The purpose of this review is to provide a comprehensive approach for assessing the upper extremity (UE) after stroke. First, common upper extremity impairments and how to assess them are briefly discussed. While multiple UE impairments are typically present after stroke, the severity of one impairment, paresis, is the primary determinant of UE functional loss. Second, UE function is operationally defined and a number of clinical measures are discussed. It is important to consider how impairment and loss of function affect UE activity outside of the clinical environment. Thus, this review also identifies accelerometry as an objective method for assessing UE activity in daily life. Finally, the role that each of these levels of assessment should play in clinical decision making is discussed in order to optimize the provision of stroke rehabilitation services.

Objective 1) Determine if higher doses of motor therapy in chronic post-stroke hemiparesis result in better outcomes compared to lower doses, and 2) Evaluate potential modifiers of the dose-response relationship. Methods Eighty-five adults with UE paresis ≥ 6 months after stroke were randomized to one of four dose groups in this single-blind, parallel, RCT. The dosing parameter manipulated was amount of task-specific training, as indexed by the number of task repetitions. Groups received 3200, 6400, 9600, or Individualized Maximum (IM) repetitions, during 1 hr sessions, 4 days/week for 8 weeks. The intervention was an individualized, progressive task-specific upper limb training program designed to improve upper limb functional motor capacity. The primary outcome was the slope of the Action Research Arm Test (ARAT) during the intervention. Effects of dose and potential modifiers of the dose-response relationship were evaluated with hierarchical linear models. Results ARAT scores for the 3200, 9600, and IM groups improved over time as indicated by slopes (ΔARAT/wk, mean ± SEs) of 0.40 ± 0.15, 0.31 ± 0.16, and 0.66 ± 0.14, respectively (p < 0.05). The slope of the 6400 group was smaller (−0.05 ± 0.15) and significantly different from the 3200 and IM groups (p < 0.001). Initial motor capacity, neglect, and other tested characteristics did not modify the dose-response relationship. Interpretation Overall, treatment effects were small. There was no evidence of a dose-response effect of task-specific training on functional capacity in people with long-standing upper limb paresis post stroke.

Objectives To (1) determine which clinical assessments at admission to an inpatient rehabilitation facility (IRF) most simply predict discharge walking ability, and (2) identify a clinical decision rule to differentiate household versus community ambulators at discharge from an IRF. Design Retrospective cohort study. Setting IRF. Participants Two samples of participants (n=110 and 159) admitted with stroke. Interventions A multiple regression determined which variables obtained at admission (age, time from stroke to assessment, Motricity Index, somatosensation, Modified Ashworth Scale, FIM, Berg Balance Scale, 10-m walk speed) could most simply predict discharge walking ability (10-m walk speed). A logistic regression determined the likelihood of a participant achieving household (<0.4m/s) versus community (≥0.4 –0.8m/s; >0.8m/s) ambulation at the time of discharge. Validity of the results was evaluated on a second sample of participants. Main Outcome Measure Discharge 10-m walk speed. Results Admission Berg Balance Scale and FIM walk item scores explained most of the variance in discharge walk speed. The odds ratio of achieving only household ambulation at discharge was 20 (95% confidence interval [CI], 6 – 63) for sample 1 and 32 (95% CI, 10 –96) for sample 2 when the combination of having a Berg Balance Scale score of ≤20 and a FIM walk item score of 1 or 2 was present. Conclusions A Berg Balance Scale score of ≤20 and a FIM walk item score of 1 or 2 at admission indicates that a person with stroke is highly likely to only achieve household ambulation speeds at discharge from an IRF.

A key reason for referral to rehabilitation services after stroke and other neurological conditions is to improve one's ability to function in daily life. It has become important to measure a person's activities in daily life, and not just measure their capacity for activity in the structured environment of a clinic or laboratory. A wearable sensor that is now enabling measurement of daily movement is the accelerometer. Accelerometers are commercially-available devices resembling large wrist watches that can be worn throughout the day. Data from accelerometers can quantify how the limbs are engaged to perform activities in peoples' homes and communities. This report describes a methodology to collect accelerometry data and turn it into clinically-relevant information. First, data are collected by having the participant wear two accelerometers (one on each wrist) for 24 h or longer. The accelerometry data are then downloaded and processed to produce four different variables that describe key aspects of upper limb activity in daily life: hours of use, use ratio, magnitude ratio, and the bilateral magnitude. Density plots can be constructed that visually represent the data from the 24 h wearing period. The variables and their resultant density plots are highly consistent in neurologically-intact, community-dwelling adults. This striking consistency makes them a useful tool for determining if upper limb daily performance is different from normal. This methodology is appropriate for research studies investigating upper limb dysfunction and interventions designed to improve upper limb performance in daily life in people with stroke and other patient populations. Because of its relative simplicity, it may not be long before it is also incorporated in clinical neurorehabilitation practice.

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples’ homes and communities.

Objective 1) To examine clinician adherence to a standardized assessment battery across settings (acute hospital, IRF, outpatient facility), professional disciplines (PT, OT, SLP), and time of assessment (admission, discharge/monthly), and 2) evaluate how specific implementation events affected adherence. Design Retrospective cohort study Setting Acute hospital, IRF, outpatient facility with approximately 118 clinicians (PT, OT, SLP). Participants 2194 participants with stroke who were admitted to at least one of the above settings. All persons with stroke undergo standardized clinical assessments. Interventions N/A Main Outcome Measure Adherence to Brain Recovery Core assessment battery across settings, professional disciplines and time. Visual inspections of 17 months of time-series data were conducted to see if the events (e.g. staff meetings) increased adherence ≥ 5% and if so, how long the increase lasted. Results Median adherence ranged from 0.52 to 0.88 across all settings and professional disciplines. Both the acute hospital and IRF had higher adherence than the outpatient setting (p ≤ .001) with PT having the highest adherence across all three disciplines (p < .004). Of the 25 events conducted across the 17 month period to improve adherence, 10 (40%) resulted in a ≥ 5% increase in adherence the following month, with 6 services (60%) maintaining their increased level of adherence for at least one additional month. Conclusion Actual adherence to a standardized assessment battery in clinical practice varied across settings, disciplines and time. Specific events increased adherence 40% of the time with gains maintained for greater than a month in 60%.

Objective While returning to driving is a major concern for many stroke survivors, predicting who will return to driving after a stroke is often difficult for rehabilitation professionals. The primary aim of this study was to identify patient factors present at admission to an inpatient rehabilitation hospital that can be used to identify which patients with acute stroke will and will not return to driving. Design After comparing returners and non-returners on demographic and clinical characteristics, a logistic regression model with return to driving as the outcome variable was built using the backward stepwise method. Results Thirty-one percent (48/156) of patients who had been driving before their stroke had returned to driving six months post-stroke. The final regression model, using FIM cognition and lower extremity Motricity Index scores, predicted the driving outcome with an accuracy of 75% (107/143). Conclusions Patients with lower FIM cognition and lower extremity Motricity Index scores at admission to inpatient rehabilitation are less likely to return to driving at six months. This model could be used by rehabilitation professionals to help counsel patients and their families and focus treatment goals.

This Special Interest article describes a multidisciplinary, interinstitutional effort to build an organized system of stroke rehabilitation and outcomes measurement across the continuum of care. This system is focused on a cohort of patients who are admitted with the diagnosis of stroke to our acute facility, are discharged to inpatient and/or outpatient rehabilitation at our free-standing facility, and are then discharged to the community. This article first briefly explains the justification, goals, and purpose of the Brain Recovery Core system. The next sections describe its development and implementation, with details on the aspects related to physical therapy. The article concludes with an assessment of how the Brain Recovery Core system has changed and improved delivery of rehabilitation services. It is hoped that the contents of this article will be useful in initiating discussions and potentially facilitating similar efforts among other centers.