Walking Task Research Articles

Immersive virtual reality for learning exoskeleton-like virtual walking: a feasibility study

PurposeVirtual Reality (VR) has proven to be an effective tool for motor (re)learning. Furthermore, with the current commercialization of low-cost head-mounted displays (HMDs), immersive virtual reality (IVR) has become a viable rehabilitation tool. Nonetheless, it is still an open question how immersive virtual environments should be designed to enhance motor learning, especially to support the learning of complex motor tasks. An example of such a complex task is triggering steps while wearing lower-limb exoskeletons as it requires the learning of several sub-tasks, e.g., shifting the weight from one leg to the other, keeping the trunk upright, and initiating steps. This study aims to find the necessary elements in VR to promote motor learning of complex virtual gait tasks.MethodsIn this study, we developed an HMD-IVR-based system for training to control wearable lower-limb exoskeletons for people with sensorimotor disorders. The system simulates a virtual walking task of an avatar resembling the sub-tasks needed to trigger steps with an exoskeleton. We ran an experiment with forty healthy participants to investigate the effects of first- (1PP) vs. third-person perspective (3PP) and the provision (or not) of concurrent visual feedback of participants’ movements on the walking performance – namely number of steps, trunk inclination, and stride length –, as well as the effects on embodiment, usability, cybersickness, and perceived workload.ResultsWe found that all participants learned to execute the virtual walking task. However, no clear interaction of perspective and visual feedback improved the learning of all sub-tasks concurrently. Instead, the key seems to lie in selecting the appropriate perspective and visual feedback for each sub-task. Notably, participants embodied the avatar across all training modalities with low cybersickness levels. Still, participants’ cognitive load remained high, leading to marginally acceptable usability scores.ConclusionsOur findings suggest that to maximize learning, users should train sub-tasks sequentially using the most suitable combination of person’s perspective and visual feedback for each sub-task. This research offers valuable insights for future developments in IVR to support individuals with sensorimotor disorders in improving the learning of walking with wearable exoskeletons

Examination of Proprioceptive Reliance During Backward Walking in Individuals With Multiple Sclerosis

Background: Slowed somatosensory conduction in multiple sclerosis (MS) increases postural instability and decreases proprioception. Despite these delays, individuals with MS rely more on proprioception for balance compared to controls. This heightened reliance, combined with slowed signal transduction, increases fall risk. Backward walking (BW) increases proprioceptive reliance by reducing visual cues. However, no study has conclusively linked proprioception to BW. This study aims to assess proprioception’s role in BW compared to forward walking (FW) in MS and to compare differences in proprioception between MS fallers and non-fallers. Methods: Fifty participants (average age: 50.34 ± 11.84, median Patient Determined Disease Steps [PDDS]: 2) completed the study. Participants completed BW and FW at comfortable and fast speeds. We have previously established vibration sensation as a proxy measure for proprioception. Vibration thresholds were quantified at the great toe bilaterally using a 2-alternative forced-choice procedure. Results: Significant correlations were seen for vibration sensation and FW comfortable (ρ = 0.35), FW fast (ρ = 0.34), BW comfortable (ρ = 0.46), and BW fast (ρ = 0.46). After controlling for age, sex, and PDDS, vibration sensation significantly predicted performance during all walking tasks, with larger beta coefficients seen during BW (comfortable β = 0.57; fast β = 0.58) compared to FW (comfortable β = 0.41; fast β = 0.45). Fallers performed significantly worse than non-fallers for vibration sensation (P = 0.04). Discussion and Conclusions: Considering the notable decrease in proprioception in participants with MS and the clear distinction between fallers and non-fallers, it is crucial to conduct fall risk assessments and interventions focusing on proprioception. With its heightened reliance on proprioception, BW offers a promising method for assessing fall risk and could be an effective exercise intervention. Video Abstract available for more insights from the authors (see the Supplemental Digital Content available at: http://links.lww.com/JNPT/A490).

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device.

Freezing of Gait (FOG) is prevalent in people with Parkinson's disease (PD) and severely disrupts mobility. Detecting the exact boundaries of FOG episodes may facilitate new technologies in "breaking" FOG in real-time. This study investigates the performance of automatic device-based FOG detection. Eight machine-learning classifiers (including Neural Networks, Ensemble methods, and Support Vector Machines) were developed using (i) accelerometer and (ii) combined accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed mobility tasks designed to elicit FOG. Two clinicians independently annotated exact FOG episodes using synchronized video and a flowchart algorithm based on international guidelines. Device-detected FOG episodes were compared to annotated episodes using 10-fold cross-validation and Interclass Correlation Coefficients (ICC) for agreement. Development used 50,962 windows of data and annotated activities (>10 hours). Strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity, and ICC1,1 = 0.97 for total FOG duration). Device performance varied by method, complexity, and cost matrix. The Neural Network using 67 accelerometer features achieved high sensitivity to FOG (89% sensitivity, 81% specificity, and ICC1,1 = 0.83) and stability (validation loss 5%). The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The strong clinician agreement indicates room for improvement in future device-based FOG detection. This study may enhance PD care by reducing reliance on visual FOG inspection, demonstrating that high sensitivity in automatic FOG detection is achievable.

Remote Gait Analysis Using Ultra-Wideband Radar Technology Based on Joint Range-Doppler-Time Representation.

In recent years, radar technology has been extensively utilized in contactless human behavior monitoring systems. The unique capabilities of ultra-wideband (UWB) radars compared to conventional radar technologies, due to time-of-flight measurements, present new untapped opportunities for in-depth monitoring of human movement during overground locomotion. This study aims to investigate the deployability of UWB radars in accurately capturing the gait patterns of healthy individuals with no known walking impairments. A novel algorithm was developed that can extract ten clinical spatiotemporal gait features using the Doppler information captured from three monostatic UWB radar sensors during a 6-meter walking task. Key gait events are detected from lower-extremity movements based on the joint range-Doppler-time representation of recorded radar data. The estimated gait parameters were validated against a gold-standard optical motion tracking system using 12 healthy volunteers. On average, nine gait parameters can be consistently estimated with 90-98% accuracy, while capturing 94.5% of participants' gait variability and 90.8% of inter-limb symmetry. Correlation and Bland-Altman analysis revealed a strong correlation between radar-based parameters and the ground-truth values, with average discrepancies consistently close to 0. Results prove that radar sensing can provide accurate biomarkers to supplement clinical human gait analysis, with quality similar to gold standard assessment. Radars can potentially allow a transition from expensive and cumbersome lab-based gait analysis tools toward a completely unobtrusive and affordable solution for in-home deployment, enabling continuous long-term monitoring of individuals for research and healthcare applications.

Evaluation of a finite state machine algorithm to measure stepping with ankle accelerometry: performance across a range of gait speeds, tasks, and individual walking ability.

Wearable sensors, including accelerometers, are a widely accepted tool to assess gait in clinical and free-living environments. Methods to identify phases and subphases of the gait cycle are necessary for comprehensive assessment of pathological gait. The current study evaluated the accuracy of a finite state machine (FSM) algorithm to detect strides by identifying gait cycle subphases from ankle-worn accelerometry. Algorithm performance was challenged across a range of speeds (0.4-2.6 m/s), task conditions (e.g., single- and dual-task walking), and individual characteristics. Specifically, the study included a range of treadmill speeds in young adults and overground walking conditions in older adults with neurological disease. Manually counted and algorithm-derived stride detection from acceleration data were evaluated using error analysis and Bland-Altman plots for visualization. Overall, the algorithm successfully detected strides (>96% accuracy) across gait speed ranges and tasks, for young and older adults. The accuracy of an FSM algorithm combined with ankle-worn accelerometers, provides an analytical approach with affordable and portable tools that permits comprehensive assessment of gait unbounded by setting and proves to perform well in in walking tasks characterized by variable walking. These algorithm capabilities and advancements are critical for identifying phase dependent gait impairments in clinical and free-living assessment.

Effect of task difficulty on dual-task cost during dual-task walking in people with multiple sclerosis

BackgroundCognitive-motor dual-task walking results a decrease in walking performance of patients with multiple sclerosis (PwMS) and it is known as dual-task cost (DTC). However, there is a lack of evidence about the effects of dual-tasks with hierarchical difficulty on DTC in PwMS. Research questionThis study aimed to investigate the effect of task difficulty on DTC during cognitive-motor dual-task walking in people with multiple sclerosis (PwMS). Methods32 PwMS and 32 healthy controls were included. The 6-meter walking test (6-Meter WT) with comfortable speed was used as single-task walking condition. For dual-task conditions, walking tasks and cognitive tasks at two difficulty levels (simple and difficult) were combined and DTC for four cognitive-motor dual-task walking conditions as simple motor-simple cognitive (SM-SC), simple motor-difficult cognitive (SM-DC), difficult motor-simple cognitive (DM-SC) and difficult motor-difficult cognitive (DM-DC) were calculated. The 6-Meter WT was used also for simple dual-task walking task. The 6-Meter WT was applied by walking in a narrow base condition for creating a difficult dual-task walking task. For cognitive task difficulty, participants were asked to count backwards by 3 as simple cognitive task and by 7 as difficult cognitive task. ResultsDTC was higher in PwMS than control subjects. DTC in all conditions were different (SM-SC<SM-DC<DM-SC<DM-DC). DTC was higher in PwMS than control subjects in three conditions and was similar SM-SC condition. In addition, DTC in all conditions (SM-SC<SM-DC<DM-SC<DM-DC) were different in both PwMS and control subjects. ConclusionThe results suggest that task difficulty affects the magnitude of DTC during cognitive-motor dual-task walking in PwMS. Moreover, difficult walking tasks combined with simple cognitive tasks result greater DCT on walking than simple walking tasks combined with difficult cognitive tasks.

Long COVID patients' brain activation is suppressed during walking and severer symptoms lead to stronger suppression.

This research aims to study the factors contributing to Long COVID and its effects on motor and cognitive brain regions using population surveys and brain imaging. The goal is to provide new insights into the neurological effects of the illness and establish a basis for addressing neuropsychiatric symptoms associated with Long COVID. Study 1 used a cross-sectional design to collect data on demographic characteristics and factors related to Long COVID symptoms in 551 participants. In Study 2, subjects with Long COVID and SARS-CoV-2 uninfected individuals underwent fNIRS monitoring while performing various tasks. Study 1 found that gender, age, BMI, Days since the first SARS-CoV-2 infection, and Symptoms at first onset influenced Long COVID performance. Study 2 demonstrated that individuals in the SARS-CoV-2 uninfected group exhibited greater activation of cognitive function-related brain regions than those in the Long COVID group while performing a level walking task. Furthermore, individuals in the Long COVID group without functional impairment displayed higher activation of brain regions associated with motor function during a weight-bearing walking task than those with functional impairment. Among individuals with Long COVID, those with mild symptoms at onset exhibited increased activation of brain regions linked to motor and cognitive function relative to those with moderate symptoms at onset. Individuals with Long COVID exhibited decreased activation in brain regions associated with cognitive and motor function compared to SARS-CoV-2 uninfected individuals. Moreover, those with more severe initial symptoms or functional impairment displayed heightened inhibition in these brain regions.

Exploring the effects of increased socket-residual limb coupling integrity via vacuum assisted suspension on prosthetic control: a preliminary study in transtibial prosthesis users.

The prosthetic socket provides the critical interface between prosthesis and residuum. The purpose of this pilot study was to explore the effect of altering socket-residuum coupling integrity on limb and body control, through the use of vacuum-assisted suspension. A secondary purpose was to explore the potential use of two measurement tools designed to assess mobility in a clinical context. Individuals with unilateral transtibial amputation performed intentional sway (n = 7) and treadmill walking (n = 6) tasks at three vacuum levels. Sway deviation from a straight-line path to peripheral targets was measured using an instrumented balance platform. Step width variability and targeting accuracy were measured using an augmented reality treadmill. There was a significant difference in intentional sway performance toward the target on the anterior diagonal toward the prosthetic side (p = 0.036); higher vacuum levels tended toward less deviation from a straight-line path. We found no group differences between total intentional sway deviation, step width variability or stepping accuracy across vacuum levels. Improved socket-residuum coupling integrity via vacuum may have measurable effects on functional control that warrant further investigation. We highlight limitations of the clinical testing paradigms to inform future work.Implications for rehabilitationThe fit of the socket is a critical factor in the success of lower limb prosthesis use.Vacuum-assisted suspension modifies the coupling between the residuum and socket.Changes in socket-residuum coupling may lead to measurable differences in control; however, these may be activity and person-specific.Clinically intended instrumented tests of movement function derived for an intact anatomy should be used with caution when assessing prosthesis users.

Effects of prefabricated arch-support insole hardness on foot pressure and muscle activity in mountaineer porters during load-bearing tasks in mountainous terrain

BackgroundThe study aimed to compare the effects of medium hardness and high hardness arch-support insoles, with the latter modified by a soft forefoot pad, on foot pressure distribution and muscle activation during high-load carrying tasks in authentic mountainous trail environments. MethodsSixteen male mountaineer porters with experience in high-load carrying tasks participated in the experiments. They wore commercially available prefabricated arch-support insoles, specifically referred to as medium hardness arch-support material (MH) and high hardness arch-support material attached a 1-mm soft sponge pad to the forefoot area (HHSF) during uphill and downhill walking tasks with a 25-kg load. Foot pressure and muscle activation were measured using wireless pressure distribution insoles and a wireless surface electromyography system, respectively. ResultsThe HHSF showed significantly higher perceived comfort scores and reduced foot pressure in specific regions during downhill walking (p < 0.05). It exhibited increased peak foot pressure in the forefoot during uphill walking (p < 0.05). The MH showed greater foot pressure in the second metatarsal during downhill walking and a larger contact area in the midfoot during uphill walking (p < 0.05). Muscle activation did not differ significantly between the two insoles (p > 0.05). ConclusionThe study indicates that combining a high hardness arch-support insole with a soft forefoot pad may enhance comfort and potentially reduce foot injury risks, and improves foot propulsion and pressure distribution.

Disability Moderates Dual Task Walking Performance and Neural Efficiency in Older Adults With Multiple Sclerosis.

Mobility and cognitive impairment are prevalent and co-occurring in older adults with multiple sclerosis (OAMS), yet there is limited research concerning the role of disability status in the cognitive control of gait among OAMS. We investigated the levels of prefrontal cortex (PFC) activation, using oxygenated hemoglobin (HbO2), during cognitively-demanding tasks in OAMS with lower and higher disability using functional near-infrared spectroscopy (fNIRS) to: (1) identify PFC activation differences in single task walk and cognitively-demanding tasks in OAMS with different levels of disability; and (2) evaluate if disability may moderate practice-related changes in neural efficiency in OAMS. We gathered data from OAMS with lower (n = 51, age = 65 ± 4 years) or higher disability (n = 48, age = 65 ± 5 years), using a cutoff of 3 or more, in the Patient Determined Disease Steps, for higher disability, under 3 different conditions (single-task walk, Single-Task-Alpha, and Dual-Task-Walk [DTW]) administered over 3 counterbalanced, repeated trials. OAMS who had a lower disability level exhibited decreased PFC activation levels during Single-Task-Walk (STW) and larger increases in PFC activation levels, when going from STW to a cognitively-demanding task, such as a DTW, than those with higher disability. OAMS with a lower disability level exhibited greater declines in PFC activation levels with additional within session practice than those with a higher disability level. These findings suggest that disability moderates brain adaptability to cognitively-demanding tasks and demonstrate the potential for fNIRS-derived outcome measures to complement neurorehabilitation outcomes.

Contralateral cutaneous reflex modulation during gait in individuals with and without chronic ankle instability

IntroductionChronic ankle instability (CAI), a common seqeula to ankle injury is characterized by a variety of sensorimotor deficits extending beyond the previously injured limb. Cutaneous reflexes have been identified as a potential contributor to these functional limitations with recent studies identifying alterations in reflex patterns following sural nerve stimulation among those with CAI. To date, no studies have measured cutaneous reflexes of the unaffected limb in this population, therefore, the objective of this study was to measure contralateral cutaneous reflexes during gait in individuals with unilateral CAI and healthy controls. MethodsMuscle activity of 6 lower limb muscles was measured in nineteen participants while receiving random, non-noxious sural nerve stimulations during a walking task. ResultsControl reflex patterns were generally well-aligned with previous literature while CAI patterns varied from controls in several muscles throughout the gait cycle. Namely, a lack of lateral gastrocnemius facilitation during late stance and medial gastrocnemius inhibition at midstance. Additionally, a lack of significant BF facilitation throughout contralateral swing was noted. These results indicate reflex alterations extend beyond the affected limb in those with unilateral CAI indicating changes at the spinal level following lateral ankle sprains (LAS). Considering the symptom variability in CAI, the lack of significant reflexes exhibited by the CAI group may be due to increased variability in motor output between subjects or between stimulation trials. ConclusionsThese findings highlight the importance of identifying reflex alterations arising from LAS and subsequently treating these limitations through rehabilitation targeting systemic neural pathways rather than local deficits.

The allocentric nature of ground-surface representation: A study of depth and location perception

When observers perceive 3D relations, they represent depth and spatial locations with the ground as a reference. This frame of reference could be egocentric, that is, moving with the observer, or allocentric, that is, remaining stationary and independent of the moving observer. We tested whether the representation of relative depth and of spatial location took an egocentric or allocentric frame of reference in three experiments, using a blind walking task. In Experiments 1 and 2, participants either observed a target in depth, and then straightaway blind walked for the previously seen distance between the target and the self; or walked to the side or along an oblique path for 3 m and then started blind walking for the previously seen distance. The difference between the conditions was whether blind walking started from the observation point. Results showed that blind walking distance varied with the starting locations. Thus, the represented distance did not seem to go through spatial updating with the moving observer and the frame of reference was likely allocentric. In Experiment 3, participants observed a target in space, then immediately blind walked to the target, or blind walked to another starting point and then blind walked to the target. Results showed that the end location of blind walking was different for different starting points, which suggested the representation of spatial location is likely to take an allocentric frame of reference. Taken together, these experiments convergingly suggested that observers used an allocentric frame of reference to construct their mental space representation.

A study on machine learning-based prediction of cerebellar ataxia using gait analysis and accelerometer data

In the neurological field, predicting Cerebellar Ataxia (CA) is based on analyzing gait values of human actions. Analyzing Gait (AoG) can potentially guide effective treatment strategies. This study aimed to create a machine-learning model for predicting AoG using gait patterns indicative of pre-AoG conditions. During the execution of designed walking tasks to provokeAoG, accelerometers were attached to the lower back of 21 subjects as they performed 12 different walking positions to collect acceleration impulses. The participants engaged in walking exercises for one minute at 12 different walking speeds on a split-belt treadmill, ranging from 0.6 to 1.7 m/s in 0.1 m/s increments. The speed sequence was randomized and concealed from the subjects to minimize fatigue effects. Prior research studies have surveyed machine-learning algorithms such as support vector machine (SVM) and k-nearest neighbors (KNN). These algorithms demonstrate strong performance, especially when the dataset is trivial, and the classification is binary. SVM, KNN, decision trees, and XGBoost algorithms were utilized in the proposed study on the CA dataset. Our findings revealed that the AdaBoost algorithm, with its high precision, offers a more precise categorisation of the severity of CA disease, instilling confidence in the study's findings.

The Time Course of Changes in Prefrontal Cortex Activity During Walking in People With Parkinson’s Disease

Background Walking abnormalities in people with Parkinson’s disease (PD) are characterized by a shift in locomotor control from healthy automaticity to compensatory, executive control, mainly located in the prefrontal cortex (PFC). Although PFC activity during walking increases in people with PD, the time course of PFC activity during walking and its relationship to clinical or gait characteristics is unknown. Objective To identify the time course of PFC activity during walking in people with PD. To investigate whether clinical or gait variables would explain the PFC activity changes. Methods Thirty-eight people with PD tested OFF medication wore a portable, functional near-infrared spectroscopy (fNIRS) system to record relative PFC activity while walking. Wearable inertial sensors recorded spatiotemporal gait characteristics. Based on the PFC activity (fNIRS) in the late phase of the walking task (final 40 seconds), compared to the early phase (initial 40 seconds), participants were separated into 2 groups: reduced or sustained PFC activity. Results People with PD who reduced PFC activity during walking had less impaired gait (eg, faster gait speed) than those who had a sustained increase in PFC activity (P < .05). Cognitive set-shifting ability explained 18% of the PFC activation in the group with a sustained increase in PFC activity (P = .033). Conclusions The time course of reduction in PFC activity corresponds to less impaired gait performance in people with PD, while a sustained increase in PFC activity is related to worse cognitive flexibility. Reduction in PFC activity while walking may indicate a less impaired, automatic control of walking.

Joint synergy and muscle activity in the motion of the ankle-foot complex.

The movement of the ankle-foot complex joints is coupled as a result of various physiological and physical constraints. This study introduces a novel approach to the analysis of joint synergies and their physiological basis by focusing on joint rotational directions and the types of muscle contractions. We developed a biomimetic model of the ankle-foot complex with seven degrees of freedom, considering the skeletal configuration and physiological axis directions. Motion capture experiments were conducted with eight participants performing dorsiflexion and plantarflexion in open-chain states, as well as various walking tasks in closed-chain states, across different ground inclinations (±10, ±5, 0deg) and walking speeds (3 and 4 km h-1). Hierarchical cluster analysis identified joint synergy clusters and motion primitives, revealing that in open-chain movements, plantarflexion of the ankle, tarsometatarsal and metatarsophalangeal joints exhibited synergy with the inversion of the remaining joints in the complex; meanwhile, dorsiflexion was aligned with eversion. During closed-chain movements, the synergies grouping was exchanged in the subtalar, talonavicular and metatarsophalangeal joints. Further analysis showed that in open-chain movements, synergy patterns influenced by multi-joint muscles crossing oblique joint axes contribute to foot motion. In closed-chain movements, these changes in synergistic patterns enhance the propulsion of the center of mass towards the contralateral leg and improve foot arch compliance, facilitating human motion. Our work enhances the understanding of the physiological mechanisms underlying synergistic motion within the ankle-foot complex.

Unraveling stroke gait deviations with movement analytics, more than meets the eye: a case control study.

This study aimed to identify and quantify the kinematic and kinetic gait deviations in post-stroke hemiplegic patients with matched healthy controls using Statistical Parametric Mapping (SPM). Fifteen chronic stroke patients [4 females, 11 males; age 53.7 (standard deviation 12.2) years; body mass 65.4 (10.4) kg; standing height 168.5 (9.6) cm] and 15 matched healthy controls [4 females, 11 males; age 52.9 (11.7) years; body weight 66.5 (10.7) years; standing height 168.3 (8.8) cm] were recruited. In a 10-m walking task, joint angles, ground reaction forces (GRF), and joint moments were collected, analyzed, and compared using SPM for an entire gait cycle. Generally, when comparing the stroke patients' affected (hemiplegic) and less-affected (contralateral) limbs with the control group, SPM identified significant differences in the late stance phase and early swing phase in the joint angles and moments in bilateral limbs (all p < 0.005). In addition, the vertical and anteroposterior components of GRF were significantly different in various periods of the stance phase (all p < 0.005), while the mediolateral component showed no differences between the two groups. SPM was able to detect abnormal gait patterns in both the affected and less-affected limbs of stroke patients with significant differences when compared with matched controls. The findings draw attention to significant quantifiable gait deviations in the less-affected post-stroke limb with the potential impact to inform gait retraining strategies for clinicians and physiotherapists.

Automatic Parkinson’s Disease Diagnosis with Wearable Sensor Technology for Medical Robot

The clinical diagnosis of Parkinson’s disease (PD) has been the subject of medical robotics research. Currently, a hot research topic is how to accurately assess the severity of Parkinson’s disease patients and enable medical robots to better assist patients in the rehabilitation process. The walking task on the Unified Parkinson’s Disease Rating Scale (UPDRS) is a well-established diagnostic criterion for PD patients. However, the clinical diagnosis of PD is determined based on the clinical experience of neurologists, which is subjective and inaccurate. Therefore, in this study, an automated diagnostic method for PD based on an improved multiclass support vector machine (MCSVM) is proposed in which wearable sensors are used. Kinematic analysis was performed to extract gait features, both spatiotemporal and kinematic, from the installed IMU and pressure sensors. Comparison experiments of three different kernel functions and linear trajectory experiments were designed. The experimental results show that the accuracies of the three kernel functions of the proposed improved MCSVM are 92.43%, 93.45%, and 95.35%. The simulation trajectories of the MCSVM are the closest to the real trajectories, which shows that the technique performs better in the clinical diagnosis of PD.

Functional and structural neurodegenerative activities of Ankaferd BloodStopper in a mouse sciatic nerve model.

Traumatic and postoperative hemorrhages are life-threatening complications. Ankaferd BloodStopper (ABS) is a potent topical hemostatic agent to stop bleeding. However, ABS is associated with nerve toxicity. The present study aimed to investigate the functional and structural neurodegenerative effects of ABS in a mouse model. A total of 30 male BALB/c mice, aged 6-8 weeks, were randomly divided into control group (no treatment), a sham group (treated with saline) and an experimental group (treated with ABS). In the saline and the ABS groups, the right sciatic nerve was surgically exposed and treated with saline or ABS, respectively. No surgical procedure was performed in the control group. On day 7 post-treatment, functional changes of the sciatic nerve were evaluated by a horizontal ladder rung walking task. Structural changes were assessed with immunohistochemistry. In the horizontal ladder rung walking test, the gait impairment was proportional to the severity of sciatic nerve damage, with the ABS group showing a significantly higher rate of errors than the control and saline groups. Immunohistochemistry demonstrated extensive degeneration and deformation in the axons and myelin sheath of the sciatic nerve in the ABS group. The results provide compelling evidence for the neurotoxicity of ABS.

Comparable cerebral cortex activity and gait performance in elderly hypertensive and healthy individuals during dual-task walking: A fNIRS study.

Hypertension increases the risk of cognitive impairment and related dementia, causing impaired executive function and unusual gait parameters. However, the mechanism of neural function illustrating this is unclear. Our research aimed to explore the differences of cerebral cortex activation, gait parameters, and working memory performance between healthy older adults (HA) and older hypertensive (HT) patients when performing cognitive and walking tasks. A total of 36 subjects, including 12 healthy older adults and 24 older hypertensive patients were asked to perform series conditions including single cognitive task (SC), single walking task (SW), and dual-task (DT), wearing functional near-infrared spectroscopy (fNIRS) equipment and Intelligent Device for Energy Expenditure and Activity equipment to record cortical hemodynamic reactions and various gait parameters. The left somatosensory cortex (L-S1) and bilateral supplementary motor area (SMA) showed higher cortical activation (p<.05) than HA when HT performed DT. The intragroup comparison showed that HT had higher cortical activation (p<.05) when performing DT as SW. The cognitive performance of HT was significantly worse (p<.05) than HA when executing SC. The activation of the L-S1, L-M1, and bilateral SMA in HT were significantly higher during SW (p<.05). Hypertension can lead to cognitive impairment in the elderly, including executive function and walking function decline. As a result of these functional declines, elderly patients with hypertension are unable to efficiently allocate brain resources to support more difficult cognitive interference tasks and need to meet more complex task demands by activating more brain regions.

Measuring gait parameters from a single chest-worn accelerometer in healthy individuals: a validation study

Digital health technologies (DHTs) are increasingly being adopted in clinical trials, as they enable objective evaluations of health parameters in free-living environments. Although lumbar accelerometers notably provide reliable gait parameters, embedding accelerometers in chest devices, already used for vital signs monitoring, could capture a more comprehensive picture of participants’ wellbeing, while reducing the burden of multiple devices. Here we assess the validity of gait parameters measured from a chest accelerometer. Twenty healthy adults (13 females, mean ± sd age: 33.9 ± 9.1 years) instrumented with lumbar and chest accelerometers underwent in-lab and outside-lab walking tasks, while monitored with reference devices (an instrumented mat, and a 6-accelerometers set). Gait parameters were extracted from chest and lumbar accelerometers using our open-source Scikit Digital Health gait (SKDH-gait) algorithm, and compared against reference values via Bland–Altman plots, Pearson’s correlation, and intraclass correlation coefficient. Mixed effects regression models were performed to investigate the effect of device, task, and their interaction. Gait parameters derived from chest and lumbar accelerometers showed no significant difference and excellent agreement across all tasks, as well as good-to-excellent agreement and strong correlation against reference values, thus supporting the deployment of a single multimodal chest device in clinical trials, to simultaneously measure gait and vital signs.Trial Registration: The study was reviewed and approved by the Advarra IRB (protocol number: Pro00043100).