Search

Falls are a major concern for people with Parkinson's disease (PwPD), but accurately assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies could enable the capture of objective and high-resolution data to better inform fall risk through measurement of everyday factors (e.g., obstacles) that contribute to falls. Wearable inertial measurement units (IMUs) capture objective high-resolution walking/gait data in all environments but are limited by not providing absolute clarity on contextual information (i.e., obstacles) that could greatly influence how gait is interpreted. Video-based data could compliment IMU-based data for a comprehensive free-living fall risk assessment. The objective of this study was twofold. First, pilot work was conducted to propose a novel artificial intelligence (AI) algorithm for use with wearable video-based eye-tracking glasses to compliment IMU gait data in order to better inform free-living fall risk in PwPD. The suggested approach (based on a fine-tuned You Only Look Once version 8 (YOLOv8) object detection algorithm) can accurately detect and contextualize objects (mAP50 = 0.81) in the environment while also providing insights into where the PwPD is looking, which could better inform fall risk. Second, we investigated the perceptions of PwPD via a focus group discussion regarding the adoption of video technologies and AI during their everyday lives to better inform their own fall risk. This second aspect of the study is important as, traditionally, there may be clinical and patient apprehension due to ethical and privacy concerns on the use of wearable cameras to capture real-world video. Thematic content analysis was used to analyse transcripts and develop core themes and categories. Here, PwPD agreed on ergonomically designed wearable video-based glasses as an optimal mode of video data capture, ensuring discreteness and negating any public stigma on the use of research-style equipment. PwPD also emphasized the need for control in AI-assisted data processing to uphold privacy, which could overcome concerns with the adoption of video to better inform IMU-based gait and free-living fall risk. Contemporary technologies (wearable video glasses and AI) can provide a holistic approach to fall risk that PwPD recognise as helpful and safe to use.

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole-derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time-series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring., Competing Interests: MW, AL, KG, BL, SS, XW, JI, ML, BK, IS, MT, DD, AB, FW, WL, GH, JU, YP, GA, JH, SS, OL, AA, RA, SH, OH Employee and shareholder of Regeneron Pharmaceuticals, Inc, (© 2024, Wipperman, Lin, Gayvert et al.)

Background: Turning is a complex measure of gait that accounts for over 50% of daily steps. Traditionally, turning has been measured in a research grade laboratory setting, however, there is demand for a low-cost and portable solution to measure turning using wearable technology. This study aimed to determine the suitability of a low-cost inertial sensor-based device (AX6, Axivity) to assess turning, by simultaneously capturing and comparing to a turn algorithm output from a previously validated reference inertial sensor-based device (Opal), in healthy young adults. Methodology: Thirty participants (aged 23.9 ± 4.89 years) completed the following turning protocol wearing the AX6 and reference device: a turn course, a two-minute walk (including 180° turns) and turning in place, alternating 360° turn right and left. Both devices were attached at the lumbar spine, one Opal via a belt, and the AX6 via double sided tape attached directly to the skin. Turning measures included number of turns, average turn duration, angle, velocity, and jerk. Results: Agreement between the outcomes from the AX6 and reference device was good to excellent for all turn characteristics (all ICCs > 0.850) during the turning 360° task. There was good agreement for all turn characteristics (all ICCs > 0.800) during the two-minute walk task, except for moderate agreement for turn angle (ICC 0.683). Agreement for turn outcomes was moderate to good during the turns course (ICCs range; 0.580 to 0.870). Conclusions: A low-cost wearable sensor, AX6, can be a suitable and fit-for-purpose device when used with validated algorithms for assessment of turning outcomes, particularly during continuous turning tasks. Future work needs to determine the suitability and validity of turning in aging and clinical cohorts within low-resource settings.

Gait assessment is emerging as a prominent way to understand impaired mobility and underlying neurological deficits. Various technologies have been used to assess gait inside and outside of laboratory settings, but wearables are the preferred option due to their cost-effective and practical use in both. There are robust conceptual gait models developed to ease the interpretation of gait parameters during indoor and outdoor environments. However, these models examine uni-modal gait characteristics (e.g., spatio-temporal parameters) only. Previous studies reported that understanding the underlying reason for impaired gait requires multi-modal gait assessment. Therefore, this study aims to develop a multi-modal approach using a synchronized inertial and electromyography (EMG) signals. Firstly, initial contact (IC), final contact (FC) moments and corresponding time stamps were identified from inertial data, producing temporal outcomes e.g., step time. Secondly, IC/FC time stamps were used to segment EMG data and define onset and offset times of muscle activities within the gait cycle and its subphases. For investigation purposes, we observed notable differences in temporal characteristics as well as muscle onset/offset timings and amplitudes between indoor and outdoor walking of three stroke survivors. Our preliminary analysis suggests a multi-modal approach may be important to augment and improve current inertial conceptual gait models by providing additional quantitative EMG data.

There is a dearth of knowledge about how symptom severity affects gait in the chronic (>3 months) mild traumatic brain injury (mTBI) population despite up to 53% of people reporting persisting symptoms after mTBI. The aim of this investigation was to determine whether gait is affected in a symptomatic, chronic mTBI group and to assess the relationship between gait performance and symptom severity on the Neurobehavioral Symptom Inventory (NSI). Gait was assessed under single- and dual-task conditions using five inertial sensors in 57 control subjects and 65 persons with chronic mTBI (1.0 year from mTBI). The single- and dual-task gait domains of Pace, Rhythm, Variability, and Turning were calculated from individual gait characteristics. Dual-task cost (DTC) was calculated for each domain. The mTBI group walked (domain z-score mean difference, single-task = 0.70; dual-task = 0.71) and turned (z-score mean difference, single-task = 0.69; dual-task = 0.70) slower ( p  < 0.001) under both gait conditions, with less rhythm under dual-task gait (z-score difference = 0.21; p  = 0.001). DTC was not different between groups. Higher NSI somatic subscore was related to higher single- and dual-task gait variability as well as slower dual-task pace and turning ( p  < 0.01). Persons with chronic mTBI and persistent symptoms exhibited altered gait, particularly under dual-task, and worse gait performance related to greater symptom severity. Future gait research in chronic mTBI should assess the possible underlying physiological mechanisms for persistent symptoms and gait deficits.

Background: Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works., Research Question and Methods: Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders., Results: Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist., Significance: This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background and Purpose: Gait and turning impairments are common in people with Parkinson disease (PwPD). Tactile cues delivered in open- or closed-loop modalities may improve gait and turning in PwPD, but underlying mechanisms are unclear. Attention stemming from the prefrontal cortex (PFC) may play a role in cue response, but PFC contributions to specific cue modalities are unclear. Examining how open- and closed-loop cueing influences PFC activity during walking and turning in PwPD may elucidate mechanisms involved in cue response, which could advance development of effective therapeutics. We examined PFC activity during walking and turning in response to open- and closed-loop cueing in PwPD, and explored relationships between PFC activity and behavioral measures., Methods: A mobile functional near-infrared spectroscopy device measured PFC activity during walking and turning in 25 PwPD (n = 13 freezers, n = 12 nonfreezers). Participants performed 180° and 360° turns while walking, and a 2-minute walk under single- and dual-task (AX-CPT) conditions with and without an open- (metronome-like vibration) or closed-loop (biofeedback vibration) tactile cue., Results: PFC activity did not change when walking or turning in PwPD; freezing status or task demands did not influence PFC activity. With both open- and closed-loop cueing dual-task cost of gait significantly improved, whereas turning slowed., Discussion and Conclusions: Our preliminary results indicate that both open- and closed-loop cueing can improve gait without additional burden to the PFC beyond usual walking. However, turning while walking slowed with cueing with no PFC activity change. Further investigations are necessary to establish these findings in a larger cohort.Video Abstract available for more insights from the authors (see Supplemental Digital Content 1, the Video, available at: http://links.lww.com/JNPT/A280).

Introduction: Mild traumatic brain injury (mTBI) can impact gait, with deficits linked to underlying neural disturbances in cognitive, motor and sensory systems. Gait is complex as it is comprised of multiple characteristics that are sensitive to underlying neural deficits. However, there is currently no clear framework to guide selection of gait characteristics in mTBI. This study developed a model of gait in chronic mTBI and replicated this in a separate group of controls, to provide a comprehensive and structured methodology on which to base gait assessment and analysis., Methods: Fifty-two people with chronic mTBI and 59 controls completed a controlled laboratory gait assessment; walking for two minutes back and forth over a 13 m distance while wearing five wirelessly synchronized inertial sensors. Thirteen gait characteristics derived from the inertial sensors were selected for entry into the principle component analysis based on previous literature, robustness and novelty. Principle component analysis was then used to derive domains (components) of gait., Results: Four gait domains were derived for our chronic mTBI group (variability, rhythm, pace and turning) and this was replicated in a separate control cohort. Domains totaled 80.8% and 77.4% of variance in gait for chronic mTBI and controls, respectively. Gait characteristic loading was unambiguous for all features, with the exception of gait speed in controls that loaded on pace and rhythm domains., Conclusion: This study contributes a four component model of gait in chronic mTBI and controls that can be used to comprehensively assess and analyze gait and underlying mechanisms involved in impairment, or examine the influence of interventions., Competing Interests: Declaration of Competing Interest None to declare., (Copyright © 2019. Published by Elsevier B.V.)

Turning elicits Freezing of Gait (FoG) episodes in people with Parkinson's disease (PD) and is thought to require higher cortical control compared to straight ahead gait. Functional near infrared spectroscopy (fNIRS) has been used to examine prefrontal cortex (PFC) activity while walking, but the relationship between PFC activity and turn performance remains unclear. The aim of this pilot study was to examine PFC activity during turning in PD and healthy controls, and to investigate the association between PFC activity and turning. Thirty-two subjects, 15 freezers (PD + FoG) and 17 non-freezers (PD - FoG), and 8 controls were asked to perform a 2-min turning-in-place test under single-task (ST) and dual-task (DT) conditions. Each participant wore an fNIRS system to measure changes in oxyhemoglobin, as measure of PFC activity, and inertial sensors to quantify turning. Our results show a significant group (p = .050), task (p = .039), and interaction (p = .047) for the PFC activity during turning. Specifically, PD + FoG show higher PFC during turning compared to the other groups; PFC activity during DT is overall different compared to ST with an opposite trend in PD + FoG compared to controls and PD - FoG. In addition, higher PFC is associated with worse FoG in PD + FoG (r = 0.57, p = .048) and with lower number of turns in PD - FoG (r = -0.70, p = .002). The increased PFC activity in PD and the association between higher PFC activity and poorer turning performance may be a sign of poor movement automaticity in PD. Although further investigations are required, these pilot findings may guide development of personalized treatments to improve motor automaticity in PD., (Copyright © 2019. Published by Elsevier Ltd.)

Background: Aging is associated with declining mobility, which negatively affects quality of life and incurs substantial economic costs. Techniques to maintain safe mobility in older adults are therefore essential. Rhythmic auditory cueing (RAC) can improve walking patterns in older adults. However, the neural correlates associated with RAC, how they are influenced by repeated exposure and their relationships with gait response, cognitive function, and depressive symptoms are unclear., Objectives: This study aimed to investigate the effects of RAC during walking on cortical activation and the relationship between RAC-related cortical changes and cognitive function, depressive symptoms, and gait response., Methods: Seventeen young adults and eighteen older adults walked on a motorized treadmill for 5 minutes (5 trials with alternating 30-second blocks of usual walking and RAC walking). Changes in oxygenated hemoglobin (HbO 2 ) in the frontal cortex were recorded using functional near-infrared spectroscopy. Cognitive domains were assessed through validated tests. A triaxial accelerometer measured gait parameters., Results: Gait variability decreased and prefrontal HbO 2 levels increased during cued walking relative to usual walking. Older adults showed greater HbO 2 levels in multiple motor regions during cued walking although the response reduced with repeated exposure. In older adults, lower depression scores, higher cognitive functioning, and reduced gait variability were linked with increased HbO 2 levels during RAC walking., Conclusion: These findings suggest that walking improves with RAC in older adults and is achieved through increased activity in multiple cortical areas. The cortical response decline with repeated exposure indicates older adults' ability to adapt to a new task.

Turning impairments are common in Parkinson's disease (PD) and can elicit freezing of gait (FoG). Extensive examination of open-loop cueing interventions has demonstrated that they can ameliorate gait deficits in PD; less is known about efficacy to improve turning. Here, we investigate the immediate effectiveness of open- and closed-loop cueing in improving turning characteristics in people with PD. Twenty-five subjects with and 18 subjects without FoG participated in the study. Subjects turned in place for one minute under single- and dual-task for 3 randomized conditions: (i) Baseline; (ii) Turning to the beat of a metronome (open-loop); and (iii) Turning with phase-dependent tactile biofeedback (closed-loop). Objective measures of freezing, such as % time spent freezing and FoG-ratio, significantly improved when turning with both open-loop and closed-loop cueing compared to baseline. Dual-tasking did not worsen FoG in freezers, but significantly slowed down turns in both groups. Both cueing modalities significantly improved turning smoothness in both groups, but reduced turning velocity and number of turns compared to baseline. Both open and closed-loop cueing markedly improved turning in people with PD. These preliminary observations warrant further exploration of vibrotactile closed-loop cueing to improve mobility in everyday life.

Gait impairment is a core feature of Parkinson's disease (PD) with implications for falls risk. Visual cues improve gait in PD, but the underlying mechanisms are unclear. Evidence suggests that attention and vision play an important role; however, the relative contribution from each is unclear. Measurement of visual exploration (specifically saccade frequency) during gait allows for real-time measurement of attention and vision. Understanding how visual cues influence visual exploration may allow inferences of the underlying mechanisms to response which could help to develop effective therapeutics. This study aimed to examine saccade frequency during gait in response to a visual cue in PD and older adults and investigate the roles of attention and vision in visual cue response in PD. A mobile eye-tracker measured saccade frequency during gait in 55 people with PD and 32 age-matched controls. Participants walked in a straight line with and without a visual cue (50 cm transverse lines) presented under single task and dual-task (concurrent digit span recall). Saccade frequency was reduced when walking in PD compared to controls; however, visual cues ameliorated saccadic deficit. Visual cues significantly increased saccade frequency in both PD and controls under both single task and dual-task. Attention rather than visual function was central to saccade frequency and gait response to visual cues in PD. In conclusion, this study highlights the impact of visual cues on visual exploration when walking and the important role of attention in PD. Understanding these complex features will help inform intervention development., (© 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Gait impairment is a core feature of Parkinson's disease (PD) which has been linked to cognitive and visual deficits, but interactions between these features are poorly understood. Monitoring saccades allows investigation of real-time cognitive and visual processes and their impact on gait when walking. This study explored: (i) saccade frequency when walking under different attentional manipulations of turning and dual-task; and (ii) direct and indirect relationships between saccades, gait impairment, vision and attention. Saccade frequency (number of fast eye movements per-second) was measured during gait in 60 PD and 40 age-matched control participants using a mobile eye-tracker. Saccade frequency was significantly reduced in PD compared to controls during all conditions. However, saccade frequency increased with a turn and decreased under dual-task for both groups. Poorer attention directly related to saccade frequency, visual function and gait impairment in PD, but not controls. Saccade frequency did not directly relate to gait in PD, but did in controls. Instead, saccade frequency and visual function deficit indirectly impacted gait impairment in PD, which was underpinned by their relationship with attention. In conclusion, our results suggest a vital role for attention with direct and indirect influences on gait impairment in PD. Attention directly impacted saccade frequency, visual function and gait impairment in PD, with connotations for falls. It also underpinned indirect impact of visual and saccadic impairment on gait. Attention therefore represents a key therapeutic target that should be considered in future research., (© 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Vision and cognition have both been related to gait impairment in Parkinson's disease (PD) through separate strands of research. The cumulative and interactive effect of both (which we term visuo-cognition) has not been previously investigated and little is known about the influence of cognition on vision with respect to gait. Understanding the role of vision, cognition and visuo-cognition in gait in PD is critical for data interpretation and to infer and test underlying mechanisms. The purpose of this comprehensive narrative review was to examine the interdependent and interactive role of cognition and vision in gait in PD and older adults. Evidence from a broad range of research disciplines was reviewed and summarised. A key finding was that attention appears to play a pivotal role in mediating gait, cognition and vision, and should be considered emphatically in future research in this field., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

This document is a compilation of research articles on gait analysis and running biomechanics. It covers topics such as the use of wearables for gait analysis, the effects of various factors on running patterns, and the reliability and validity of different measurement methods. The articles include studies on different populations, including neurological patients, elderly individuals, and runners. This comprehensive resource can be valuable for library patrons conducting research on gait analysis and running biomechanics. [Extracted from the article]

Although the multifactorial nature of falls in Parkinson's disease (PD) is well described, optimal assessment for the identification of fallers remains unclear. Thus, we aimed to identify clinical and objective gait measures that best discriminate fallers from non-fallers in PD, with suggestions of optimal cutoff scores. METHODS: Individuals with mild-to-moderate PD were classified as fallers (n = 31) or non-fallers (n = 96) based on the previous 12 months' falls. Clinical measures (demographic, motor, cognitive and patient-reported outcomes) were assessed with standard scales/tests, and gait parameters were derived from wearable inertial sensors (Mobility Lab v2); participants walked overground, at a self-selected speed, for 2 min under single and dual-task walking conditions (maximum forward digit span). Receiver operating characteristic curve analysis identified measures (separately and in combination) that best discriminate fallers from non-fallers; we calculated the area under the curve (AUC) and identified optimal cutoff scores (i.e., point closest-to-(0,1) corner). RESULTS: Single gait and clinical measures that best classified fallers were foot strike angle (AUC = 0.728; cutoff = 14.07°) and the Falls Efficacy Scale International (FES-I; AUC = 0.716, cutoff = 25.5), respectively. Combinations of clinical + gait measures had higher AUCs than combinations of clinical-only or gait-only measures. The best performing combination included the FES-I score, New Freezing of Gait Questionnaire score, foot strike angle and trunk transverse range of motion (AUC = 0.85). CONCLUSION: Multiple clinical and gait aspects must be considered for the classification of fallers and non-fallers in PD. [ABSTRACT FROM AUTHOR]

Walking/gait quality is a useful clinical tool to assess general health and is now broadly described as the sixth vital sign. This has been mediated by advances in sensing technology, including instrumented walkways and three-dimensional motion capture. However, it is wearable technology innovation that has spawned the highest growth in instrumented gait assessment due to the capabilities for monitoring within and beyond the laboratory. Specifically, instrumented gait assessment with wearable inertial measurement units (IMUs) has provided more readily deployable devices for use in any environment. Contemporary IMU-based gait assessment research has shown evidence of the robust quantifying of important clinical gait outcomes in, e.g., neurological disorders to gather more insightful habitual data in the home and community, given the relatively low cost and portability of IMUs. The aim of this narrative review is to describe the ongoing research regarding the need to move gait assessment out of bespoke settings into habitual environments and to consider the shortcomings and inefficiencies that are common within the field. Accordingly, we broadly explore how the Internet of Things (IoT) could better enable routine gait assessment beyond bespoke settings. As IMU-based wearables and algorithms mature in their corroboration with alternate technologies, such as computer vision, edge computing, and pose estimation, the role of IoT communication will enable new opportunities for remote gait assessment. [ABSTRACT FROM AUTHOR]

Fall risk assessment needs contemporary approaches based on habitual data. Currently, inertial measurement unit (IMU)-based wearables are used to inform free-living spatio-temporal gait characteristics to inform mobility assessment. Typically, a fluctuation of those characteristics will infer an increased fall risk. However, current approaches with IMUs alone remain limited, as there are no contextual data to comprehensively determine if underlying mechanistic (intrinsic) or environmental (extrinsic) factors impact mobility and, therefore, fall risk. Here, a case study is used to explore and discuss how contemporary video-based wearables could be used to supplement arising mobility-based IMU gait data to better inform habitual fall risk assessment. A single stroke survivor was recruited, and he conducted a series of mobility tasks in a lab and beyond while wearing video-based glasses and a single IMU. The latter generated topical gait characteristics that were discussed according to current research practices. Although current IMU-based approaches are beginning to provide habitual data, they remain limited. Given the plethora of extrinsic factors that may influence mobility-based gait, there is a need to corroborate IMUs with video data to comprehensively inform fall risk assessment. Use of artificial intelligence (AI)-based computer vision approaches could drastically aid the processing of video data in a timely and ethical manner. Many off-the-shelf AI tools exist to aid this current need and provide a means to automate contextual analysis to better inform mobility from IMU gait data for an individualized and contemporary approach to habitual fall risk assessment. [ABSTRACT FROM AUTHOR]

Degradation of striatal dopamine in Parkinson's disease (PD) may initially be supplemented by increased cognitive control mediated by cholinergic mechanisms. Shift to cognitive control of walking can be quantified by prefrontal cortex activation. Levodopa improves certain aspects of gait and worsens others, and cholinergic augmentation influence on gait and prefrontal cortex activity remains unclear. This study examined dopaminergic and cholinergic influence on gait and prefrontal cortex activity while walking in PD. A single‐site, randomized, double‐blind crossover trial examined effects of levodopa and donepezil in PD. Twenty PD participants were randomized, and 19 completed the trial. Participants were randomized to either levodopa + donepezil (5 mg) or levodopa + placebo treatments, with 2 weeks with treatment and a 2‐week washout. The primary outcome was change in prefrontal cortex activity while walking, and secondary outcomes were change in gait and dual‐task performance and attention. Levodopa decreased prefrontal cortex activity compared with off medication (effect size, −0.51), whereas the addition of donepezil reversed this decrease. Gait speed and stride length under single‐ and dual‐task conditions improved with combined donepezil and levodopa compared with off medication (effect size, 1 for gait speed and 0.75 for stride length). Dual‐task reaction time was quicker with levodopa compared with off medication (effect size, −0.87), and accuracy improved with combined donepezil and levodopa (effect size, 0.47). Cholinergic therapy, specifically donepezil 5 mg/day for 2 weeks, can alter prefrontal cortex activity when walking and improve secondary cognitive task accuracy and gait in PD. Further studies will investigate whether higher prefrontal cortex activity while walking is associated with gait changes. © 2020 International Parkinson and Movement Disorder Society [ABSTRACT FROM AUTHOR]

Eye movements are impaired by Parkinson’s disease (PD) although limited research has explored if PD affects the relevance of visual fixations when walking. Visual fixations may provide crucial contextual information for safe navigation and important insights into fall risk. This study aimed to: investigate visual fixations made while walking under a range of conditions in PD; identify their task relevance; and explore their relationship with clinical features. Thirty-eight people with mild-moderate PD and forty age-matched control participants completed a straight walk with (i) no additional stimuli and (ii) with additional stimuli (visual cues or a high contrast obstacle), whilst wearing a mobile eye-tracker. Fixations were extracted and classified by location and relevance. PD participants made proportionally fewer task-relevant fixations (floor, walls and additional stimuli ahead), caused by significantly more task-irrelevant fixations (floor, walls and ceiling away from waking path) during normal walking ( p  = 0.014). These group differences were not apparent with visual cues ( p  = 0.359). During obstacle crossing trials, PD made significantly more task-relevant fixations than controls ( p  = 0.007). Reduced bilateral visual acuity was associated with fewer fixations in PD. Our findings suggest that people with PD visually explore complex environments less efficiently likely owing to underlying PD pathology. Visual exploration improved with the addition of salient stimuli (for example visual cues or an obstacle) and thus developing and optimising visual interventions could prove critical to improving locomotor safety and reducing falls risk in home environments. [ABSTRACT FROM AUTHOR]

Introduction: Gait impairment occurs across the spectrum of traumatic brain injury (TBI); from mild (mTBI) to moderate (modTBI), to severe (sevTBI). Recent evidence suggests that objective gait assessment may be a surrogate marker for neurological impairment such as TBI. However, the most optimal method of objective gait assessment is still not well understood due to previous reliance on subjective assessment approaches. The purpose of this review was to examine objective assessment of gait impairments across the spectrum of TBI. Methods: PubMed, AMED, OVID and CINAHL databases were searched with a search strategy containing key search terms for TBI and gait. Original research articles reporting gait outcomes in adults with TBI (mTBI, modTBI, sevTBI) were included. Results: 156 citations were identified from the search, of these, 13 studies met the initial criteria and were included into the review. The findings from the reviewed studies suggest that gait is impaired in mTBI, modTBI and sevTBI (in acute and chronic stages), but methodological limitations were evident within all studies. Inertial measurement units were most used to assess gait, with single-task, dual-task and obstacle crossing conditions used. No studies examined gait across the full spectrum of TBI and all studies differed in their gait assessment protocols. Recommendations for future studies are provided. Conclusion: Gait was found to be impaired in TBI within the reviewed studies regardless of severity level (mTBI, modTBI, sevTBI), but methodological limitations of studies (transparency and reproducibility) limit clinical application. Further research is required to establish a standardised gait assessment procedure to fully determine gait impairment across the spectrum of TBI with comprehensive outcomes and consistent protocols. [ABSTRACT FROM AUTHOR]

Background: People with PD who exhibit freezing of gait (FOG) also exhibit poor balance compared to those who do not freeze. However, balance is a broad construct that can be subdivided into subdomains that include dynamic balance (gait), anticipatory postural adjustments (APAs) & gait initiation, postural sway in stance, and automatic postural responses (e.g., reactive stepping). Few studies have provided a robust investigation on how each of these domains is impacted by FOG, and no studies have compared balance across groups while rigorously controlling for disease severity.Methods: Structural equation modeling was used to evaluate the relationships between FOG and balance domains constructed as latent variables and controlling for disease severity. Domains included: dynamic balance (gait), APAs, postural sway, and reactive stepping. Models were run relating domains to both the presence and severity of FOG.Results: Latent variables reflecting domains of Gait and APAs, but not postural sway or reactive stepping, were significantly related to the severity of FOG. Models for presence of FOG showed the same results, as Gait and APAs, but not postural sway or reactive stepping, were related to presence of FOG.Conclusion: These results are consistent with hypotheses that balance deficits in people with PD who freeze are most pronounced in gait and anticipatory postural adjustments. Reactive stepping and postural sway domains are less effected in PD patients who freeze compared to those who do not. These findings suggest that rehabilitative strategies focused on gait and APAs may be most effective for people with PD who freeze. [ABSTRACT FROM AUTHOR]