Background: Gait is often impaired in people after stroke, restricting personal independence and affecting quality of life. During stroke rehabilitation, walking capacity is conventionally assessed by measuring walking distance and speed. Gait features, such as asymmetry and variability, are not routinely determined, but may provide more specific insights into the patient’s walking capacity. Inertial measurement units offer a feasible and promising tool to determine these gait features. Objective: We examined the test–retest reliability of inertial measurement units-based gait features measured in a two-minute walking assessment in people after stroke and while in clinical rehabilitation. Method: Thirty-one people after stroke performed two assessments with a test–retest interval of 24 h. Each assessment consisted of a two-minute walking test on a 14-m walking path. Participants were equipped with three inertial measurement units, placed at both feet and at the low back. In total, 166 gait features were calculated for each assessment, consisting of spatio-temporal (56), frequency (26), complexity (63), and asymmetry (14) features. The reliability was determined using the intraclass correlation coefficient. Additionally, the minimal detectable change and the relative minimal detectable change were computed. Results: Overall, 107 gait features had good–excellent reliability, consisting of 50 spatio-temporal, 8 frequency, 36 complexity, and 13 symmetry features. The relative minimal detectable change of these features ranged between 0.5 and 1.5 standard deviations. Conclusion: Gait can reliably be assessed in people after stroke in clinical stroke rehabilitation using three inertial measurement units.

Post-stroke, patients exhibit considerable variations in gait patterns. One of the variations that can be present in post-stroke gait is knee hyperextension in the stance phase. What is the current evidence for the effectiveness of the treatment of knee hyperextension in post-stroke gait? MEDLINE, EMBASE, PEDro, CINAHL, and the Cochrane library were searched for relevant controlled trials. Two researchers independently extracted the data and assessed the methological quality. A best evidence synthesis was conducted to summarize the results. Eight controlled trials (5 RCTs, 3 CCTs) were included. Three types of interventions were identified: proprioceptive training, orthotic treatment, and functional electrostimulation (FES). In the included studies, the time since the stroke occurrence varied from the (sub)acute phase to the chronic phase. Only short-term effects were investigated. The adjustment from a form of proprioceptive training to physiotherapy training programs seems to be effective (moderate evidence) for treating knee hyperextension in gait, as applied in the subacute phase post-stroke. Neither evidence for effects on gait speed nor gait symmetry were found as a result of proprioceptive training. Orthoses that cover the knee have some effects (limited evidence) on knee hyperextension and gait speed. No evidence was found for FES. This is the first systematic literature review on the effectiveness of interventions on knee hyperextension in post-stroke gait. We found promising results (moderate evidence) for some "proprioceptive approaches" as an add-on therapy to physiotherapy training programs for treating knee hyperextension during the subacute phase post-stroke, in the short-term. Therefore, initially, clinicians should implement a training program with a proprioceptive approach in order to restore knee control in these patients. Because only studies reporting short-term results were found, more high-quality RCTs and CCTs are needed that also study mid- and long-term effects.

This study aimed to acquire insight into the decision-making processes of healthcare professionals concerning referral to primary care physiotherapy at the time of discharge from inpatient stroke rehabilitation. A generic qualitative study using an inductive thematic analysis was performed. Semi-structured interviews were conducted following an interview guide. Secondary care centers in the Netherlands: neurology departments of nine hospitals and (geriatric) rehabilitation centers. Nineteen healthcare professionals (physiotherapists, specialist in geriatric medicine, physiatrist, physician assistant) participated in the study. All were involved in the decision for referral to primary care physiotherapy. During the inpatient period, healthcare professionals gather information to form a complete picture of the stroke survivor as a basis for decision-making. The decision on referral is influenced by personal factors and home environment of the stroke survivor, organizational factors within the care setting, and the intuition and feeling of social responsibility of the individual healthcare professional. After inpatient rehabilitation, many elements are considered that may influence referral to primary care physiotherapy. Presently, there is no consensus concerning referrals. The final decision depends on the individual physiotherapist and care setting. Healthcare professionals mentioned the importance of movement behavior, although there is no consensus if secondary prevention is a primary task of the physiotherapist. More research is needed to identify risk factors for functional decline in order to develop a referral policy that addresses primary care physiotherapy to the right group of stroke survivors.

Importance: During rehabilitation, the balance of a person with stroke is commonly monitored using the Berg Balance Scale and the Mini-Balance Evaluation Systems Test. These tests evaluate the ability to maintain balance in an upright position while performing tasks. Currently, clinical practice lacks an adequate assessment of balance impairments like the increased postural sway poststroke. Integrating postural sway measurement with a body-worn inertial measurement unit could offer clinicians an objective and rapid measurement method. Objective: Sensitivity to change and responsiveness of postural sway measurement during stroke rehabilitation were explored. Design: A longitudinal study was conducted. Setting: Data were collected in 5 rehabilitation centers. Participants: 94 people with stroke were included in the study. Intervention: Sensitivity to change was evaluated by comparing the percentages of participants who exceeded the minimal detectable change for both the conventional and inertial measurement unit tests. Responsiveness was assessed through hypotheses testing, utilizing both a criterion approach (external criterion: a 5-point retrospective Global Rating of Change score) and a construct approach. Results: At discharge, only 3.2% to 23.9% of the participants showed genuine improvement (ie, had a lower postural sway) on the inertial measurement unit test, compared to 33% to 60% on the conventional tests. In total, 67.4% of the hypotheses were rejected. Conclusions: The sensitivity to change and responsiveness of postural sway measurement in people with stroke are limited. Restoring balance to achieve functional independence is not necessarily dependent on, or associated with, the level of postural sway. At present, integrating postural sway measurement into clinical stroke rehabilitation seems to provide no added value for monitoring balance. Relevance: A novel approach to balance assessment in clinical stroke rehabilitation was investigated. It was found that while most participants improved in terms of functionality and independence, only a small percentage exhibited a significant change in postural sway. Therefore, postural sway may not effectively serve as an indicator of improved movement quality. This insight is crucial for both researchers and clinicians involved in neurorehabilitation.

Balance impairments in stroke rehabilitation are commonly assessed using the Trunk Control Test (TCT), Berg Balance Scale (BBS), and Mini Balance Evaluation System Test (Mini-BESTest). However, these conventional tests are subjective, susceptible to floor and ceiling effects, and time-intensive. Inertial measurement units (IMUs) may address these limitations by providing objective, impairment-level metrics, not captured by conventional tests. This observational study explored the measurement properties of an IMU-based balance assessment of postural sway, and compared them with conventional tests in routine stroke rehabilitation. Stroke survivors from five Dutch rehabilitation centers were assessed at admission and discharge using conventional and IMU-based balance tests during sitting and standing tasks. Floor and ceiling effects were evaluated, and relationships between measures were examined using correlation analysis. At admission, 105 participants were measured, and 90 at discharge. IMU measures showed no floor or ceiling effects despite skewed distributions. IMU stance-tasks correlated moderately with the BBS and Mini-BESTest (18–29% variance explained), whereas IMU sitting-tasks showed weak to no relationship with the TCT. IMU-based balance assessment of postural sway captures balance-related information that is partially different from conventional tests. Although IMUs offer practical advantages, further research is needed to establish the clinical relevance of postural sway measurements alongside conventional tests.

Objective: To evaluate the added value of sensor-based tests over conventional tests in explaining the variance in independence in activities of daily living (ADL) and independent walking in patients during inpatient stroke rehabilitation. Design: Cross-sectional design Setting: Inpatient stroke rehabilitation Participants: Data were collected from 115 patients with stroke admitted to inpatient rehabilitation. Intervention: No intervention has been applied. Main measures: Conventional measures and sensor-based tests in which postural sway and gait variables were measured using inertial measurement units. Outcome measures were ADL independence (determined by Barthel Index [BI]) and independent walking (determined by Functional Ambulation Categories [FAC]). Results: With univariable linear regression analyses showed that the Berg Balance Scale (BBS) explained most variance in ADL independence ( R ²  = .527) and independent walking ( R ²  = .727). In hierarchical multivariable regression analyses, symmetry during walking without a walking aid contributed most (Δ R ²=18.6%) in explaining variance in ADL independency, resulting in a model explaining 15.7% ( p = .029) of the variance in the BI. Tempo during walking with a walking aid contributed most (Δ R² = 20.1%) in explaining variance in independent walking, resulting in a model explaining 23.3% ( p = .002) of the variance in the FAC. Adding sensor-based variables to models with the BBS did not significantly improve variance explanation. Conclusions: The added value of variables measured with an inertial measurement unit in explaining ADL independence and walking ability after stroke is limited. These findings contribute to understanding the use of inertial measurement units in stroke rehabilitation, but caution is needed when applying them to predict physical recovery.