Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. METHOD: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. RESULTS: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. CONCLUSION: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Using Video Technology and AI within Parkinson's Disease Free-Living Fall Risk Assessment.

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.

Elevated Gaussian-modeled beta power in the cortex characterizes aging, but not Parkinson's disease.

Aging is a key risk factor for the development of Parkinson's disease (PD). PD is characterized by excessive synchrony of beta oscillations (13-30 Hz) in the basal ganglia thalamo-cortical network. However, cortical beta power is not reliably elevated in individuals with PD. Here, we sought to disentangle how resting cortical beta power compares in younger controls, older controls, and individuals with PD using scalp electroencephalogram (EEG) and a novel approach for quantifying beta power. Specifically, we used a Gaussian model to determine if sensorimotor beta power distinguishes these groups. In addition, we looked at the distribution of beta power across the entire cortex. Our findings showed that Gaussian-modeled beta power does not differentiate individuals with PD (on medication) from healthy younger or older controls in sensorimotor cortex. However, beta power (and not theta or alpha) was higher in healthy older versus younger controls. This effect was most pronounced in regions near sensorimotor cortex including the frontal and parietal areas [P < 0.05, false discovery rate (FDR) corrected]. In addition, the bandwidth of the periodic beta was also higher in healthy older than young individuals in parietal regions. Finally, the aperiodic component, specifically the exponent of the signal, was higher (steeper) in younger controls than in individuals with PD in the right parietal-occipital region (P < 0.05, FDR corrected), possibly reflecting differences in neuronal spiking. Our findings suggest that cortical Gaussian beta power is possibly modulated by age and could be further explored in longitudinal studies to determine whether sensorimotor beta increases with increasing age.NEW & NOTEWORTHY Altered sensorimotor beta activity has been shown to be a feature in aging and PD. Using a novel approach, we clarify that resting sensorimotor beta power does not distinguish subjects with PD from healthy younger and older controls. However, beta power was higher in older compared with younger controls in central sensorimotor, frontal, and parietal regions. These results provide a clearer picture of sensorimotor beta power, demonstrating that it is elevated in aging but not PD.

CSF-1R inhibitor PLX3397 attenuates peripheral and brain chronic GVHD and improves functional outcomes in mice.

Graft-versus-host disease (GVHD) is a serious complication of otherwise curative allogeneic haematopoietic stem cell transplants. Chronic GVHD induces pathological changes in peripheral organs as well as the brain and is a frequent cause of late morbidity and death after bone-marrow transplantation. In the periphery, bone-marrow-derived macrophages are key drivers of pathology, but recent evidence suggests that these cells also infiltrate into cGVHD-affected brains. Microglia are also persistently activated in the cGVHD-affected brain. To understand the involvement of these myeloid cell populations in the development and/or progression of cGVHD pathology, we here utilized the blood-brain-barrier permeable colony stimulating factor-1 receptor (CSF-1R) inhibitor PLX3397 (pexidartinib) at varying doses to pharmacologically deplete both cell types. We demonstrate that PLX3397 treatment during the development of cGVHD (i.e., 30 days post-transplant) improves disease symptoms, reducing both the clinical scores and histopathology of multiple cGVHD target organs, including the sequestration of T cells in cGVHD-affected skin tissue. Cognitive impairments associated with cGVHD and neuroinflammation were also attenuated by PLX3397 treatment. PLX3397 treatment prior to the onset of cGVHD (i.e., immediately post-transplant) did not change in clinical scores or histopathology. Overall, our data demonstrate significant benefits of using PLX3397 for the treatment of cGVHD and associated organ pathologies in both the periphery and brain, highlighting the therapeutic potential of pexidartinib for this condition.

Ocular microtremor: a structured review.

Ocular microtremor (OMT) is the smallest of three involuntary fixational micro eye movements, which has led to it being under researched in comparison. The link between OMT and brain function generates a strong rationale for further study as there is potential for its use as a biomarker in populations with neurological injury and disease. This structured review focused on populations previously studied, instrumentation used for measurement, commonly reported OMT outcomes, and recommendations concerning protocol design and future studies. Current methods of quantifying OMT will be reviewed to analyze their efficacy and efficiency and guide potential development and understanding of novel techniques. Electronic databases were systematically searched and compared with predetermined inclusion criteria. 216 articles were identified in the search and screened by two reviewers. 16 articles were included for review. Findings showed that piezoelectric probe is the most common method of measuring OMT, with fewer studies involving non-invasive approaches, such as contact lenses and laser imaging. OMT frequency was seen to be reduced during general anesthesia at loss of consciousness and in neurologically impaired participants when compared to healthy adults. We identified the need for a non-invasive technique for measuring OMT and highlight its potential in clinical applications as an objective biomarker for neurological assessments. We highlight the need for further research on the clinical validation of OMT to establish its potential to identify or predict a meaningful clinical or functional state, specifically, regarding accuracy, precision, and reliability of OMT.

Faster Walking Speeds Require Greater Activity from the Primary Motor Cortex in Older Adults Compared to Younger Adults.

Gait speed declines with age and slower walking speeds are associated with poor health outcomes. Understanding why we do not walk faster as we age, despite being able to, has implications for rehabilitation. Changes in regional oxygenated haemoglobin (HbO2) across the frontal lobe were monitored using functional near infrared spectroscopy in 17 young and 18 older adults while they walked on a treadmill for 5 min, alternating between 30 s of walking at a preferred and fast (120% preferred) speed. Gait was quantified using a triaxial accelerometer (lower back). Differences between task (preferred/fast) and group (young/old) and associations between regional HbO2 and gait were evaluated. Paired tests indicated increased HbO2 in the supplementary motor area (right) and primary motor cortex (left and right) in older adults when walking fast (p < 0.006). HbO2 did not significantly change in the young when walking fast, despite both groups modulating gait. When evaluating the effect of age (linear mixed effects model), greater increases in HbO2 were observed for older adults when walking fast (prefrontal cortex, premotor cortex, supplementary motor area and primary motor cortex) compared to young adults. In older adults, increased step length and reduced step length variability were associated with larger increases in HbO2 across multiple regions when walking fast. Walking fast required increased activation of motor regions in older adults, which may serve as a therapeutic target for rehabilitation. Widespread increases in HbO2 across the frontal cortex highlight that walking fast represents a resource-intensive task as we age.

Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera.

Running gait assessment is essential for the development of technical optimization strategies as well as to inform injury prevention and rehabilitation. Currently, running gait assessment relies on (i) visual assessment, exhibiting subjectivity and limited reliability, or (ii) use of instrumented approaches, which often carry high costs and can be intrusive due to the attachment of equipment to the body. Here, the use of an IoT-enabled markerless computer vision smartphone application based upon Google's pose estimation model BlazePose was evaluated for running gait assessment for use in low-resource settings. That human pose estimation architecture was used to extract contact time, swing time, step time, knee flexion angle, and foot strike location from a large cohort of runners. The gold-standard Vicon 3D motion capture system was used as a reference. The proposed approach performs robustly, demonstrating good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all running gait outcomes. Additionally, temporal outcomes exhibit low mean error (0.01−0.014 s) in left foot outcomes. However, there are some discrepancies in right foot outcomes, due to occlusion. This study demonstrates that the proposed low-cost and markerless system provides accurate running gait assessment outcomes. The approach may help routine running gait assessment in low-resource environments.

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring.

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.

Enhancing Free-Living Fall Risk Assessment: Contextualizing Mobility Based IMU Data.

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.

Combination of Clinical and Gait Measures to Classify Fallers and Non-Fallers in Parkinson's Disease.

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.

Visual Cues for Turning in Parkinson's Disease.

Turning is a common impairment of mobility in people with Parkinson's disease (PD), which increases freezing of gait (FoG) episodes and has implications for falls risk. Visual cues have been shown to improve general gait characteristics in PD. However, the effects of visual cues on turning deficits in PD remains unclear. We aimed to (i) compare the response of turning performance while walking (180° and 360° turns) to visual cues in people with PD with and without FoG; and (ii) examine the relationship between FoG severity and response to visual cues during turning. This exploratory interventional study measured turning while walking in 43 participants with PD (22 with self-reported FoG) and 20 controls using an inertial sensor placed at the fifth lumbar vertebrae region. Participants walked straight and performed 180° and 360° turns midway through a 10 m walk, which was done with and without visual cues (starred pattern). The turn duration and velocity response to visual cues were assessed using linear mixed effects models. People with FoG turned slower and longer than people with PD without FoG and controls (group effect: p < 0.001). Visual cues reduced the velocity of turning 180° across all groups and reduced the velocity of turning 360° in people with PD without FoG and controls. FoG severity was not significantly associated with response to visual cues during turning. Findings suggest that visual cueing can modify turning during walking in PD, with response influenced by FoG status and turn amplitude. Slower turning in response to visual cueing may indicate a more cautious and/or attention-driven turning pattern. This study contributes to our understanding of the influence that cues can have on turning performance in PD, particularly in freezers, and will aid in their therapeutic application.

Suitability of a Low-Cost Wearable Sensor to Assess Turning in Healthy Adults.

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 Impairment in Traumatic Brain Injury: A Systematic Review.

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.

Measuring freezing of gait during daily-life: an open-source, wearable sensors approach.

BACKGROUND: Although a growing number of studies focus on the measurement and detection of freezing of gait (FoG) in laboratory settings, only a few studies have attempted to measure FoG during daily life with body-worn sensors. Here, we presented a novel algorithm to detect FoG in a group of people with Parkinson's disease (PD) in the laboratory (Study I) and extended the algorithm in a second cohort of people with PD at home during daily life (Study II). METHODS: In Study I, we described of our novel FoG detection algorithm based on five inertial sensors attached to the feet, shins and lumbar region while walking in 40 participants with PD. We compared the performance of the algorithm with two expert clinical raters who scored the number of FoG episodes from video recordings of walking and turning based on duration of the episodes: very short (< 1 s), short (2-5 s), and long (> 5 s). In Study II, a different cohort of 48 people with PD (with and without FoG) wore 3 wearable sensors on their feet and lumbar region for 7 days. Our primary outcome measures for freezing were the % time spent freezing and its variability. RESULTS: We showed moderate to good agreement in the number of FoG episodes detected in the laboratory (Study I) between clinical raters and the algorithm (if wearable sensors were placed on the feet) for short and long FoG episodes, but not for very short FoG episodes. When extending this methodology to unsupervised home monitoring (Study II), we found that percent time spent freezing and the variability of time spent freezing differentiated between people with and without FoG (p < 0.05), and that short FoG episodes account for 69% of the total FoG episodes. CONCLUSION: Our findings showed that objective measures of freezing in PD using inertial sensors on the feet in the laboratory are matching well with clinical scores. Although results found during daily life are promising, they need to be validated. Objective measures of FoG with wearable technology during community-living would be useful for managing this distressing feature of mobility disability in PD.

Prefrontal Cortex Activity and Gait in Parkinson's Disease With Cholinergic and Dopaminergic Therapy.

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.

Prefrontal Cortical Activation With Open and Closed-Loop Tactile Cueing When Walking and Turning in Parkinson Disease: A Pilot Study.

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).

Pro-Saccades Predict Cognitive Decline in Parkinson's Disease: ICICLE-PD.

BACKGROUND: Cumulative dementia incidence in Parkinson's disease (PD) is significant, with major personal and socioeconomic impacts on individuals with PD and their carers. Early identification of dementia risk is vital to ensuring optimal intervention. Saccadic deficits often distinguish neurodegenerative disorders and cognitive impairment, but their ability to predict cognitive decline in PD has yet to be determined. The aims of this study were to (1) evaluate baseline (6.4 ± 6.1 months since PD diagnosis) differences in pro-saccadic metrics between those with early PD and healthy age-matched adults; and (2) assess the ability of baseline pro-saccades to predict subsequent cognitive decline over 4.5 years. METHODS: One hundred and forty-one PD and 90 age-matched participants recruited at diagnosis underwent saccadometric assessment of pro-saccades at baseline and had cognition assessed at baseline, 18, 36, and 54 months. Pro-saccadic characteristics included latency, duration, amplitude, peak, and average velocity. Cognitive assessment included executive function, attention, fluctuating attention, and memory. Linear mixed-effects models examined pro-saccadic metrics as predictors of cognitive decline over 54 months. RESULTS: Pro-saccades were significantly impaired at baseline in PD compared with controls. Pro-saccadic characteristics of latency, duration, peak, and average velocity predicted decline in global cognition, executive function, attention, and memory over 54 months in PD. In addition, only reduction in global cognition and attention were predicted by pro-saccadic metrics in age-matched adults, indicating that PD findings were not purely age related. CONCLUSIONS: Saccadic characteristics are impaired in early PD and are predictive of cognitive decline in several domains. Assessment of saccades may provide a useful non-invasive biomarker for long-term PD cognitive decline in early disease. © 2019 International Parkinson and Movement Disorder Society.

Inertial Sensors Reveal Subtle Motor Deficits When Walking With Horizontal Head Turns After Concussion.

OBJECTIVE: To examine whether horizontal head turns while seated or while walking, when instrumented with inertial sensors, were sensitive to the acute effects of concussion and whether horizontal head turns had utility for concussion management. SETTING: Applied field setting, athletic training room. PARTICIPANTS: Twenty-four collegiate athletes with sports-related concussion and 25 healthy control athletes. DESIGN: Case-control; longitudinal. MAIN MEASURES: Peak head angular velocity and peak head angle (range of motion) when performing head turns toward an auditory cue while seated or walking. Gait speed when walking with and without head turns. RESULTS: Athletes with acute sports-related concussion turned their head slower than healthy control subjects initially (group ß = -49.47; SE = 16.33; P = .003) and gradually recovered to healthy control levels within 10 days postconcussion (group × time ß = 4.80; SE = 1.41; P < .001). Peak head velocity had fair diagnostic accuracy in differentiating subjects with acute concussion compared with controls (areas under the receiver operating characteristic curve [AUC] = 0.71-0.73). Peak head angle (P = .17) and gait speed (P = .64) were not different between groups and showed poor diagnostic utility (AUC = 0.57-0.62). CONCLUSION: Inertial sensors can improve traditional clinical assessments by quantifying subtle, nonobservable deficits in people following sports-related concussion.

Saccade frequency response to visual cues during gait in Parkinson's disease: the selective role of attention.

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.

Direct and indirect effects of attention and visual function on gait impairment in Parkinson's disease: influence of task and turning.

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.