motor tests including leg agility, pronation-supination movement of hands, and walking in a clinic while wearing inertial measurement unit sensors on their wrists and ankles. They performed the tests repeatedly before and after taking 150% of their individual oral levodopa-carbidopa equivalent morning dose.Three neurologists blinded to treatment status, viewed patients' videos and rated their motor symptoms, dyskinesia, overall motor state based on selected items of Unified PD Rating Scale (UPDRS) part III, Dyskinesia scale, and Treatment Response Scale (TRS). To build TRIMS, out of initially 178 extracted features from upper- and lower-limbs data, 39 features were selected by stepwise regression method and were used as input to support vector machines to be mapped to mean reference TRS scores using 10-fold cross-validation method. Test-retest reliability, responsiveness to medication, and correlation to TRS as well as other UPDRS items were evaluated for TRIMS. RESULTS: The correlation of TRIMS with TRS was 0.93. TRIMS had good test-retest reliability (ICC = 0.83). Responsiveness of the TRIMS to medication was good compared to TRS indicating its power in capturing the treatment effects. TRIMS was highly correlated to dyskinesia (R = 0.85), bradykinesia (R = 0.84) and gait (R = 0.79) UPDRS items. Correlation of sensor index from the upper-limb to TRS was 0.89. CONCLUSION: Using the fusion of upper- and lower-limbs sensor data to construct TRIMS provided accurate PD motor states estimation and responsive to treatment. In addition, quantification of upper-limb sensor data during walking test provided strong results.