Observational Study of 180° Turning Strategies Using Inertial Measurement Units and Fall Risk in Poststroke Hemiparetic Patients

Cautious Gait during Navigational Tasks in People with Hemiparesis: An Observational Study

Locomotor and balance disorders are major limitations for subjects with hemiparesis. The Timed Up and Go (TUG) test is a complex navigational task involving oriented walking and obstacle circumvention. We hypothesized that subjects with hemiparesis adopt a cautious gait during complex locomotor tasks. The primary aim was to compare spatio-temporal gait parameters, indicators of cautious gait, between the locomotor subtasks of the TUG (Go, Turn, Return) and a Straight-line walk in people with hemiparesis. Our secondary aim was to analyze the relationships between TUG performance and balance measures, compare spatio-temporal gait parameters between fallers and non-fallers, and identify the biomechanical determinants of TUG performance. Biomechanical parameters during the TUG and Straight-line walk were analyzed using a motion capture system. A repeated measures ANOVA and two stepwise ascending multiple regressions (with performance variables and biomechanical variables) were conducted. Gait speed, step length, and % single support phase (SSP) of the 29 participants were reduced during Turn compared to Go and Return and the Straight-line walk, and step width and % double support phase were increased. TUG performance was related to several balance measures. Turn performance (R2 = 63%) and Turn trajectory deviation followed by % SSP on the paretic side and the vertical center of mass velocity during Go (R2 = 71%) determined TUG performance time. People with hemiparesis adopt a cautious gait during complex navigation at the expense of performance.

Automatic gait events detection with inertial measurement units: healthy subjects and moderate to severe impaired patients

BACKGROUND

Recently, the use of inertial measurement units (IMUs) in quantitative gait analysis has been widely developed in clinical practice. Numerous methods have been developed for the automatic detection of gait events (GEs). While many of them have achieved high levels of efficiency in healthy subjects, detecting GEs in highly degraded gait from moderate to severely impaired patients remains a challenge. In this paper, we aim to present a method for improving GE detection from IMU recordings in such cases.

METHODS

We recorded 10-meter gait IMU signals from 13 healthy subjects, 29 patients with multiple sclerosis, and 21 patients with post-stroke equino varus foot. An instrumented mat was used as the gold standard. Our method detects GEs from filtered acceleration free from gravity and gyration signals. Firstly, we use autocorrelation and pattern detection techniques to identify a reference stride pattern. Next, we apply multiparametric Dynamic Time Warping to annotate this pattern from a model stride, in order to detect all GEs in the signal.

RESULTS

We analyzed 16,819 GEs recorded from healthy subjects and achieved an F1-score of 100%, with a median absolute error of 8 ms (IQR [3-13] ms). In multiple sclerosis and equino varus foot cohorts, we analyzed 6067 and 8951 GEs, respectively, with F1-scores of 99.4% and 96.3%, and median absolute errors of 18 ms (IQR [8-39] ms) and 26 ms (IQR [12-50] ms).

CONCLUSIONS

Our results are consistent with the state of the art for healthy subjects and demonstrate a good accuracy in GEs detection for pathological patients. Therefore, our proposed method provides an efficient way to detect GEs from IMU signals, even in degraded gaits. However, it should be evaluated in each cohort before being used to ensure its reliability.

Innovative multidimensional gait evaluation using IMU in multiple sclerosis: introducing the semiogram

Background

Quantifying gait using inertial measurement units has gained increasing interest in recent years. Highly degraded gaits, especially in neurological impaired patients, challenge gait detection algorithms and require specific segmentation and analysis tools. Thus, the outcomes of these devices must be rigorously tested for both robustness and relevancy in order to recommend their routine use. In this study, we propose a multidimensional score to quantify and visualize gait, which can be used in neurological routine follow-up. We assessed the reliability and clinical coherence of this method in a group of severely disabled patients with progressive multiple sclerosis (pMS), who display highly degraded gait patterns, as well as in an age-matched healthy subjects (HS) group.

Methods

Twenty-two participants with pMS and nineteen HS were included in this 18-month longitudinal follow-up study. During the follow-up period, all participants completed a 10-meter walk test with a U-turn and back, twice at M0, M6, M12, and M18. Average speed and seven clinical criteria (sturdiness, springiness, steadiness, stability, smoothness, synchronization, and symmetry) were evaluated using 17 gait parameters selected from the literature. The variation of these parameters from HS values was combined to generate a multidimensional visual tool, referred to as a semiogram.

Results

For both cohorts, all criteria showed moderate to very high test-retest reliability for intra-session measurements. Inter-session quantification was also moderate to highly reliable for all criteria except smoothness, which was not reliable for HS participants. All partial scores, except for the stability score, differed between the two populations. All partial scores were correlated with an objective but not subjective quantification of gait severity in the pMS population. A deficit in the pyramidal tract was associated with altered scores in all criteria, whereas deficits in cerebellar, sensitive, bulbar, and cognitive deficits were associated with decreased scores in only a subset of gait criteria.

Conclusions

The proposed multidimensional gait quantification represents an innovative approach to monitoring gait disorders. It provides a reliable and informative biomarker for assessing the severity of gait impairments in individuals with pMS. Additionally, it holds the potential for discriminating between various underlying causes of gait alterations in pMS.

Sensor based assessment of turning during instrumented Timed Up and Go Test for quantifying mobility in chronic stroke patients

BACKGROUND

Turning may be particularly challenging for stroke patients leading to decreased mobility and increased functional restriction. Timed up and go instrumentation using a simple technology in the clinical context could allow for the collection of both traditional and potentially more discriminatory variables in turning ability.

AIM

Determine whether the speed turning metrics obtained by a single inertial sensor are suitable for differentiating between stroke patients with varying levels of mobility and disability.

DESIGN

Cross-sectional study.

SETTING

Outpatients setting.

POPULATION

Chronic stroke patients.

METHODS

A total of 48 chronic stroke patients and 23 healthy controls were included. Stroke patients were divided in two groups based on the total iTUG score: an impaired mobility (> 20 seconds) and an available mobility (<20 seconds) group. All subjects performed an instrumented Timed Up and Go (iTUG) wearing a single IMU sensor on the lower back. Time of subcomponents of the timed up and go test and kinematic parameters of turning were quantified. Other clinical outcomes were: 10 meters walk test, Functional Ambulation Categories Scale (FAC), the Rivermead Mobility Index (RMI), Modified Rankin Scale and the Saltin-Grimby Physical Activity Level Scale (SGPALS).

RESULTS

There were significant differences (P<0.01) in iTUG phases and turning speeds among groups. Low to strong significant correlations were found between measures derived from the turning speeds and clinical measures. The area under the curve (AUC) of Receiver Operating Characteristic (ROC) turning speeds was demonstrated to be able to discriminate (AUC: 0.742-0.912) from available to impaired stroke patients.

CONCLUSIONS

This study provides evidence that turning speeds during timed up and go test are accurate measures of mobility and capable of discriminating stroke patients with impaired mobility from those with normal mobility.

CLINICAL REHABILITATION IMPACT

The turning metrics are related to impairment and mobility in chronic stroke patients; hence they are important to include during clinical evaluation and may assist in creating a customized strategy, assess potential treatments, and effectively organize recovery.

Preventing falls: the use of machine learning for the prediction of future falls in individuals without history of fall

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experience falls whose consequences may accelerate the deterioration of their quality of life (injuries, fear of falling, reduction of physical activity). In that context, detecting frailty and high risk of fall at an early stage is the first line of defense against the detrimental consequences of fall. The second line of defense would be to develop original protocols to detect future fallers before any fall occur. This paper briefly summarizes the current advancements and perspectives that may arise from the combination of affordable and easy-to-use non-wearable systems (force platforms, 3D tracking motion systems), wearable systems (accelerometers, gyroscopes, inertial measurement units-IMUs) with appropriate machine learning analytics, as well as the efforts to address these challenges.

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.

Turning assessment for discrimination of frailty syndrome among community-dwelling older adults

BACKGROUND

Frailty is a common geriatric syndrome and is characterized by decreased physiological reserve and increased vulnerability towards adverse health outcomes including falls. Turning is a challenging task and is reported to be one of the daily activities that leads to falling in older populations.

RESEARCH QUESTION

Does 180° walking turns and 360° turning on the spot differ among frail, pre-frail, and non-frail older adults? Can 180° walking turns and 360° turning on the spot cutoffs discriminate older adults with frailty from those without?

METHODS

A cross-sectional study was conducted on community-dwelling older adults aged over 65 years. Frailty was assessed using Fried's phenotype method, and turning tasks were measured by inertial sensors. The turn duration (s) and angular velocity (°/s) were recorded for analysis.

RESULTS

In total, 109 participants were enrolled including 50 pre-frail and 12 frail individuals. Frail older adults took significantly longer and had slower angular velocities to complete the 180° and 360° turning than did either pre-frail (p = 0.002 and p < 0.001, respectively) or non-frail (p = 0.03 and p < 0.001, respectively) older adults. Cutoff times of 2.45 and 3.46 s were found to best discriminate frail people from those without frailty in both the 180° (sensitivity 83.3 %, specificity 71.1 %, area under the receiver operating characteristic curve (AUC) 0.796) and 360° (sensitivity 91.7 %, specificity 74.2 %, AUC 0.857) turn tasks.

SIGNIFICANCE

Older individuals with frailty syndrome had difficulty turning as evidenced by a longer turning duration and a slower angular velocity. The turn duration could be a potential biomarker of frailty in older populations. Assessing the turning performance can facilitate early detection of the onset of frailty and inform early prevention and rehabilitation interventions in clinical practice.

Comparison of 360° Turn Cycles among Individuals after Stroke and Healthy Older Adults

Stroke survivors are at high risk of falling during turning. The kinematics of performing a 360° turn have not been fully analyzed among individuals after stroke. Quantitative differences in the parameters of turning between healthy older adults and those after stroke could provide detailed information on turning ability among these groups. The purpose of the current study was to characterize differences between healthy older adults and adults after stroke in 360° turn kinematics. Fourteen individuals with chronic stroke (mean age: 69 ± 8.4 years) and 14 healthy older adults (mean age: 74 ± 8.7 years) performed three trials of 360° turning. Kinematics data were collected using 26 reflective markers at several body landmarks. This new method for quantifying turning revealed that stroke significantly affected the number of turn cycles, number of single support (SS) critical phases, and critical time. In some cases, falls among individuals with stroke may be related to the combination of impaired movement patterns and the complexity of tasks such as turning. Understanding turning kinematics can inform clinical interventions targeting improvements in turning ability and consequently, fall risk reduction in individuals after stroke.

Gait analysis in neurological populations: Progression in the use of wearables

Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies and provide limitations and possible future directions in the field of gait assessment. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial and EMG based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature.

Turning duration and steps predict future falls in poststroke hemiplegic individuals: A preliminary cohort study

Introduction: Turning was reported as one of the activities that most frequently leads to falling among stroke patients. This study investigated whether the duration and steps of a 180° turn while walking can distinguish retrospective fallers from non-fallers and predict future falls in a 1-year period in patients with poststroke hemiplegia. Methods: Thirty stroke patients were recruited. They were instructed to get up from a chair, walk straight 3 m, turn around, and return to seated position to assess the 180° walking-turn task. Turning performance was measured by two inertial sensor units of Physilog. Turn duration and steps were recorded for analysis. The numbers of retrospective and prospective falls were also obtained. Results: No significant difference was observed between retrospective stroke fallers and non-fallers in turn duration and steps. Turn duration and steps were significantly greater in prospective stroke fallers than in non-fallers. The cutoff turn duration of 4 s (area under the curve 0.75, 95% CI: 0.56-0.93, sensitivity 67%, specificity 80%, p =.04) and turn step of 7 steps (area under the curve 0.73, 95% CI: 0.51-0.94, sensitivity 56%, specificity 85%, p =.05) were found to most accurately predict prospective stroke fallers from non-fallers. Conclusions: Turn duration and steps were unable to discriminate between retrospective fallers and non-fallers but could predict prospective falls in patients with stroke. More than 4 s or 7 steps to complete a 180° turn while walking can be a predictor for patients with stroke at an increased risk of falling.

Can We Accurately Measure Axial Segment Coordination during Turning Using Inertial Measurement Units (IMUs)?

Camera-based 3D motion analysis systems are considered to be the gold standard for movement analysis. However, using such equipment in a clinical setting is prohibitive due to the expense and time-consuming nature of data collection and analysis. Therefore, Inertial Measurement Units (IMUs) have been suggested as an alternative to measure movement in clinical settings. One area which is both important and challenging is the assessment of turning kinematics in individuals with movement disorders. This study aimed to validate the use of IMUs in the measurement of turning kinematics in healthy adults compared to a camera-based 3D motion analysis system. Data were collected from twelve participants using a Vicon motion analysis system which were compared with data from four IMUs placed on the forehead, middle thorax, and feet in order to determine accuracy and reliability. The results demonstrated that the IMU sensors produced reliable kinematic measures and showed excellent reliability (ICCs 0.80-0.98) and no significant differences were seen in paired t-tests in all parameters when comparing the two systems. This suggests that the IMU sensors provide a viable alternative to camera-based motion capture that could be used in isolation to gather data from individuals with movement disorders in clinical settings and real-life situations.

Gait turning patterns in chronic ischemic stroke males and its relationship to recovery: A cross-sectional study

INTRODUCTION

Impaired turning patterns have been considered as 1 factor which potentially leads to disability in chronic stroke patients. Mobility comprises 80% of the chief disability, and would eventually lead to falls. Expanded Timed Up and Go (ETUG) is an effective mobility assessment method. It utilizes video recording to analyze the conventional Time Up and Go (TUG) Test components, which includes turning pattern analysis.

METHODS

Six healthy males without stroke history and 21 chronic ischemic stroke males (divided into subjects with or without the presence of flexor synergy pattern subgroups) capable of independent ambulation were recruited from Neurology and Medical Rehabilitation Department outpatient clinic. ETUG tests were recorded for each subject and were analyzed thoroughly using a computer program.

RESULTS

Timed Up and Go time was significantly different between the 3 groups (P = .001). As compared to control, and synergy absent group, median turning time was highest in chronic stroke patients with presence of flexor synergy by 2786 ms (P = .002), but was not significantly different in percentage ETUG (14%, P = .939). Further analysis revealed that Brunnstrom stage and number of steps taken for turning significantly affect TUG duration. Other factors such as hemiparetic side, or body height were not significantly associated.

DISCUSSION

The presence of flexor synergy would significantly affect turning time, this would then correlate to the disability of shifting body's center of gravity, as a part of the Stroke core set of International Classification of Functioning, Disability, and Health (ICF).Therefore, stroke patients need to have early ambulatory training regarding pivoting motion rather than solely focusing on straight walking. Instead of hemiparetic side, it is possible that overall turning time is affected by coordination and orientation capability, signifying the importance of cortical plasticity.

Value of gait analysis for measuring disease severity using inertial sensors in patients with multiple sclerosis: protocol for a systematic review and meta-analysis

BACKGROUND

Gait impairment is a hallmark of multiple sclerosis (MS) which significantly endangers the quality of life of the individual. Inertial measurement units (IMUs) are small, light wearable sensors that can be used in routine neurological practice. InertiaLocoGraphy (ILG), the quantification of gait with IMUs, has proven useful to detect early changes in MS undetectable with standard stopwatch-timed measures. Still, whether such markers are useful for evaluating the severity of the disease remains unknown. Therefore, the correlation between ILG and disease progression would be worth exploring.

METHODS

We will search MEDLINE via PubMed, Cochrane, and EMBASE electronic databases to identify articles published before May 2, 2018 that measure gait using IMUs in MS patients. In addition, grey literature will be searched. Inclusion criteria will be adults with a clinical diagnosis of MS and gait measured by using inertial sensors. We will exclude from the meta-analysis articles that do not provide sufficient data for evaluating the correlations between ILG parameters and disease severity as measured by at least one of the six following tests: the Expanded Disability Status Scale (EDSS), the Multiple Sclerosis Walking Scale-12 (MSWS), the Multiple Sclerosis Severity Score (MSSS), the Multiple Sclerosis Impact Scale (MSIS-29), the Multiple Sclerosis Functional Composite (MSFC), and the Timed 25-ft Walk Test (T25FW). Extracted data from included articles will be presented descriptively, and effect sizes will be computed based on the recommendations from the Cochrane Collaboration handbook and RevMan software.

DISCUSSION

Identifying changes in disease state throughout the course of MS is essential for optimal care. Current clinical and performance tests allow for identifying advanced gait alteration but lack sensitivity to detect subtle gait change. IMUs can be easily used in clinical practice to quantify gait in MS patients. Nevertheless, whether these outcomes are clinically relevant is uncertain because no study has evaluated their correlation with disease severity across different settings. This systematic review and meta-analysis would bring insight into the potential of this outcome as a marker of disease evolution.

SYSTEMATIC REVIEW REGISTRATION

This review was registered with the International Prospective Register of Systematic Reviews on May 2, 2018 (Registration: CRD42018092651). Both the search strategy and study protocol are available at https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=92651 .

Inertial Sensors to Assess Gait Quality in Patients with Neurological Disorders: A Systematic Review of Technical and Analytical Challenges

Gait disorders are major causes of falls in patients with neurological diseases. Understanding these disorders allows prevention and better insights into underlying diseases. InertiaLocoGraphy (ILG) -the quantification of gait by using inertial measurement units (IMUs) -shows great potential to address this public health challenge, but protocols vary widely and normative values of gait parameters are still unavailable. This systematic review critically compares ILG protocols, questions features extracted from inertial signals and proposes a semeiological analysis of clinimetric characteristics for use in neurological clinical routine. For this systematic review, PubMed, Cochrane and EMBASE were searched for articles assessing gait quality by using IMUs that were published from January 1, 2014 to August 31, 2016. ILG was used to assess gait in a wide range of neurological disorders - including Parkinson disease, mild cognitive impairment, Alzheimer disease, cerebral palsy, and cerebellar atrophy - as well as in the faller or frail older population and in people presenting rheumatological pathologies. However, results have not yet been driving changes in clinical practice. One reason could be that studies mainly aimed at comparing pathological gait to healthy gait, but there is stronger need for semiological descriptions of gait perturbation, severity or prognostic assessment. Furthermore, protocols used to assess gait using IMUs are too many. Likely, outcomes are highly heterogeneous and difficult to compare across large panels of studies. Therefore, homogenization is needed to foster the use of ILG to assess gait quality in neurological routine practice. The pros and cons of each protocol are emphasized so that a compromise can be reached. As well, analysis of seven complementary clinical criteria (springiness, sturdiness, smoothness, steadiness, stability, symmetry, synchronization) is advocated.