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Background While walking, people swing their arms in a specific pattern. This specific arm swing pattern during walking has shown to have a beneficial effect on gait as it reduces walking energy cost and optimizes balance. In several patient populations the arm movements can be directly affected (e.g. in patients with acquired brain injury (ABI)), which in turn has a negative effect on their gait pattern, balance and energy cost of walking. Main text In December 2019, Kahn et al. published a paper in JNER concerning the quantification of upper limb associated reactions (ARs) during walking in people with ABI. ARs are defined as “an effort-dependent phenomenon causing an involuntary increase in upper limb muscle tone, with awkward and uncomfortable postures”. These upper limb ARs appear often in patients with ABI and can have an important effect on their gait. The authors calculated kinematic measures using three-dimensional gait analysis relating to range of motion, variability and mean position over the gait cycle for the different upper limb joints (shoulder, elbow, wrist) during self-selected steady-state walking. Based on differences they found between an ABI cohort and healthy control cohort, the authors concluded that they were able to quantify ARs during walking in this population. This calculation, however, is not specific for upper limb ARs. In fact, the authors calculated general measures of arm posture (e.g. mean position over the gait cycle) or arm movement (e.g. range of motion and variability) during gait. Previous research has already indicated that other factors than ARs can influence the posture or movement of the arm during gait in patients with brain injury, such as voluntary compensations for gait instability and contractures or spasticity of upper arm muscles. Yet, it is not possible to disentangle the different causes of the altered arm posture during steady-state walking based on the proposed measures. Conclusion The kinematic arm measures proposed by Kahn et al. (J Neuroeng Rehabil 16(1):160, 2019) are not a direct measure of ARs, but provide a quantification of overall deviation of arm posture or movement during gait. Depending on the specific study design these measures may provide insights in ARs.

Training fall-resisting skills can prevent falls in older adults. These fall-resisting skills include proactive gait adaptability, gait robustness, and reactive gait recovery, which allow people to effectively avoid, resist, and recover from balance threats, respectively. This pilot study guided the design of an RCT of fall-resisting skills training by investigating key design factors, such as the design of a placebo-control group, obstacle difficulty settings, exploring evaluation methods for gait robustness, testing the effect of task unpredictability on anxiety, and the general feasibility. Eleven healthy older adults performed non-task-specific “placebo” balance tasks and assessment and training tasks for each fall-resisting skill. Placebo tasks included static weight-shifting exercises and dual-task walking. For the fall-resisting skill tasks, participants walked on a treadmill under different conditions. For proactive gait adaptability, participants avoided projected obstacles varying in size, approach speed, and available response time. Gait robustness was assessed using perturbations of increasing magnitude, where the margin of stability following each perturbation was compared with participants’ perceived balance loss and researchers’ observations. For reactive gait recovery, perturbations with increasing unpredictability were applied, after which participants reported their anxiety scores. Weight-shifting tasks were perceived as balance training by most participants, indicating their potential as placebo tasks. Obstacle avoidance difficulty increased most with fast approach speed and large obstacle sizes. A margin of stability-based threshold did not consistently align with perceived balance loss or observer judgement. Anxiety did not increase with more unpredictable perturbation tasks when introduced gradually. Fall-resisting skill tasks generally were feasible for older adults.

Observational research suggests that in children with cerebral palsy, the altered arm swing is linked to instability during walking. Therefore, the current study investigates whether children with cerebral palsy use their arms more than typically developing children, to enhance gait stability. Evidence also suggests an influence of walking speed on gait stability. Moreover, previous research highlighted a link between walking speed and arm swing. Hence, the experiment aimed to explore differences between typically developing children and children with cerebral palsy taking into account the combined influence of restricting arm swing and increasing walking speed on gait stability. Spatiotemporal gait characteristics, trunk movement parameters and margins of stability were obtained using three dimensional gait analysis to assess gait stability of 26 children with cerebral palsy and 24 typically developing children. Four walking conditions were evaluated: (i) free arm swing and preferred walking speed; (ii) restricted arm swing and preferred walking speed; (iii) free arm swing and high walking speed; and (iv) restricted arm swing and high walking speed. Double support time and trunk acceleration variability increased more when arm swing was restricted in children with bilateral cerebral palsy compared to typically developing children and children with unilateral cerebral palsy. Trunk sway velocity increased more when walking speed was increased in children with unilateral cerebral palsy compared to children with bilateral cerebral palsy and typically developing children and in children with bilateral cerebral palsy compared to typically developing children. Trunk sway velocity increased more when both arm swing was restricted and walking speed was increased in children with bilateral cerebral palsy compared to typically developing children. It is proposed that facilitating arm swing during gait rehabilitation can improve gait stability and decrease trunk movements in children with cerebral palsy. The current results thereby partly support the suggestion that facilitating arm swing in specific situations possibly enhances safety and reduces the risk of falling in children with cerebral palsy.

Shifts of the center of pressure (CoP) through modulation of foot placement and ankle moments (CoP-mechanism) cause accelerations of the center of mass (CoM) that can be used to stabilize gait. An additional mechanism that can be used to stabilize gait, is the counter-rotation mechanism, i.e., changing the angular momentum of segments around the CoM to change the direction of the ground reaction force. The relative contribution of these mechanisms to the control of the CoM is unknown. Therefore, we aimed to determine the relative contribution of these mechanisms to control the CoM in the anteroposterior (AP) direction during a normal step and the first recovery step after perturbation in healthy adults. Nineteen healthy subjects walked on a split-belt treadmill and received unexpected belt acceleration perturbations of various magnitudes applied immediately after right heel-strike. Full-body kinematic and force plate data were obtained to calculate the contributions of the CoP-mechanism and the counter-rotation mechanism to control the CoM. We found that the CoP-mechanism contributed to corrections of the CoM acceleration after the AP perturbations, while the counter-rotation mechanism actually counteracted the CoM acceleration after perturbation, but only in the initial phases of the first step after the perturbation. The counter-rotation mechanism appeared to prevent interference with the gait pattern, rather than using it to control the CoM after the perturbation. Understanding the mechanisms used to stabilize gait may have implications for the design of therapeutic interventions that aim to decrease fall incidence.

Introduction. Spatiotemporal gait parameters, e.g., gait stride length, are measurements that are classically derived from instrumented gait analysis. Today, different solutions are available for gait assessment outside the laboratory, specifically for spatiotemporal gait parameters. Such solutions are wearable devices that comprise an inertial measurement unit (IMU) sensor and a microcontroller (MCU). However, these existing wearable devices are resource-constrained. They contain a processing unit with limited processing and memory capabilities which limit the use of machine learning to estimate spatiotemporal gait parameters directly on the device. The solution for this limitation is embedded machine learning or tiny machine learning (tinyML). This study aims to create a machine-learning model for gait stride length estimation deployable on a microcontroller. Materials and Method. Starting from a dataset consisting of 4467 gait strides from 15 healthy people, measured by IMU sensor, and using state-of-the-art machine learning frameworks and machine learning operations (MLOps) tools, a multilayer 1D convolutional float32 and int8 model for gait stride length estimation was developed. Results. The developed float32 model demonstrated a mean accuracy and precision of 0.23 ± 4.3 cm, and the int8 model demonstrated a mean accuracy and precision of 0.07 ± 4.3 cm. The memory usage for the float32 model was 284.5 kB flash and 31.9 kB RAM. The int8 model memory usage was 91.6 kB flash and 13.6 kB RAM. Both models were able to be deployed on a Cortex-M4F 64 MHz microcontroller with 1 MB flash memory and 256 kB RAM. Conclusions. This study shows that estimating gait stride length directly on a microcontroller is feasible and demonstrates the potential of embedded machine learning, or tinyML, in designing wearable sensor devices for gait analysis.

Functional near-infrared spectroscopy (fNIRS) is particularly suitable for measuring brain activity during motor tasks, due to its portability and good motion tolerance. In such cases, the trials’ duration may vary depending on the experimental conditions or the participant’s response, therefore a comparison of hemodynamic responses across repetitions cannot be properly performed. In this work, we present a MATLAB (R2023a) function (TaskNorm.m) developed for time-normalizing fNIRS data recorded during trials with different durations. It is based on a spline interpolation method that rescales the time -axis to the percentage of the trial with a fixed number of samples. This allows us to successively average across repetitions to obtain the mean hemodynamic responses and complete the standard data processing. The algorithm was tested on eight subjects (four with developmental coordination disorder, age: 9.78 ± 0.30 and four typically developing children, age: 9.02 ± 0.30) performing three different tasks. The results show that the TaskNorm function works as expected, allowing both a comparison and averaging of the data across multiple repetitions. The performance of the function is independent of the task or the pre-processing pipeline applied. The proposed function is publicly available and importable into the HomER3 package (v1.72.0), representing a further step in the ongoing standardization process of fNIRS data analysis.

Folk psychology advocates the existence of gender differences in socio-cognitive functions such as 'reading' the mental states of others or discerning subtle differences in body-language. A female advantage has been demonstrated for emotion recognition from facial expressions, but virtually nothing is known about gender differences in recognizing bodily stimuli or body language. The aim of the present study was to investigate potential gender differences in a series of tasks, involving the recognition of distinct features from point light displays (PLDs) depicting bodily movements of a male and female actor. Although recognition scores were considerably high at the overall group level, female participants were more accurate than males in recognizing the depicted actions from PLDs. Response times were significantly higher for males compared to females on PLD recognition tasks involving (i) the general recognition of 'biological motion' versus 'non-biological' (or 'scrambled' motion); or (ii) the recognition of the 'emotional state' of the PLD-figures. No gender differences were revealed for a control test (involving the identification of a color change in one of the dots) and for recognizing the gender of the PLD-figure. In addition, previous findings of a female advantage on a facial emotion recognition test (the 'Reading the Mind in the Eyes Test' (Baron-Cohen, 2001)) were replicated in this study. Interestingly, a strong correlation was revealed between emotion recognition from bodily PLDs versus facial cues. This relationship indicates that inter-individual or gender-dependent differences in recognizing emotions are relatively generalized across facial and bodily emotion perception. Moreover, the tight correlation between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion provides indications that differences in emotion recognition may - at least to some degree - be related to more basic differences in processing biological motion per se.

The aim of this pilot study was to investigate the feasibility of markerless tracking to assess upper body movements of children with and without human immunodeficiency virus encephalopathy (HIV-E). Sagittal and frontal video recordings were used to track anatomical landmarks with the DeepLabCut pre-trained human model in five children with HIV-E and five typically developing (TD) children to calculate shoulder flexion/extension, shoulder abduction/adduction, elbow flexion/extension and trunk lateral sway. Differences in joint angle trajectories of the two cohorts were investigated using a one-dimensional statistical parametric mapping method. Children with HIV-E showed a larger range of motion in shoulder abduction and trunk sway than TD children. In addition, they showed more shoulder extension and more lateral trunk sway compared to TD children. Markerless tracking was feasible for 2D movement analysis and sensitive to observe expected differences in upper limb and trunk sway movements between children with and without HIVE. Therefore, it could serve as a useful alternative in settings where expensive gait laboratory instruments are unavailable, for example, in clinical centers in low- to middle-income countries. Future research is needed to explore 3D markerless movement analysis systems and investigate the reliability and validity of these systems against the gold standard 3D marker-based systems that are currently used in clinical practice.

Proprioceptive deficits can lead to impaired motor performance. Therefore, accurately measuring proprioceptive function in order to identify deficits as soon as possible is important. Techniques based on deep learning to track body landmarks in simple video recordings are promising to assess proprioception (joint position sense) during joint position reproduction (JPR) tests in clinical settings, outside the laboratory and without the need to attach markers. Fifteen typically developing children participated in 90 knee JPR trials and 21 typically developing children participated in 126 hip JPR trials. Concurrent validity of two-dimensional deep-learning-based motion capture (DeepLabCut) to measure the Joint Reproduction Error (JRE) with respect to laboratory-based optoelectronic three-dimensional motion capture (Vicon motion capture system, gold standard) was assessed. There was no significant difference in the hip and knee JRE measured with DeepLabCut and Vicon. Two-dimensional deep-learning-based motion capture (DeepLabCut) is valid to assess proprioception with respect to the gold standard in typically developing children. Tools based on deep learning, such as DeepLabCut, make it possible to accurately measure joint angles in order to assess proprioception without the need of a laboratory and to attach markers, with a high level of automatization.

Background: Vestibular hypofunction occurs in 29.5% of older adults with benign paroxysmal positional vertigo (BPPV), but its impact on postural control, well-being and frailty was not studied before. This study compared the well-being, frailty and postural control between older adults with BPPV and vestibular hypofunction (oaBPPV+), and older adults with only BPPV (oaBPPV). Methods: Thirty-one older adults (≥65 years old) diagnosed with BPPV were recruited. Unilateral vestibular hypofunction was defined as a >25% caloric asymmetry, and bilateral vestibular hypofunction as a total response <6°/s per ear, using bithermal caloric irrigations. The oaBPPV+ group was compared to the oaBPPV group using the measures of well-being (Dizziness Handicap Inventory, Falls Efficacy Scale and 15-item Geriatric Depression Scale), frailty (Modified Fried Criteria), and postural control (timed chair stand test, mini-Balance Evaluation Systems test and Clinical Test of Sensory Interaction on Balance (CTSIB)). Falls and the number of repositioning maneuvers were documented. Significance level was set at α = 0.05. Results: Unilateral vestibular hypofunction was present in 32% of participants, mainly in females (p = 0.04). Bilateral vestibular hypofunction was not found. The oaBPPV+ group (n = 10, mean age 72.5 (4.5)) experienced more comorbidities (p = 0.02) than the oaBPPV group (n = 21, mean age 72.6 (4.9)). Groups did not differ regarding dizziness symptoms (p = 0.46), fear of falling (p = 0.44), depression (p = 0.48), falls (p = 0.08) or frailty (p = 0.36). However, the oaBPPV+ group showed significantly worse postural control under vestibular-dependent conditions (p < 0.001). Conclusions: Despite equally impaired well-being and frailty, the oaBPPV+ group showed greater sensory orientation deficits. Clinicians and researchers should be alert for co-existing vestibular hypofunction in older adults with BPPV, since this may exacerbate their already impaired postural control more than only BPPV.