Stroke Inpatient Rehabilitation Reinforcement of ACTivity — SIRRACT  

Stroke Clinical Trial

Official title: Stroke Inpatient Rehabilitation Reinforcement of ACTivty: An International Multisite Clinical Trial

Status Completed

Clinical Trial Summary

The purpose of this study is to determine the effects of daily feedback about physical activity (number of bouts of walking, duration of bouts, total walking distance, average and fastest walking speed) and walking average speed compared to feedback about walking speed only on walking-related outcomes during inpatient rehabilitation for stroke. For the first time, daily walking and other exercise will be monitored by bilateral triaxial accelerometers on the ankles. Activity-recognition algorithms will analyze the inpatient sensor data and return a summary to the participants at each site.

Clinical Trial Description

Wireless Sensor System The inertial sensor system and activity-recognition algorithms were previously described and tested for short-term reliability. Three sets of triaxial accelerometers (Gulf Coast Data Concepts, Waveland, MS) were mailed to each site's coordinator. Therapists placed one sensor on each ankle before participants got out of bed each morning and removed them once they were in bed at the end of the day; sensor use during weekends was optional. A soft snap band secured each sensor proximal to the medial malleolus, flush against the bony tibia. Every night, sensors were plugged into a local computer to recharge while accelerometer data were uploaded to the central server at UCLA for secure storage and processing. Sensor Calibration and Data Processing In recognition of the variations in gait speed and stand and swing symmetry that occur in patients who need inpatient rehabilitation after stroke, we chose to generate individual templates of each participant's gait from a pair of standardized walks. On study entry participants performed two stopwatch- timed 10-meter walks at self-selected casual and safest fast walking speeds. A hybrid classifier employing dynamic time warping and Naïve Bayes algorithms generated statistical models of each participant's gait based on the two walks. Repeat walks were performed and the templates updated weekly for the remainder of each participant's rehabilitation stay to account for expected changes in gait parameters. ;

Related Conditions & MeSH terms

• Stroke

• NCT number: NCT01246882
• Study type: Interventional
• Source: University of California, Los Angeles
• Status: Completed
• Phase: Phase 3
• Start date: January 2011
• Completion date: November 2012