Fusing GPS, Activity Monitors, and Self-Report to Improve Assessment of Walking Activity and Community Participation After Stroke.

Background And Purpose: Walking and participation in the community are important goals for people post-stroke (PPS). These constructs are challenging to measure given limitations in current data collection methodologies. The purpose of this study was to (1) develop a data fusion approach that combined data from global positioning system (GPS), activity monitor (AM), and daily trip log to identify walking activity and participation in the community, and (2) to examine the construct validity of the data fusion method.

Sleep Health During Recovery After Stroke.

Study Objectives: People with stroke are susceptible to developing sleep disorders, which may negatively impact recovery. Little is known about sleep health (SH) broadly and its impact on recovery after stroke. The purpose of this study was to explore factors that are associated with SH during recovery after stroke.

Prevalence and Detection of Obstructive Sleep Apnea Early after Stroke.

Background: Obstructive sleep apnea (OSA) negatively impacts post-stroke recovery. This study's purpose: examine the prevalence of undiagnosed OSA and describe a simple tool to identify those at-risk for OSA in the early phase of stroke recovery.

Methods: This was a cross-sectional descriptive study of people ∼15 days post-stroke.

Research from Low-Income and Middle-Income Countries will Benefit Global Health and the Physiotherapy Profession, but it Requires Support.

Disparities in research publications are common in the physiotherapy and rehabilitation fields. A small proportion of published research arises from low-income and middle-income countries (LMICs), home to 85% of the world's population. Systems-level, institutional-level, and individual-level factors contribute to these disparities.

Study Protocol: Sleep Effects on Poststroke Rehabilitation Study.

Background: A range of sleep disturbances and disorders are problematic in people after stroke; they interfere with recovery of function during poststroke rehabilitation. However, studies to date have focused primarily on the effects of one sleep disorder-obstructive sleep apnea (OSA)-on stroke recovery.

Objectives: The study protocol for the SLEep Effects on Poststroke Rehabilitation (SLEEPR) Study is presented with aims of characterizing proportion of non-OSA sleep disorders in the first 90 days after stroke, evaluating the effect of non-OSA sleep disorders on poststroke recovery, and exploring the complex relationships between stroke, sleep, and recovery in the community setting.

The Impact of Sleep Disorders on Functional Recovery and Participation Following Stroke: A Systematic Review and Meta-Analysis.

Background: Adequate sleep is vital for health and quality of life. People with stroke and a concomitant sleep disorder may have poorer outcomes than those without a sleep disorder.

Objective: To systematically evaluate the published literature to determine the impact of sleep disorders on physical, functional recovery at the activity and participation level after stroke.

Minimal Clinically Important Difference of the 6-Minute Walk Test in People With Stroke.

Background And Purpose: The 6-minute walk test (6MWT) is commonly used in people with stroke. The purpose of this study was to estimate the minimal clinically important difference (MCID) of the 6MWT 2 months poststroke.

Methods: We performed a secondary analysis of data from a rehabilitation trial.

Predicting Home and Community Walking Activity Poststroke.

Background And Purpose: Walking ability poststroke is commonly assessed using gait speed categories developed by Perry et al. The purpose of this study was to reexamine factors that predict home and community ambulators determined from real-world walking activity data using activity monitors.

Methods: Secondary analyses of real-world walking activity from 2 stroke trials.

Self-Selected and Maximal Walking Speeds Provide Greater Insight Into Fall Status Than Walking Speed Reserve Among Community-Dwelling Older Adults.

Objective: To determine the degree to which self-selected walking speed (SSWS), maximal walking speed (MWS), and walking speed reserve (WSR) are associated with fall status among community-dwelling older adults.

Design: WS and 1-year falls history data were collected on 217 community-dwelling older adults (median age = 82, range 65-93 years) at a local outpatient PT clinic and local retirement communities and senior centers. WSR was calculated as a difference (WSRdiff = MWS - SSWS) and ratio (WSRratio = MWS/SSWS).

Development of the RT-GAIT, a Real-Time feedback device to improve Gait of individuals with stroke.

Regaining the ability to walk is a major rehabilitation goal after a stroke. Recent research suggests that, in people with stroke, task-oriented and intensive rehabilitation strategies can drive cortical reorganization and increase activity levels. This paper describes development and pilot testing of a novel wearable device for Real-Time Gait and Activity Improving Telerehabilitation (RT-GAIT), designed for use with such rehabilitation strategies.

Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults.

Daily ambulatory activity is associated with health and functional status in older adults; however, assessment requires multiple days of activity monitoring. The objective of this study was to determine the relative capabilities of self-selected walking speed (SSWS), maximal walking speed (MWS), and walking speed reserve (WSR) to provide insight into daily ambulatory activity (steps per day) in community-dwelling older adults. Sixty-seven older adults completed testing and activity monitoring (age 80.

EMG control of a bionic knee prosthesis: exploiting muscle co-contractions for improved locomotor function.

This paper presents the development and experimental evaluation of a volitional control architecture for a powered-knee transfemoral prosthesis that affords the amputee user with direct control of knee impedance using measured electromyogram (EMG) potentials of antagonist muscles in the residual limb. The control methodology incorporates a calibration procedure performed with each donning of the prosthesis that characterizes the co-contraction levels as the user performs volitional phantom-knee flexor and extensor contractions. The performance envelope for EMG control of impedance is then automatically shaped based on the flexor and extensor calibration datasets.

Using decision trees to measure activities in people with stroke.

Improving community mobility is a common goal for persons with stroke. Measuring daily physical activity is helpful to determine the effectiveness of rehabilitation interventions. In our previous studies, a novel wearable shoe-based sensor system (SmartShoe) was shown to be capable of accurately classify three major postures and activities (sitting, standing, and walking) from individuals with stroke by using Artificial Neural Network (ANN).

Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury.

Background: Advances in sensor technologies and signal processing techniques provide a method to accurately measure walking activity in the home and community. Activity monitors geared toward consumer or patient use may be an alternative to more expensive monitors designed for research to measure stepping activity.

Objective: The objective of this study was to examine the accuracy of 2 consumer/patient activity monitors, the Fitbit Ultra and the Nike+ Fuelband, in identifying stepping activity in people with stroke and traumatic brain injury (TBI).

Recognition of household and athletic activities using SmartShoe.

The ability to provide real time feedback concerning a person's activity level and energy expenditure can be beneficial for improving activity levels of individuals. Examples include biofeedback systems used for body weight and physical activity management and biofeedback systems for rehabilitation of stroke patients. A critical aspect of any such system is being able to accurately classify data in real-time so that active and timely feedback can be provided.

Identifying activity levels and steps of people with stroke using a novel shoe-based sensor.

Background/purpose: Advances in sensor technologies provide a method to accurately assess activity levels of people with stroke in their community. This information could be used to determine the effectiveness of rehabilitation interventions as well as provide behavior-enhancing feedback. The purpose of this study was to assess the accuracy of a novel shoe-based sensor system (SmartShoe) to identify different functional postures and steps in people with stroke.

Using sensors to measure activity in people with stroke.

Purpose: The purpose of this study was to determine the ability of a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with a support vector machine (SVM) to accurately identify sitting, standing, and walking postures in people with stroke.

Methods: Subjects with stroke wore the shoe-based sensor while randomly assuming 3 main postures: sitting, standing, and walking. A SVM classifier was used to train and validate the data to develop individual and group models, which were tested for accuracy, recall, and precision.