Stability and Harmony of Gait in Patients with Subacute Stroke

Modeling the Heterogeneity of Post-Stroke Gait Control in Free-Living Environments Using a Personalized Causal Network

Post-stroke gait control is a complex, often fail to account for the heterogeneity and continuity of gait in existing gait models. Precisely evaluating gait speed adjustability and gait instability in free-living environments is important to understand how individuals with post-stroke gait dysfunction approach diverse environments and contexts. This study aimed to explore individual causal interactions in the free-living gait control of persons with stroke. To this end, fifty persons with stroke wore an accelerometer on the fifth lumbar vertebra (L5) for 24 h in a free-living environment. Individually directed acyclic graphs (DAGs) were generated based on the spatiotemporal gait parameters at contemporaneous and temporal points calculated from the acceleration data. Spectral clustering and Bayesian model comparison were used to characterize the DAGs. Finally, the DAG patterns were interpreted via Bayesian logistic analysis. Spectral clustering identified three optimal clusters from the DAGs. Cluster 1 included persons with moderate stroke who showed high gait asymmetry and gait instability and primarily adjusted gait speed based on cadence. Cluster 2 included individuals with mild stroke who primarily adjusted their gait speed based on step length. Cluster 3 comprised individuals with mild stroke who primarily adjusted their gait speed based on both step length and cadence. These three clusters could be accurately classified based on four variables: Ashman's D for step velocity, Fugl-Meyer Assessment, step time asymmetry, and step length. The diverse DAG patterns of gait control identified suggest the heterogeneity of gait patterns and the functional diversity of persons with stroke. Understanding the theoretical interactions between gait functions will provide a foundation for highly tailored rehabilitation.

Differences in Trunk Acceleration-Derived Gait Indexes in Stroke Subjects with and without Stroke-Induced Immunosuppression

Background: Stroke-induced immunosuppression (SII) represents a negative rehabilitative prognostic factor associated with poor motor performance at discharge from a neurorehabilitation unit (NRB). This study aims to evaluate the association between SII and gait impairment at NRB admission. Methods: Forty-six stroke patients (65.4 ± 15.8 years, 28 males) and 42 healthy subjects (HS), matched for age, sex, and gait speed, underwent gait analysis using an inertial measurement unit at the lumbar level. Stroke patients were divided into two groups: (i) the SII group was defined using a neutrophil-to-lymphocyte ratio ≥ 5, and (ii) the immunocompetent (IC) group. Harmonic ratio (HR) and short-term largest Lyapunov's exponent (sLLE) were calculated as measures of gait symmetry and stability, respectively. Results: Out of 46 patients, 14 (30.4%) had SII. HR was higher in HS when compared to SII and IC groups (p < 0.01). HR values were lower in SII when compared to IC subjects (p < 0.01). sLLE was lower in HS when compared to SII and IC groups in the vertical and medio-lateral planes (p ≤ 0.01 for all comparisons). sLLE in the medio-lateral plane was higher in SII when compared to IC subjects (p = 0.04). Conclusions: SII individuals are characterized by a pronounced asymmetric gait and a more impaired dynamic gait stability. Our findings underline the importance of devising tailored rehabilitation programs in patients with SII. Further studies are needed to assess the long-term outcomes and the role of other clinical features on gait pattern.

Exploring harmonic walking development in children with unilateral cerebral palsy and typically developing toddlers: Insights from walking experience

This longitudinal study investigated the impact of the first independent steps on harmonic gait development in unilateral cerebral palsy (CP) and typically developing (TD) children. We analysed the gait ratio values (GR) by comparing the duration of stride/stance, stance/swing and swing/double support phases. Our investigation focused on identifying a potential trend towards the golden ratio value of 1.618, which has been observed in the locomotion of healthy adults as a characteristic of harmonic walking. Locomotor ability was assessed in both groups at different developmental stages: before and after the emergence of independent walking. Results revealed that an exponential fit was observed only after the first unsupported steps were taken. TD children achieved harmonic walking within a relatively short period (approximately one month) compared to children with CP, who took about seven months to develop harmonic walking. Converging values for stride/stance and stance/swing gait ratios, averaged on the two legs, closely approached the golden ratio in TD children (R2 = 0.9) with no difference in the analysis of the left vs right leg separately. In contrast, children with CP exhibited a trend for stride/stance and stance/swing (R2 = 0.7), with distinct trends observed for the most affected leg which did not reach the golden ratio value for the stride/stance ratio (GR = 1.5), while the least affected leg exceeded it (GR = 1.7). On the contrary, the opposite trend was observed for the stance/swing ratio. These findings indicate an overall harmonic walking in children with CP despite the presence of asymmetry between the two legs. These results underscore the crucial role of the first independent steps in the progressive development of harmonic gait over time.

Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study

BACKGROUND

Incorporating instrument measurements into clinical assessments can improve the accuracy of results when assessing mobility related to activities of daily living. This can assist clinicians in making evidence-based decisions. In this context, kinematic measures are considered essential for the assessment of sensorimotor recovery after stroke. The aim of this study was to assess the validity of using an Android device to evaluate kinematic data during the performance of a standardized mobility test in people with chronic stroke and hemiparesis.

METHODS

This is a cross-sectional study including 36 individuals with chronic stroke and hemiparesis and 33 age-matched healthy subjects. A simple smartphone attached to the lumbar spine with an elastic band was used to measure participants' kinematics during a standardized mobility test by using the inertial sensor embedded in it. This test includes postural control, walking, turning and sitting down, and standing up. Differences between stroke and non-stroke participants in the kinematic parameters obtained after data sensor processing were studied, as well as in the total execution and reaction times. Also, the relationship between the kinematic parameters and the community ambulation ability, degree of disability and functional mobility of individuals with stroke was studied.

RESULTS

Compared to controls, participants with chronic stroke showed a larger medial-lateral displacement (p = 0.022) in bipedal stance, a higher medial-lateral range (p < 0.001) and a lower cranio-caudal range (p = 0.024) when walking, and lower turn-to-sit power (p = 0.001), turn-to-sit jerk (p = 0.026) and sit-to-stand jerk (p = 0.001) when assessing turn-to-sit-to-stand. Medial-lateral range and total execution time significantly correlated with all the clinical tests (p < 0.005), and resulted significantly different between independent and limited community ambulation patients (p = 0.042 and p = 0.006, respectively) as well as stroke participants with significant disability or slight/moderate disability (p = 0.024 and p = 0.041, respectively).

CONCLUSION

This study reports a valid, single, quick and easy-to-use test for assessing kinematic parameters in chronic stroke survivors by using a standardized mobility test with a smartphone. This measurement could provide valid clinical information on reaction time and kinematic parameters of postural control and gait, which can help in planning better intervention approaches.

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Minimal detectable change in inertial measurement unit-based trunk acceleration indices during gait in inpatients with subacute stroke

Gait analysis using inertial measurement units (IMU) provides a multifaceted assessment of gait characteristics, but minimal detectable changes (MDC), the true change beyond measurement error, during gait in patients hospitalized with subacute stroke has not been clarified. This study aimed to determine the MDC in IMU-based trunk acceleration indices during gait in patients hospitalized with subacute stroke. Nineteen patients with subacute stroke (mean ± SD, 75.4 ± 10.9 years; 13 males) who could understand instructions, had a pre-morbid modified Rankin Scale < 3 and could walk straight for 16 m under supervision were included. As trunk acceleration indices, Stride regularity, harmonic ratio (HR), and normalized root mean square (RMS) during gait were calculated on three axes: mediolateral (ML), vertical (VT), and anterior-posterior (AP). MDC was calculated from two measurements taken on the same day according to the following formula: MDC = standard error of measurement × 1.96 × 2. The MDCs for each trunk acceleration index were, in order of ML, VT, and AP: 0.175, 0.179, and 0.149 for stride regularity; 0.666, 0.741, and 0.864 for HR; 4.511, 2.288, and 2.680 for normalized RMS. This finding helps determine the effectiveness of rehabilitation interventions in the gait assessment of patients with stroke.

Smoothness Evaluation Indices during Sit-to-Stand-to-Sit Motions in Healthy Older Females and after Hip Fracture Using an Accelerometer: A Pilot Study

BACKGROUND

Studies that quantify the quality of sit-to-stand-to-sit (STS) motions, particularly in terms of smoothness, are limited. Thus, this study aimed to investigate the possibility and usefulness of quality evaluation during STS motions.

METHODS

This cross-sectional study enrolled 36 females aged >60 years, including 18 females each in the healthy and hip fracture groups. Measurements were performed at two different speeds: five STS as fast as possible (STSF) and two seconds for each motion (STS2s). Indices of smoothness, including harmonic ratio (HR) and power spectrum entropy (PSE), were calculated and compared from the measured data in each of the three axial directions.

RESULTS

HR in the vertical direction was significantly higher in the healthy group (STSF: 3.65 ± 1.74, STS2s: 3.42 ± 1.54) than in the hip fracture group (STSF: 2.67 ± 1.01, STS2s: 2.58 ± 0.83) for STSF and STS2s. Furthermore, PSE for all directions and triaxial composites were significantly lower for STS2s (the healthy group (mediolateral (ML): 7.63 ± 0.31, vertical (VT): 7.46 ± 0.22, anterior-posterior (AP): 7.47 ± 0.15, triaxial: 7.45 ± 0.25), the hip fracture group (ML: 7.82 ± 0.16, VT: 7.63 ± 0.16, AP: 7.61 ± 0.17, triaxial: 7.66 ± 0.17)).

CONCLUSIONS

This study suggests the usefulness of HR and PSE as quality evaluations for STS motions.

Identification of Gait Unbalance and Fallers Among Subjects with Cerebellar Ataxia by a Set of Trunk Acceleration-Derived Indices of Gait

This study aimed to assess the ability of 25 gait indices to characterize gait instability and recurrent fallers among persons with primary degenerative cerebellar ataxia (pwCA), regardless of gait speed, and investigate their correlation with clinical and kinematic variables. Trunk acceleration patterns were acquired during the gait of 34 pwCA, and 34 age- and speed-matched healthy subjects (HS_matched) using an inertial measurement unit. We calculated harmonic ratios (HR), percent recurrence, percent determinism, step length coefficient of variation, short-time largest Lyapunov exponent (sLLE), normalized jerk score, log-dimensionless jerk (LDLJ-A), root mean square (RMS), and root mean square ratio of accelerations (RMSR) in each spatial direction for each participant. Unpaired t-tests or Mann-Whitney tests were performed to identify significant differences between the pwCA and HS_matched groups. Receiver operating characteristics were plotted to assess the ability to characterize gait alterations in pwCA and fallers. Optimal cutoff points were identified, and post-test probabilities were calculated. The HRs showed to characterize gait instability and pwCA fallers with high probabilities. They were correlated with disease severity and stance, swing, and double support duration, regardless of gait speed. sLLEs, RMSs, RMSRs, and LDLJ-A were slightly able to characterize the gait of pwCA but failed to characterize fallers.

A scoping review on recent trends in wearable sensors to analyze gait in people with stroke: From sensor placement to validation against gold-standard equipment

The purpose of the review is to evaluate wearable sensor placement, their impact and validation of wearable sensors on analyzing gait, primarily the postural instability in people with stroke. Databases, namely PubMed, Cochrane, SpringerLink, and IEEE Xplore were searched to identify related articles published since January 2005. The authors have selected the articles by considering patient characteristics, intervention details, and outcome measurements by following the priorly set inclusion and exclusion criteria. From a total of 1077 articles, 142 were included in this study and classified into functional fields, namely postural stability (PS) assessments, physical activity monitoring (PA), gait pattern classification (GPC), and foot drop correction (FDC). The review covers the types of wearable sensors, their placement, and their performance in terms of reliability and validity. When employing a single wearable sensor, the pelvis and foot were the most used locations for detecting gait asymmetry and kinetic parameters, respectively. Multiple Inertial Measurement Units placed at different body parts were effectively used to estimate postural stability and gait pattern. This review article has compared results of placement of sensors at different locations helping researchers and clinicians to identify the best possible placement for sensors to measure specific kinematic and kinetic parameters in persons with stroke.

Present and future of gait assessment in clinical practice: Towards the application of novel trends and technologies

Background

Despite being available for more than three decades, quantitative gait analysis remains largely associated with research institutions and not well leveraged in clinical settings. This is mostly due to the high cost/cumbersome equipment and complex protocols and data management/analysis associated with traditional gait labs, as well as the diverse training/experience and preference of clinical teams. Observational gait and qualitative scales continue to be predominantly used in clinics despite evidence of less efficacy of quantifying gait.

Research objective

This study provides a scoping review of the status of clinical gait assessment, including shedding light on common gait pathologies, clinical parameters, indices, and scales. We also highlight novel state-of-the-art gait characterization and analysis approaches and the integration of commercially available wearable tools and technology and AI-driven computational platforms.

Methods

A comprehensive literature search was conducted within PubMed, Web of Science, Medline, and ScienceDirect for all articles published until December 2021 using a set of keywords, including normal and pathological gait, gait parameters, gait assessment, gait analysis, wearable systems, inertial measurement units, accelerometer, gyroscope, magnetometer, insole sensors, electromyography sensors. Original articles that met the selection criteria were included.

Results and significance

Clinical gait analysis remains highly observational and is hence subjective and largely influenced by the observer's background and experience. Quantitative Instrumented gait analysis (IGA) has the capability of providing clinicians with accurate and reliable gait data for diagnosis and monitoring but is limited in clinical applicability mainly due to logistics. Rapidly emerging smart wearable technology, multi-modality, and sensor fusion approaches, as well as AI-driven computational platforms are increasingly commanding greater attention in gait assessment. These tools promise a paradigm shift in the quantification of gait in the clinic and beyond. On the other hand, standardization of clinical protocols and ensuring their feasibility to map the complex features of human gait and represent them meaningfully remain critical challenges.

Sensitivity to gait improvement after levodopa intake in Parkinson's disease: A comparison study among synthetic kinematic indices

The synthetic indices are widely used to describe balance and stability during gait. Some of these are employed to describe the gait features in Parkinson's disease (PD). However, the results are sometimes inconsistent, and the same indices are rarely used to compare the individuals affected by PD before and after levodopa intake (OFF and ON condition, respectively). Our aim was to investigate which synthetic measure among Harmonic Ratio, Jerk Ratio, Golden Ratio and Trunk Displacement Index is representative of gait stability and harmony, and which of these are more sensitive to the variations between OFF and ON condition. We found that all indices, except the Jerk Ratio, significantly improve after levodopa. Only the improvement of the Trunk Displacement Index showed a direct correlation with the motor improvement measured through the clinical scale UPDRS-III (Unified Parkinson's Disease Rating Scale-part III). In conclusion, we suggest that the synthetic indices can be useful to detect motor changes induced by, but not all of them clearly correlate with the clinical changes achieved with the levodopa administration. In our analysis, only the Trunk Displacement Index was able to show a clear relationship with the PD clinical motor improvement.

Performance Index for in Home Assessment of Motion Abilities in Ataxia Telangiectasia: A Pilot Study

Background. It has been shown in the very recent literature that human walking generates rhythmic motor patterns with hidden time harmonic structures that are represented (at the subject’s comfortable speed) by the occurrence of the golden ratio as the the ratio of the durations of specific walking gait subphases. Such harmonic proportions may be affected—partially or even totally destroyed—by several neurological and/or systemic disorders, thus drastically reducing the smooth, graceful, and melodic flow of movements and altering gait self-similarities. Aim. In this paper we aim at, preliminarily, showing the reliability of a technologically assisted methodology—performed with an easy to use wearable motion capture system—for the evaluation of motion abilities in Ataxia-Telangiectasia (AT), a rare infantile onset neurodegenerative disorder, whose typical neurological manifestations include progressive gait unbalance and the disturbance of motor coordination. Methods. Such an experimental methodology relies, for the first time, on the most recent accurate and objective outcome measures of gait recursivity and harmonicity and symmetry and double support subphase consistency, applied to three AT patients with different ranges of AT severity. Results. The quantification of the level of the distortions of harmonic temporal proportions is shown to include the qualitative evaluations of the three AT patients provided by clinicians. Conclusions. Easy to use wearable motion capture systems might be used to evaluate AT motion abilities through recursivity and harmonicity and symmetry (quantitative) outcome measures.

Artificial Neural Network Detects Hip Muscle Forces as Determinant for Harmonic Walking in People after Stroke

Many recent studies have highlighted that the harmony of physiological walking is based on a specific proportion between the durations of the phases of the gait cycle. When this proportion is close to the so-called golden ratio (about 1.618), the gait cycle assumes an autosimilar fractal structure. In stroke patients this harmony is altered, but it is unclear which factor is associated with the ratios between gait phases because these relationships are probably not linear. We used an artificial neural network to determine the weights associable to each factor for determining the ratio between gait phases and hence the harmony of walking. As expected, the gait ratio obtained as the ratio between stride duration and stance duration was found to be associated with walking speed and stride length, but also with hip muscle forces. These muscles could be important for exploiting the recovery of energy typical of the pendular mechanism of walking. Our study also highlighted that the results of an artificial neural network should be associated with a reliability analysis, being a non-deterministic approach. A good level of reliability was found for the findings of our study.

The Role of Walking Experience in the Emergence of Gait Harmony in Typically Developing Toddlers

The ability to walk without support usually develops in the first year of a typically developing toddler’s life and matures further in the following years. Mature walking is characterized by the correct timing of the different gait phases that make up a full gait cycle formed by stance, swing, and double support phases. The harmony of mature walking is given by a specific self-similar structure of the ratios between the durations of these phases (stride/stance, stance/swing, swing/double support), that in adults all converge to the golden ratio (phi, about 1.618). The aim of this longitudinal, prospective, experimental study was to investigate the evolution of this gait harmonic structure in the transition from supported to independent walking. In total, 27 children were recruited and recorded at various stages of locomotor development, ranging from neonatal stepping up to an independent walking experience of about six months. Differently from walking speed that progressively increased with age, the gait phase ratios started to converge to golden value only after the first independent steps, suggesting a relation to the maturation of the walking experience. The independent walking experience seems to represent a trigger for the evolution of a locomotor harmonic pattern in toddlers learning to walk.

Increased Trailing Limb Angle is Associated with Regular and Stable Trunk Movements in Patients with Hemiplegia

OBJECTIVES

In post-stroke patients, shifts in the center of gravity may affect joint movement patterns of the paraplegic lower limb during walking. The impact of changes in ankle dorsiflexion angle and trailing limb angle due to slight weight-shifting is unknown. This study aimed to investigate the effect of the abovementioned parameters on gait characteristics measured by trunk acceleration.

MATERIALS AND METHODS

During walking, the ankle dorsiflexion angle and trailing limb angle were assessed using two-dimensional motion analysis. Shifts in the center of gravity were assessed to evaluate symmetry, regularity, and sway of trunk movements by calculating the harmonic ratio, autocorrelation coefficient, and root mean square using a wearable trunk accelerometer.

RESULTS

Ankle dorsiflexion angle showed a significant negative correlation with the root mean square of the anteroposterior axis (r = -0.460, p = 0.005). Trailing limb angle was significantly correlated with the autocorrelation coefficient of the vertical axis (r = 0.585, p < 0.001) and root mean square of the vertical (r = -0.579, p < 0.001), mediolateral (r = -0.474, p = 0.004), and anteroposterior axes (r = -0.548, p = 0.001). Trailing limb angle was a significant predictor (autocorrelation coefficient vertical axis, p = 0.001; root mean square vertical axis, p = 0.001; mediolateral axis, p = 0.007; anteroposterior axis, p = 0.001).

CONCLUSIONS

Trailing limb angle can indicate the acquisition of forward propulsion during walking; an increase in it may contribute to improvements of the regular vertical movement ability and stability of the center of gravity sway.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

Modifications in Prefrontal Cortex Oxygenation in Linear and Curvilinear Dual Task Walking: A Combined fNIRS and IMUs Study

Increased oxygenated hemoglobin concentration of the prefrontal cortex (PFC) has been observed during linear walking, particularly when there is a high attention demand on the task, like in dual-task (DT) paradigms. Despite the knowledge that cognitive and motor demands depend on the complexity of the motor task, most studies have only focused on usual walking, while little is known for more challenging tasks, such as curved paths. To explore the relationship between cortical activation and gait biomechanics, 20 healthy young adults were asked to perform linear and curvilinear walking trajectories in single-task and DT conditions. PFC activation was assessed using functional near-infrared spectroscopy, while gait quality with four inertial measurement units. The Figure-of-8-Walk-Test was adopted as the curvilinear trajectory, with the "Serial 7s" test as concurrent cognitive task. Results show that walking along curvilinear trajectories in DT led to increased PFC activation and decreased motor performance. Under DT walking, the neural correlates of executive function and gait control tend to be modified in response to the cognitive resources imposed by the motor task. Being more representative of real-life situations, this approach to curved walking has the potential to reveal crucial information and to improve people' s balance, safety, and life's quality.

Effects of cognitive workload on heart and locomotor rhythms coupling

Different physiological signals could be coupled under specific conditions, in some cases related to pathologies or reductions in system complexity. Cardiac-locomotor synchronization (CLS) has been one of the most investigating coupling. The influence of a cognitive task on walking was investigated in dual-task experiments, but how different cognitive tasks may influence CLS has poorly been investigated. Twenty healthy subjects performed a dual-task walking (coupled with verbal fluency vs calculation) on a treadmill at three different speeds (comfortable speed CS; fast-speed: CS + 2 km/h; slow-speed: CS-2 km/h) while cardiac and walking rhythms were recorded using surface electrodes and a triaxial accelerometer, respectively. According to previous studies, we found a cognitive-motor interference for which cognitive performance was affected by motor exercise, but not vice-versa. We found a CLS at the baseline condition, at fast speed in both cognitive tasks, while at comfortable speed only for the verbal fluency task. In conclusion, the cardiac and locomotor rhythms were not coupled at slow speed and at comfortable speed during subtraction task. Cognitive performances generally increased at faster speed, when cardiac locomotor coupling was stronger.

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis

Background: Gait dysfunction or impairment is considered one of the most common and devastating physiological consequences of stroke, and achieving optimal gait is a key goal for stroke victims with gait disability along with their clinical teams. Many researchers have explored post stroke gait, including assessment tools and techniques, key gait parameters and significance on functional recovery, as well as data mining, modeling and analyses methods.

Research Question: This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.

Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.

Results and Significance: This scoping review aimed to shed light on tools and technologies employed in post stroke gait assessment toward bridging the existing gap between the research and clinical communities. Conventional qualitative gait analysis, typically used in clinics is mainly based on observational gait and is hence subjective and largely impacted by the observer's experience. Quantitative gait analysis, however, provides measured parameters, with good accuracy and repeatability for the diagnosis and comparative assessment throughout rehabilitation. Rapidly emerging smart wearable technology and AI, including Machine Learning, Support Vector Machine, and Neural Network approaches, are increasingly commanding greater attention in gait research. Although their use in clinical settings are not yet well leveraged, these tools promise a paradigm shift in stroke gait quantification, as they provide means for acquiring, storing and analyzing multifactorial complex gait data, while capturing its non-linear dynamic variability and offering the invaluable benefits of predictive analytics.

Artificial Neural Network Analyzing Wearable Device Gait Data for Identifying Patients With Stroke Unable to Return to Work

A potential dramatic effect of long-term disability due to stroke is the inability to return to work. An accurate prognosis and the identification of the parameters inflating the possibility of return to work after neurorehabilitation are crucial. Many factors may influence it, such as mobility and, in particular, walking ability. In this pilot study, two emerging technologies have been combined with the aim of developing a prognostic tool for identifying patients able to return to work: a wearable inertial measurement unit for gait analysis and an artificial neural network (ANN). Compared with more conventional statistics, the ANN showed a higher accuracy in identifying patients with respect to healthy subjects (90.9 vs. 75.8%) and also in identifying the subjects unable to return to work (93.9 vs. 81.8%). In this last analysis, the duration of double support phase resulted the most important input of the ANN. The potentiality of the ANN, developed also in other fields such as marketing on social networks, could allow a powerful support for clinicians that today should manage a large amount of instrumentally recorded parameters in patients with stroke.

Quantitative and Qualitative Running Gait Analysis through an Innovative Video-Based Approach

Quantitative and qualitative running gait analysis allows the early identification and the longitudinal monitoring of gait abnormalities linked to running-related injuries. A promising calibration- and marker-less video sensor-based technology (i.e., Graal), recently validated for walking gait, may also offer a time- and cost-efficient alternative to the gold-standard methods for running. This study aim was to ascertain the validity of an improved version of Graal for quantitative and qualitative analysis of running. In 33 healthy recreational runners (mean age 41 years), treadmill running at self-selected submaximal speed was simultaneously evaluated by a validated photosensor system (i.e., Optogait—the reference methodology) and by the video analysis of a posterior 30-fps video of the runner through the optimized version of Graal. Graal is video analysis software that provides a spectral analysis of the brightness over time for each pixel of the video, in order to identify its frequency contents. The two main frequencies of variation of the pixel’s brightness (i.e., F1 and F2) correspond to the two most important frequencies of gait (i.e., stride frequency and cadence). The Optogait system recorded step length, cadence, and its variability (vCAD, a traditional index of gait quality). Graal provided a direct measurement of F2 (reflecting cadence), an indirect measure of step length, and two indexes of global gait quality (harmony and synchrony index). The correspondence between quantitative indexes (Cadence vs. F2 and step length vs. Graal step length) was tested via paired t-test, correlations, and Bland–Altman plots. The relationship between qualitative indexes (vCAD vs. Harmony and Synchrony Index) was investigated by correlation analysis. Cadence and step length were, respectively, not significantly different from and highly correlated with F2 (1.41 Hz ± 0.09 Hz vs. 1.42 Hz ± 0.08 Hz, p = 0.25, r² = 0.81) and Graal step length (104.70 cm ± 013.27 cm vs. 107.56 cm ± 13.67 cm, p = 0.55, r² = 0.98). Bland–Altman tests confirmed a non-significant bias and small imprecision between methods for both parameters. The vCAD was 1.84% ± 0.66%, and it was significantly correlated with neither the Harmony nor the Synchrony Index (0.21 ± 0.03, p = 0.92, r² = 0.00038; 0.21 ± 0.96, p = 0.87, r² = 0.00122). These findings confirm the validity of the optimized version of Graal for the measurement of quantitative indexes of gait. Hence, Graal constitutes an extremely time- and cost-efficient tool suitable for quantitative analysis of running. However, its validity for qualitative running gait analysis remains inconclusive and will require further evaluation in a wider range of absolute and relative running intensities in different individuals.

The Effects of Combining Transcranial Direct Current Stimulation and Gait Training with Functional Electrical Stimulation on Trunk Acceleration During Walking in Patients with Subacute Stroke

OBJECTIVES

This study aimed to investigate whether the combination of transcranial direct current stimulation (tDCS) and gait training with FES affected walking speed and trunk accelerometry-based gait characteristics in patients with subacute stroke, compared with FES or tDCS gait training only.

MATERIALS AND METHODS

Stroke patients (n = 34; female 15; mean age, 72.5 ± 11.2 years; mean days poststroke, 38.7) with resultant paresis in the lower extremity (mean Fugl-Meyer score, 25.5) were enrolled. Patients were randomly assigned to one of three groups: combined anodal tDCS and gait training with FES (tDCS+FES, n = 11), anodal tDCS with gait training (tDCS, n = 11), or combined sham tDCS and gait training with FES (FES, n = 12). Participants received the intervention for 20 minutes and a 40-minute conventional rehabilitative intervention daily for a week. Patients' walking ability was evaluated using walking speed, harmonic ratio (HR), autocorrelation coefficient (AC), and root mean square (RMS) along each axis using a wearable trunk accelerometer.

RESULTS

The tDCS+FES group had a significantly greater change in AC in the anteroposterior axis and mediolateral axis than the FES and tDCS groups and FES group, respectively. There were no significant effects on walking speed or other parameters (HR and RMS) among the groups.

CONCLUSIONS

The combination of anodal tDCS and gait training with FES improved the post-stroke patients' gait regularity than FES gait training intervention only. Thus, combined tDCS and FES gait training, as a novel intervention, could be an important therapeutic tool in improving walking performance.

Functional Electrical Stimulation for Foot Drop in Post-Stroke People: Quantitative Effects on Step-to-Step Symmetry of Gait Using a Wearable Inertial Sensor

The main purpose of the present study was to assess the effects of foot drop stimulators (FDS) in individuals with stroke by means of spatio-temporal and step-to-step symmetry, harmonic ratio (HR), parameters obtained from trunk accelerations acquired using a wearable inertial sensor. Thirty-two patients (age: 56.84 ± 9.10 years; 68.8% male) underwent an instrumental gait analysis, performed using a wearable inertial sensor before and a day after the 10-session treatment (PRE and POST sessions). The treatment consisted of 10 sessions of 20 min of walking on a treadmill while using the FDS device. The spatio-temporal parameters and the HR in the anteroposterior (AP), vertical (V), and mediolateral (ML) directions were computed from trunk acceleration data. The results showed that time had a significant effect on the spatio-temporal parameters; in particular, a significant increase in gait speed was detected. Regarding the HRs, the HR in the ML direction was found to have significantly increased (+20%), while those in the AP and V directions decreased (approximately 13%). Even if further studies are necessary, from these results, the HR seems to provide additional information on gait patterns with respect to the traditional spatio-temporal parameters, advancing the assessment of the effects of FDS devices in stroke patients.

[Trunk kinematics during walking in stroke patients: A systematic review]

The trunk and pelvis are affected after stroke, predisposing individuals to falls and dependency. The aim of this review was to describe the lineal and angular kinematics of the trunk and pelvis in patients with post-stroke sequels during walking. We included studies published up to June 2018 using a 2-3 D motion capture system during walking. We searched the Cochrane, Medline, PEDRo, Lilacs, Scielo, EBSCO, ClinicalKey and Elsevier databases. Twelve articles were selected. Linear kinematics showed greater lateral displacement and acceleration in all axes. Angular kinematics in the swing phase of the paretic segment showed the pelvis in posterior rotation, with elevation and lower velocity and the trunk in anterior flexion, with lateral inclination and ipsilateral rotation. The studies showed wide variability, making it impossible to establish of a common effect. However, the results allow description of the movement of the trunk and pelvis.

Control of Linear Head and Trunk Acceleration During Gait After Unilateral Vestibular Deficits

OBJECTIVE

To use clinically available inertial measurement units to quantify the control of linear accelerations at the head and trunk during gait in different sensory conditions in individuals with unilateral vestibular loss.

DESIGN

Observational study.

SETTING

Outpatient research laboratory.

PARTICIPANTS

Individuals (n=13; mean age, 47.6±13.7y; 69% women) 6 weeks after vestibular schwannoma resection surgery and vestibular healthy participants (n=16; mean age, 29.7±5.9y; 56% women).

INTERVENTION

Not applicable.

MAIN OUTCOME MEASURES

Walking speed normalized, root mean square values of cranial-caudal, medial-lateral, and anterior-posterior directed linear accelerations at the head and the trunk while walking in 2 visual sensory conditions (eyes open and eyes closed).

RESULTS

Linear mixed models for each root mean square value were fit on the effects of group, condition, and group by condition. The group by condition effect was used to examine the primary hypothesis that individuals with vestibular loss would experience greater change in triplanar root mean square values at the head and trunk from the eyes open to eyes closed condition compared with the vestibular healthy group. The group by condition effect was found to be significant at the head in the cranial-caudal (β=0.39; P=.002), medial-lateral (β=0.41; P<.001), and anterior-posterior (β=0.43; P<.001) directions. The group by condition effect was also significant in the cranial-caudal (β=0.39; P=.002), medial-lateral (β=0.39; P<.001), and anterior-posterior (β=0.23; P=.002) directions at the trunk.

CONCLUSIONS

Participants who underwent vestibular schwannoma resection were more impaired in their ability to control accelerations at the head and trunk without visual sensory information than vestibular healthy participants. These impairments were detectable using clinically available inertial measurement units.

Sensorized Assessment of Dynamic Locomotor Imagery in People with Stroke and Healthy Subjects

Dynamic motor imagery (dMI) is a motor imagery task associated with movements partially mimicking those mentally represented. As well as conventional motor imagery, dMI has been typically assessed by mental chronometry tasks. In this paper, an instrumented approach was proposed for quantifying the correspondence between upper and lower limb oscillatory movements performed on the spot during the dMI of walking vs. during actual walking. Magneto-inertial measurement units were used to measure limb swinging in three different groups: young adults, older adults and stroke patients. Participants were tested in four experimental conditions: (i) simple limb swinging; (ii) limb swinging while imagining to walk (dMI-task); (iii) mental chronometry task, without any movement (pure MI); (iv) actual level walking at comfortable speed. Limb swinging was characterized in terms of the angular velocity, frequency of oscillations and sinusoidal waveform. The dMI was effective at reproducing upper limb oscillations more similar to those occurring during walking for all the three groups, but some exceptions occurred for lower limbs. This finding could be related to the sensory feedback, stretch reflexes and ground reaction forces occurring for lower limbs and not for upper limbs during walking. In conclusion, the instrumented approach through wearable motion devices adds significant information to the current dMI approach, further supporting their applications in neurorehabilitation for monitoring imagery training protocols in patients with stroke.

Smoothness of Gait in Healthy and Cognitively Impaired Individuals: A Study on Italian Elderly Using Wearable Inertial Sensor

The main purpose of the present study was to compare the smoothness of gait in older adults with and without cognitive impairments, using the harmonic ratio (HR), a metric derived from trunk accelerations. Ninety older adults aged over 65 (age: 78.9 ± 4.8 years; 62% female) underwent instrumental gait analysis, performed using a wearable inertial sensor and cognitive assessment with the Mini Mental State Examination (MMSE) and Addenbrooke’s Cognitive Examination Revised (ACE-R). They were stratified into three groups based on their MMSE performance: healthy controls (HC), early and advanced cognitive decline (ECD, ACD). The spatio-temporal and smoothness of gait parameters, the latter expressed through HR in anteroposterior (AP), vertical (V) and mediolateral (ML) directions, were derived from trunk acceleration data. The existence of a relationship between gait parameters and degree of cognitive impairment was also explored. The results show that individuals with ECD and ACD exhibited significantly slower speed and shorter stride length, as well as reduced values of HR in the AP and V directions compared to HC, while no significant differences were found between ECD and ACD in any of the investigated parameters. Gait speed, stride length and HR in all directions were found to be moderately correlated with both MMSE and ACE-R scores. Such findings suggest that, in addition to the known changes in gait speed and stride length, important reductions in smoothness of gait are likely to occur in older adults, owing to early/prodromal stages of cognitive impairment. Given the peculiar nature of these metrics, which refers to overall body stability during gait, the calculation of HR may result in being useful in improving the characterization of gait patterns in older adults with cognitive impairments.

Fifteen Years of Wireless Sensors for Balance Assessment in Neurological Disorders

Balance impairment is a major mechanism behind falling along with environmental hazards. Under physiological conditions, ageing leads to a progressive decline in balance control per se. Moreover, various neurological disorders further increase the risk of falls by deteriorating specific nervous system functions contributing to balance. Over the last 15 years, significant advancements in technology have provided wearable solutions for balance evaluation and the management of postural instability in patients with neurological disorders. This narrative review aims to address the topic of balance and wireless sensors in several neurological disorders, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, stroke, and other neurodegenerative and acute clinical syndromes. The review discusses the physiological and pathophysiological bases of balance in neurological disorders as well as the traditional and innovative instruments currently available for balance assessment. The technical and clinical perspectives of wearable technologies, as well as current challenges in the field of teleneurology, are also examined.

Signatures of knee osteoarthritis in women in the temporal and fractal dynamics of human gait

BACKGROUND

Osteoarthritis of the knee is characterized by progressive cartilage deterioration causing pain and function loss. Symptoms develop late with limited disease-modifying opportunities. Osteoarthritis is a major cause of immobility, with a higher prevalence above 60 years. This age-related increase in prevalence is further amplified by the female gender. Imaging and biochemical analyses for detection of osteoarthritis of the knee are expensive and labor-intensive. Continuous movement tracking could aid in detecting onset and/or worsening of symptoms.

METHODS

We used portable technology to investigate kinematic differences in female patients with knee osteoarthritis, weight-matched healthy female volunteers and obese female patients with osteoarthritis of the knee. Knee osteoarthritis was established radiographically and corroborated using magnetic resonance imaging.

FINDINGS

The total amount, type and level of activity did not differ significantly between groups. The temporal activity pattern during the day was however significantly different with a bimodal signature in healthy volunteers only. Sequence analyses revealed more time to recuperate after dynamic activity in both patient groups. Analysis of walking bouts revealed significant differences in stride interval dynamics, indicative of gait naturalness, only in healthy volunteers. Temporal activity, sequence and walking patterns were independent of body weight.

INTERPRETATION

We thus provide for the first-time evidence of temporal specific kinematic signatures in amount and quality of movement also in stride interval dynamics between people with and without osteoarthritis of the knee independent of body weight. These findings could allow early and non-intrusive diagnosis of osteoarthritis enabling concordant treatment.

Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk

Asymmetry is a cardinal symptom of gait post-stroke that is targeted during rehabilitation. Technological developments have allowed accelerometers to be a feasible tool to provide digital gait variables. Many acceleration-derived variables are proposed to measure gait asymmetry. Despite a need for accurate calculation, no consensus exists for what is the most valid and reliable variable. Using an instrumented walkway (GaitRite) as the reference standard, this study compared the validity and reliability of multiple acceleration-derived asymmetry variables. Twenty-five post-stroke participants performed repeated walks over GaitRite whilst wearing a tri-axial accelerometer (Axivity AX3) on their lower back, on two occasions, one week apart. Harmonic ratio, autocorrelation, gait symmetry index, phase plots, acceleration, and jerk root mean square were calculated from the acceleration signals. Test-retest reliability was calculated, and concurrent validity was estimated by comparison with GaitRite. The strongest concurrent validity was obtained from step regularity from the vertical signal, which also recorded excellent test-retest reliability (Spearman's rank correlation coefficients (rho) = 0.87 and Intraclass correlation coefficient (ICC21) = 0.98, respectively). Future research should test the responsiveness of this and other step asymmetry variables to quantify change during recovery and the effect of rehabilitative interventions for consideration as digital biomarkers to quantify gait asymmetry.

Effects of mechanical assistance on muscle activity and motor performance during isometric elbow flexion

Mechanical assistance on joint movement is generally beneficial; however, its effects on cooperative performance and muscle activity needs to be further explored. This study examined how motor performance and muscle activity are altered when mechanical assistance is provided during isometric force control of ramp-down and hold phases. Thirteen right-handed participants (age: 24.7 ± 1.8 years) performed trajectory tracking tasks. Participants were asked to maintain the reference magnitude of 47 N (REF) during isometric elbow flexion. The force was released to a step-down magnitude of either 75% REF or 50% REF and maintained, with and without mechanical assistance. The ramp-down durations of force release were set to 0.5, 2.5, or 5.0 s. Throughout the experiment, we measured the following: (1) the force output using load cells to compute force variability and overshoot ratio; (2) peak perturbation on the elbow movement using an accelerometer; (3) the surface electromyography (sEMG) from biceps brachii and triceps brachii muscles; and (4) EMG oscillation from the biceps brachii muscle in the bandwidth of 15-45 Hz. Our results indicated that mechanical assistance, which involved greater peak perturbation, demonstrated lower force variability than non-assistance (p < 0.01), while EMG oscillation in the biceps brachii muscle from 15 to 45 Hz was increased (p < 0.05). These findings imply that if assistive force is provided during isometric force control, the central nervous system actively tries to stabilize motor performance by controlling specific motor unit activity in the agonist muscle.

The relationship between trunk acceleration parameters and kinematic characteristics during walking in patients with stroke

[Purpose] Limited literature has investigated the relationships between acceleration-based gait characteristics and kinematic information from motion analysis systems in gait analysis. The purpose of this study is to determine whether acceleration-based gait characteristics were associated with gait characteristics by motion analysis systems in patients with stroke. [Participants and Methods] Seventeen patients with stroke walked along a 10-m-long walkway at their comfortable speed. Trunk acceleration was measured with an accelerometer. Several reflective markers over bony landmarks on the lower extremities were used to capture movements. We evaluated the correlations of variables calculated between the trunk accelerometers and the motion analysis system. [Results] Walking speed was positively correlated with harmonic ratios along the anteroposterior axis and stride regularity along the vertical and anteroposterior axes. Harmonic ratios were associated with the stance phase percent on the unaffected side. Stride regularity was associated with the stance phase percent on both sides. Smaller interstride variability was associated with smaller peak ankle plantarflexion during both phases and greater peak ankle dorsiflexion during swing phase. Stride regularity is positively associated with maximal knee flexion during swing phase. [Conclusion] Relationships with spatiotemporal and joint kinematic parameters from the motion analysis system support the potential use of accelerometers.

Instrumented Version of the Modified Dynamic Gait Index in Patients With Neurologic Disorders

BACKGROUND

Gait instability is common in adults with neurologic disorders and the modified Dynamic Gait Index (mDGI) was recently introduced to assess dynamic balance. However, instrumental assessment is needed to provide quantitative measures.

OBJECTIVE

To develop and validate an instrumented version of the mDGI.

DESIGN

Cross-sectional study.

SETTING

Clinical setting.

PARTICIPANTS

Thirty adults with neurologic disorders (10 with multiple sclerosis, 10 with Parkinson disease, and 10 with stroke) and 20 healthy volunteers.

METHODS

Participants were assessed with the Timed Up and Go test (TUG) and with the mDGI. During the assessment of mDGI, data were collected by a single Inertial Measurement Unit (IMU) positioned on the sternum. Principal component analysis (PCA) was performed on the instrumented data extracting eight PC scores (ImPC) describing dynamic balance. The instrumented overall score (ImDGI) was then calculated as the sum of the mPCs. PCA revealed two components associated with stride features and regularity (ImDGI_Gait_Pattern) and trunk movements (ImDGI_Trunk_Sway). Spearman coefficients were calculated between mDGI and ImDGI, whereas Mann-Whitney (U) and Kruskal-Wallis (H) tests assessed differences between groups and neurologic conditions.

MAIN OUTCOME MEASUREMENTS

ImDGI.

RESULTS

ImDGI did not show ceiling effects, and good correlations were found between ImDGI and mDGI (r = .84), and TUG (r = .84) for people with neurologic disorders (P < .001). Significant differences among pathologies (H test₍₂₎ =12.5, P = .002) and between healthy participants and adults with neurologic disorders (U test = 47.0, P = .001) were found. ImDGI_Trunk_Sway discriminated between people using or not using walking aids and among the three pathologies (H₍₂₎ = 10.0, P = .007).

CONCLUSIONS

The ImDGI test seems to provide valid measures to objectively assess dynamic balance in neurologic conditions and possibly quantify balance deficits also in adults with neurologic disorders.

Three-Dimensional Human Gait Pattern: Reference Data for Young, Active Women Walking with Low, Preferred, and High Speeds

Normal gait pattern is the key component in the investigation of pathological gait patterns. In computer motion analysis there is a need to include data from participants with different somatic structures to develop a normative database or to limit the database results to a specific population. The aim of this study was to determine kinematic gait patterns for young, active women walking with low, preferred, and self-selected speeds with regard to their somatic characteristics. Laboratory-based gait analysis was performed on 1320 gait cycles taken from 20 young, active women walking with three different speeds. Comprehensive anthropometric measurements and descriptive statistics were used to describe spatiotemporal and angular variables at each walking condition. The results demonstrated some significant differences in young, active women walking between different speeds and compared to the literature. This suggests that there is a need to include data from participants with different somatic structures to develop a normative database or limit the database results to a specific population. Detailed linear and angular kinematic variables allow for proper adjustment of parameters depending on the gait speed of people with locomotion disorders.

Instrumental Assessment of Stair Ascent in People With Multiple Sclerosis, Stroke, and Parkinson's Disease: A Wearable-Sensor-Based Approach

Stair ascent is a challenging daily-life activity highly related to independence. This task is usually assessed with clinical scales suffering from partial subjectivity and limited detail in evaluating different task aspects. In this paper, we instrumented the assessment of stair ascent in people with multiple sclerosis (MS), stroke (ST), and Parkinson's disease (PD) to analyze the validity of the proposed quantitative indexes and characterize subjects' performances. Participants climbed 10 steps wearing a magneto-inertial sensor [magneto-inertial measurement unit (MIMU)] at sternum level. Gait pattern features (step frequency, symmetry, regularity, and harmonic ratios), and upper trunk sway were computed from MIMU signals. Clinical modified dynamic gait index (mDGI) and mDGI-Item 8 "Up stairs" were administered. Significant correlations with clinical scores were found for gait pattern features ( ) and trunk pitch sway ( ) demonstrating their validity. Instrumental indexes showed alterations in the three pathological groups compared to healthy subjects and significant differences, not clinically detected, among MS, ST, and PD. MS showed the worst performance, with alterations of all gait pattern aspects and larger trunk pitch sway. ST showed worsening in gait pattern features but not in trunk motion. PD showed fewer alterations consisting in reduced step frequency and trunk yaw sway. These results suggest that the use of an MIMU provided valid objective indexes revealing between-group differences in stair ascent not detected by clinical scales. Importantly, the indexes include upper trunk measures, usually not present in clinical tests, and provide relevant hints for tailored rehabilitation.

Multiple-Wearable-Sensor-Based Gait Classification and Analysis in Patients with Neurological Disorders

The aim of this study was to conduct a comprehensive analysis of the placement of multiple wearable sensors for the purpose of analyzing and classifying the gaits of patients with neurological disorders. Seven inertial measurement unit (IMU) sensors were placed at seven locations: the lower back (L5) and both sides of the thigh, distal tibia (shank), and foot. The 20 subjects selected to participate in this study were separated into two groups: stroke patients (11) and patients with neurological disorders other than stroke (brain concussion, spinal injury, or brain hemorrhage) (9). The temporal parameters of gait were calculated using a wearable device, and various features and sensor configurations were examined to establish the ideal accuracy for classifying different groups. A comparison of the various methods and features for classifying the three groups revealed that a combination of time domain and gait temporal feature-based classification with the Multilayer Perceptron (MLP) algorithm outperformed the other methods of feature-based classification. The classification results of different sensor placements revealed that the sensor placed on the shank achieved higher accuracy than the other sensor placements (L5, foot, and thigh). The placement-based classification of the shank sensor achieved 89.13% testing accuracy with the Decision Tree (DT) classifier algorithm. The results of this study indicate that the wearable IMU device is capable of differentiating between the gait patterns of healthy patients, patients with stroke, and patients with other neurological disorders. Moreover, the most favorable results were reported for the classification that used the combination of time domain and gait temporal features as the model input and the shank location for sensor placement.

Watch your step! Who can recover stair climbing independence after stroke?

BACKGROUND

After discharge, most patients who have suffered a stroke remain with some limitations in their stair climbing ability. This is a critical factor in order to be independent in real-life mobility. Although there are several studies on prognostic factors for gait recovery, few of them have focused on the recovery of stair climbing.

AIM

The aim of this study was to identify prognostic risk factors for the recovery of stair climbing ability in a large sample of subjects with subacute stroke.

DESIGN

Observational study.

SETTING

Neurorehabilitation Inpatient Unit.

POPULATION

Subjects within the first month after stroke that had been admitted to an inpatient rehabilitation unit and discharged after an intensive inpatient rehabilitation.

METHODS

Demographical and clinical data were collected. Barthel Index (BI), Trunk Control Test and Motricity Index (MI) scores were recorded at admission and at discharge. Patients received two daily 40-minute sessions of motor rehabilitation, six days per week, during approximately two months. Forward Binary Logistic regressions were used to identify the role of risk factors, using as dependent variables the recovery of stair climbing ability and walking ability at discharge. As independent variables we used age, gender, onset-to-admission interval, side of hemiparesis, trunk control, Motricity Index (MI), presence of obesity, presence of neglect, presence of depression, classification of cerebral infarction (total anterior circulation, partial anterior circulation, posterior circulation or lacunar infarcts), degree of independence in activities of daily living, and cognitive state, all assessed at admission.

RESULTS

A total of 257 subjects were enrolled. BI-Score, MI-Score and presence of unilateral spatial neglect at admission were able to explain 83% of variance for the recovery of stair climbing ability. Subjects with a BI >40 at admission were about 17 times more likely to be able to climb stairs again than other patients, and those with MI ≥25 were about 9 times more likely than the rest. The presence of unilateral spatial neglect reduced this possibility of recovering stair climbing ability by about 5.5 times. Of these factors, only MI ≥25, together with a score at Trunk Control Test >12, significantly predicted also walking recovery.

CONCLUSIONS

This study highlights the different prognostic factors for recovering stair climbing and walking abilities, with a major role of unilateral spatial neglect in the former.

CLINICAL REHABILITATION IMPACT

There is a need for specific rehabilitation of stair climbing, also for improving the independence in activities of daily living, especially in patients who the clinical staff already knows should manage stairs in their community after being discharged.

Evaluation of gait symmetry using a tri-axial accelerometer in stroke patients

OBJECTIVES

The purpose of this study was to confirm the intra-rater reliability and absolute reliability of Lissajous Index (LI) in evaluating the symmetry of trunk movement during gait in patients with stroke and to examine the relation between LI and body function in patients with stroke.

METHODS

Twenty-one healthy subjects (11 males and 10 females, age 63.3±2.0 yrs) and 45 patients with stroke (33 males and 12 females, age 58.7±13.4 yrs) were included in the study. The accelerometer was fixed to a belt at the level of the L3 spinous process. The 10-m walk test was performed twice to record definitive data on trunk acceleration. LI was calculated from trunk accelerations. We confirmed the intra-rater reliability and absolute reliability of LI in patients with stroke and we examined the relation between LI and body function in patients with stroke.

RESULTS

There was no fixed bias and proportional bias in the LI of patients with stroke. It was found that BBS significantly correlated with LI in stroke patients (p < 0.05, r = -0.413).

CONCLUSIONS

It was clear that LI during gait was effective at evaluating gait symmetry and balance. LI was indicated to be useful in evaluating gait in patients with stroke.

Golden Gait: An Optimization Theory Perspective on Human and Humanoid Walking

Human walking is a complex task which includes hundreds of muscles, bones and joints working together to deliver harmonic movements with the need of finding equilibrium between moving forward and maintaining stability. Many different computational approaches have been used to explain human walking mechanisms, from pendular model to fractal approaches. A new perspective can be gained from using the principles developed in the field of Optimization theory and in particularly the branch of Game Theory. In particular we provide a new insight into human walking showing as the trade-off between advancement and equilibrium managed during walking has the same solution of the Ultimatum game, one of the most famous paradigms of game theory, and this solution is the golden ratio. The golden ratio is an irrational number that was found in many biological and natural systems self-organized in a harmonic, asymmetric, and fractal structure. Recently, the golden ratio has also been found as the equilibrium point between two players involved into the Ultimatum Game. It has been suggested that this result can be due to the fact that the golden ratio is perceived as the fairest asymmetric solution by the two players. The golden ratio is also the most common proportion between stance and swing phase of human walking. This approach may explain the importance of harmony in human walking, and provide new perspectives for developing quantitative assessment of human walking, efficient humanoid robotic walkers, and effective neurorobots for rehabilitation.

Brain lesions affecting gait recovery in stroke patients

OBJECTIVES

Gait recovery is an important goal in stroke patients. Several studies have sought to uncover relationships between specific brain lesions and the recovery of gait, but the effects of specific brain lesions on gait remain unclear. Thus, we investigated the effects of stroke lesions on gait recovery in stroke patients.

MATERIALS AND METHODS

In total, 30 subjects with stroke were assessed in a retrograde longitudinal observational study. To assess gait function, the functional ambulation category (FAC) was tested four times: initially (within 2 weeks) and 1, 3, and 6 months after the onset of the stroke. Brain lesions were analyzed via overlap, subtraction, and voxel-based lesion symptom mapping (VLSM).

RESULTS

Ambulation with FAC improved significantly with time. Subtraction analysis showed that involvement of the corona radiata, internal capsule, globus pallidus, and putamen were associated with poor recovery of gait throughout 6 months after onset. The caudate nucleus did influence poor recovery of gait at 6 months after onset. VLSM revealed that corona radiata, internal capsule, globus pallidus, putamen and cingulum were related with poor recovery of gait at 3 months after onset. Corona radiata, internal capsule, globus pallidus, putamen, primary motor cortex, and caudate nucleus were related with poor recovery of gait at 6 months after onset.

CONCLUSION

Results identified several important brain lesions for gait recovery in patients with stroke. These results may be useful for planning rehabilitation strategies for gait and understanding the prognosis of gait in stroke patients.

Harmony as a convergence attractor that minimizes the energy expenditure and variability in physiological gait and the loss of harmony in cerebellar ataxia

BACKGROUND

The harmony of the human gait was recently found to be related to the golden ratio value (ϕ). The ratio between the duration of the stance and that of the swing phases of a gait cycle was in fact found to be close to ϕ, which implies that, because of the fractal property of autosimilarity of that number, the gait ratios stride/stance, stance/swing, swing/double support, were not significantly different from one another. We studied a group of patients with cerebellar ataxia to investigate how the differences between their gait ratios and the golden ratio are related to efficiency and stability of their gait, assessed by energy expenditure and stride-to-stride variability, respectively.

METHODS

The gait of 28 patients who were affected by degenerative cerebellar ataxia and of 28 healthy controls was studied using a stereophotogrammetric system. The above mentioned gait ratios, the energy expenditure estimated using the pelvis reconstructed method and the gait variability in terms of the stride length were computed, and their relationships were analyzed. Matching procedures have also been used to avoid multicollinearity biases.

FINDINGS

The gait ratio values of the patients were farther from the controls (and hence from ϕ), even in speed matched conditions (P=0.011, Cohen's D=0.76), but not when the variability and energy expenditure were matched between the two groups (Cohen's D=0.49). In patients with cerebellar ataxia, the farther the stance-swing ratio was from ϕ, the larger the total mechanical work (R²_adj=0.64). Further, a significant positive correlation was observed between the difference of the gait ratio from the golden ratio and the severity of the disease (R=0.421, P=0.026).

INTERPRETATION

Harmony of gait appears to be a benchmark of physiological gait leading to physiological energy recovery and gait reliability. Neurorehabilitation of patients with ataxia might benefit from the restoration of harmony of their locomotor patterns.

Multi-sensor assessment of dynamic balance during gait in patients with subacute stroke

The capacity to maintain upright balance by minimising upper body oscillations during walking, also referred to as gait stability, has been associated with a decreased risk of fall. Although it is well known that fall is a common complication after stroke, no study considered the role of both trunk and head when assessing gait stability in this population. The primary aim of this study was to propose a multi-sensor protocol to quantify gait stability in patients with subacute stroke using gait quality indices derived from pelvis, sternum, and head accelerations. Second, the association of these indices with the level of walking ability, with traditional clinical scale scores, and with fall events occurring within the six months after patients' dismissal was investigated. The accelerations corresponding to the three abovementioned body levels were measured using inertial sensors during a 10-Meter Walk Test performed by 45 inpatients and 25 control healthy subjects. A set of indices related to gait stability were estimated and clinical performance scales were administered to each patient. The amplitude of the accelerations, the way it is attenuated/amplified from lower to upper body levels, and the gait symmetry provide valuable information about subject-specific motor strategies, discriminate between different levels of walking ability, and correlate with clinical scales. In conclusion, the proposed multi-sensor protocol could represent a useful tool to quantify gait stability, support clinicians in the identification of patients potentially exposed to a high risk of falling, and assess the effectiveness of rehabilitation protocols in the clinical routine.