SIESTA (Sleep of Inpatients: Empower Staff to Act) for Acute Stroke Rehabilitation

The QI score is a measure used in the inpatient setting at the Shirley Ryan AbilityLab that has replaced the Functional Independence Measure (FIM). The score can be obtained in all patients, regardless of stroke type or deficit. The QI evaluates level of disability, and how much assistance is needed for a subject to perform activities of daily living. Each item is scored ranging from total assistance to total independence. Items include eating, grooming, bathing, dressing, toiling, bladder/bowel management, transfers, locomotion, stairs, comprehension, etc.

This questionnaire calculates the sleep quality index (SQI) using four items: slept throughout, sleep restless, ease falling asleep, and premature awakenings. A higher SQI indicates better sleep quality. Additionally, three items (ease awakening, refreshed, sufficient sleep) yield an awake score with lower scores indicating better sleep. Items have 5-point verbal anchors, and response alternatives vary with each question. It has been correlated with measures from polysomnography to measure sleep quality the night prior to administration.

This subjective questionnaire asks inpatients how specific items disrupted their sleep the prior night from 1 (not disruptive) to 5 (extremely disruptive). Select items correlate with in-hospital actigraphy, and specific items address rehabilitation.

Small multi-modality research-grade, wireless, and wearable sensors (Philips Actiwatch and Actigraph wGT3X-BT) are used to calculate total sleep time.

obtained from the ApneaLink™ devices, which are simple, cost-effective portable devices for diagnosing sleep-disordered breathing. It automatically analyzes and derives an AHI, flow limitation, snoring and oxygen desaturation index. The automatic analysis will be reviewed by an expert sleep specialist to ensure correct interpretation. The AHI is calculated based on number of events of apnea or blood O2 desaturation per hour, with <5 being normal and >30 being severe

We will obtain objective baseline data on orders of nighttime vitals, nocturnal medications that disrupt sleep (heparin q8, nighttime medications, bathing, etc.).

This questionnaire is a 7-item validated screening tool designed to assess the nature, severity, and impact of insomnia in adults.

Because stroke characteristics can impact sleep, we will obtain participant data about type of stroke (hemorrhagic/ischemic), stroke location (per CT), stroke deficits (urinary incontinence, aphasia, etc.), stroke severity (based on the NIH Stroke Scale), and presence of recurrent stroke (obtained from chart audit).

Using the electronic health record and a previously developed University of Chicago chart abstraction tool, a percentage of pharmacologic sleep aids used will be calculated.

For patients utilizing a CPAP, device adherence will be collected wirelessly through the device modem.

The 6MWT measures the distance a subject can walk indoors on a flat, hard surface in 6 minutes, using assistive devices as necessary. The test is a reliable and valid evaluation of functional exercise capacity and is used as a sub-maximal test of aerobic capacity and endurance. The minimal detectable change for people with sub-acute stroke is 60.98 meters.

The 10MWT measures the amount of time it takes to walk 10 meters. Time will be recorded using a stopwatch and recorded to the one hundredth of a second. The effects of acceleration and deceleration are minimized by adding 1 meter at the beginning and end of the course to isolate the subject's steady state speed. The test will be recorded 3 times each at a normal self-selected pace and at a faster pace, with adequate rest in between. Results will be averaged from 3 trials. Any assistive devices or orthotics should be kept consistent throughout and documented.

The BBS is a 14-item test, scored on a 5-level ordinal scale and validated against length of stay and discharge destination for stroke patients. It measures functional balance in a clinical setting during static and dynamic tasks (sitting, standing, transitioning from sit to stand, etc.).

The TUG assesses mobility by measuring the time a person take to rise from a chair, walk 3 meters, turn around, walk back to the chair, and sit down. It can detect longitudinal changes in mobility in stroke patients. The subject wears their routine footwear and orthotics and can use their mobility aids.

Gait analysis provides a quantitative means of assessing walking function based on spatiotemporal parameters of gait. Subjects walk at both a comfortable and a fast pace over the GaitRite system, an electronic walkway with integrated sensors. Data from GaitRite is reliable and valid for evaluating walking characteristics and provides a gold standard for validating gait parameters from the sensors. For gait analysis, we will focus on 5 parameters: stride time, swing time, stance time, step length, and cadence.

The 10-item MoCA assesses several cognitive domains. These include short-term memory recall, visuospatial abilities, executive function, attention, concentration, language and orientation to time and place.

Small multi-modality research-grade, wireless, and wearable sensors (eg. MC10 Biostamp, ActiGraph, and ActiLink) will be used to calculate REM cycles without the use of PPG. The MC10 or other wearable sensors can be placed simultaneously on body locations, collecting accelerometer, gyroscope, and bio-potential sensor data to provide a more in-depth analysis of heart rate variability across the night. The ActiGraph and ActiLink can be worn on the wrist or waist to collect accelerometer, gyroscope, and magnetometer. Actigraph management and data analysis are done using SRALab machine learning algorithms specific to stroke.

Small multi-modality research-grade, wireless, and wearable sensors (MC10 Biostamp, ActiGraph, and ActiLink) will be used to calculate objective measures of activity. The MC10 can be placed simultaneously on body locations, and the ActiGraph and ActiLink are worn on the wrist, with all three collecting accelerometer and gyroscope data. Actigraph management and data analysis are done using SRALab machine learning algorithms specific to stroke. Raw acceleration data will be converted into a measure of step count.

Small multi-modality research-grade, wireless, and wearable sensors (Philips Actiwatch and Actigraph wGT3X-BT) are used to calculate total wake after sleep onset.

Small multi-modality research-grade, wireless, and wearable sensors (Philips Actiwatch and Actigraph wGT3X-BT) are used to calculate total sleep efficiency.