Neurological soft signs in adolescents are associated with brain structure and postural control

Neurological soft signs (NSS) are minor deviations from the norm in sensory and motor performance. NSS exist in the general population but are more frequently found in cohorts with neurodevelopmental disorders. NSS are considered a diffuse and unspecific marker of altered neurodevelopment but receive increasing attention since the presence of NSS in children has been found to be predictive of psychiatric disorders in late adolescence. To date, only little is known about potential neurodevelopmental alterations that may underlay the presence of NSS. The prevalence of NSS has been shown to decrease during adolescence as part of continued neural development and brain re-wiring processes. Therefore, adolescence has been proposed as an important phase for the manifestation or outgrowing of NSS. The underlying mechanisms that may underly this process, however, are largely unknown. As NSS are subtle signs and commonly identified by subjective observer-based neurological examinations, quantitative tools may help to objectively investigate functional and structural correlates associated with NSS. For the work included in this dissertation, healthy adolescent athletes from three European countries were investigated. All participants underwent a neurological examination, resulting in a categorization of participants into groups with and without NSS (NSS+/NSS-). A total NSS score was calculated to provide a continuous measure spanning the whole spectrum of NSS. Two quantitative tools were used to investigate functional and structural correlates of NSS in healthy adolescents: Study I) Instrumented force plate measures to investigate postural control (Bonke et al., 2023), and Study II) Structural magnetic resonance imaging to investigate brain morphology and white matter microstructure (Bonke et al., 2022). Study I aimed to investigate the incremental value of instrumented force plate measures in addition to observer-based neurological examinations. Such associations have not been assessed before but are important for capturing subtle alterations in postural control. This will help to acquire a more comprehensive assessment of motor development. We found no statistically significant differences in postural control between NSS+ and NSS- group. However, participants performing non-optimal in the diadochokinesis sub-test measuring pronation/supination of forearms showed significantly reduced postural control in the medial-lateral (ML) direction. Moreover, the total NSS score correlated significantly with postural control performance in the ML direction. Findings from this study reveal that adolescents with NSS, and in particular adolescents that perform non-optimal in pronation/supination movements of the forearms also perform worse in ML postural control assessed by force plate assessments. As pronation/supination movements of forearms and ML postural control continue to mature until adolescence, it can be assumed that these functions are related and may indicate altered motor development. Study II aimed to identify and characterize NSS-related brain structure alterations using structural magnetic resonance imaging. NSS-related brain structure alterations have not yet been investigated in healthy adolescents. However, this investigation is of high relevance to better understand potential alterations in adolescent brain-rewiring processes related to NSS. Using T1-weighted imaging, we found significantly higher gyrification in the left superior frontal and parietal lobe in the group of adolescents with NSS, likely reflecting alterations in synaptic pruning. We did not find differences in cortical volume or thickness. Using diffusion tensor imaging, we found lower tissue fractional anisotropy (FAt) and higher tissue radial diffusivity (RDt) in widespread white matter clusters in the group of adolescents with NSS, likely indicating alterations in myelination. Findings from this study reveal that NSS in healthy adolescents are associated with brain structure alterations that can be objectively quantified using magnetic resonance imaging. As of now, the relevance of NSS-related brain structure alterations in otherwise healthy adolescents is not fully understood. Future studies should assess whether these alterations may explain the described association between NSS and psychiatric disorders. In summary, the work presented in this doctoral dissertation uses two different quantitative measures to objectively investigate functional and structural differences between adolescents with and without NSS. Insights derived from this work show the beneficial use of instrumented tools to complement neurological examinations for a better understanding of functional and structural correlates of NSS. This work will help to generate a more complete picture of NSS-related developmental alterations and potentially related psychiatric vulnerabilities. Future research should make use of larger and more representative datasets to replicate, as well as extend our findings. Specific attention should be drawn on the investigation of factors that contribute to the development of NSS, longitudinal studies that allow to capture NSS-related alterations in developmental trajectories, as well as on investigating the underlying neural mechanisms of NSS

Robot-Aided Systems for Improving the Assessment of Upper Limb Spasticity: A Systematic Review

This article belongs to the Special Issue Sensors Technology for Medical Robotics.Spasticity is a motor disorder that causes stiffness or tightness of the muscles and can interfere with normal movement, speech, and gait. Traditionally, the spasticity assessment is carried out by clinicians using standardized procedures for objective evaluation. However, these procedures are manually performed and, thereby, they could be influenced by the clinician’s subjectivity or expertise. The automation of such traditional methods for spasticity evaluation is an interesting and emerging field in neurorehabilitation. One of the most promising approaches is the use of robot-aided systems. In this paper, a systematic review of systems focused on the assessment of upper limb (UL) spasticity using robotic technology is presented. A systematic search and review of related articles in the literature were conducted. The chosen works were analyzed according to the morphology of devices, the data acquisition systems, the outcome generation method, and the focus of intervention (assessment and/or training). Finally, a series of guidelines and challenges that must be considered when designing and implementing fully-automated robot-aided systems for the assessment of UL spasticity are summarized

Wearable fusion system for assessment of motor function in lesion-symptom mapping studies

Lesion-symptom mapping studies are a critical component of addressing the relationship between brain and behaviour. Recent developments have yielded significant improvements in the imaging and detection of lesion profiles, but the quantification of motor outcomes is still largely performed by subjective and low-resolution standard clinical rating scales. This mismatch means than lesion-symptom mapping studies are limited in scope by scores which lack the necessary accuracy to fully quantify the subcomponents of motor function. The first study conducted aimed to develop a new automated system of motor function which addressed the limitations inherent in the clinical rating scales. A wearable fusion system was designed that included the attachment of inertial sensors to record the kinematics of upper extremity. This was combined with the novel application of mechanomyographic sensors in this field, to enable the quantification of hand/wrist function. Novel outputs were developed for this system which aimed to combine the validity of the clinical rating scales with the high accuracy of measurements possible with a wearable sensor system. This was achieved by the development of a sophisticated classification model which was trained on series of kinematic and myographic measures to classify the clinical rating scale. These classified scores were combined with a series of fine-grained clinical features derived from higher-order sensor metrics. The developed automated system graded the upper-extremity tasks of the Fugl-Meyer Assessment with a mean accuracy of 75\% for gross motor tasks and 66\% for the wrist/hand tasks. This accuracy increased to 85\% and 74\% when distinguishing between healthy and impaired function for each of these tasks. Several clinical features were computed to describe the subcomponents of upper extremity motor function. This fine-grained clinical feature set offers a novel means to complement the low resolution but well-validated standardised clinical rating scales. A second study was performed to utilise the fine-grained clinical feature set calculated in the previous study in a large-scale region-of-interest lesion-symptom mapping study. Statistically significant regions of motor dysfunction were found in the corticospinal tract and the internal capsule, which are consistent with other motor-based lesion-symptom mapping studies. In addition, the cortico-ponto-cerebellar tract was found to be statistically significant when testing with a clinical feature of hand/wrist motor function. This is a novel finding, potentially due to prior studies being limited to quantifying this subcomponent of motor function using standard clinical rating scales. These results indicate the validity and potential of the clinical feature set to provide a more detailed picture of motor dysfunction in lesion-symptom mapping studies.Open Acces

Enhancing the measurement of clinical outcomes using Microsoft Kinect

There is a growing body of applications leveraging Microsoft Kinect and the associated Windows Software Development Kit in health and wellness. In particular, this platform has been valuable in developing interactive solutions for rehabilitation including creating more engaging exercise regimens and ensuring that exercises are performed correctly for optimal outcomes. Clinical trials rely upon robust and validated methodologies to measure health status and to detect treatment-related changes over time to enable the efficacy and safety of new drug treatments to be assessed and measured. In many therapeutic areas, traditional outcome measures rely on subjective investigator and patient ratings. Subjective ratings are not always sensitive to detecting small improvements, are subject to inter- and intra-rater variability and limited in their ability to record detailed or subtle aspects of movement and mobility. For these reasons, objective measurements may provide greater sensitivity to detect treatment-related changes where they exist. In this review paper, we explore the use of the Kinect platform to develop low-cost approaches to objectively measure aspects of movement. We consider published applications that measure aspects of gait and balance, upper extremity movement, chest wall motion and facial analysis. In each case, we explore the utility of the approach for clinical trials, and the precision and accuracy of estimates derived from the Kinect output. We conclude that the use of games platforms such as Microsoft Kinect to measure clinical outcomes offer a versatile, easy to use and low-cost approach that may add significant value and utility to clinical drug development, in particular in replacing conventional subjective measures and providing richer information about movement than previously possible in large scale clinical trials, especially in the measurement of gross spatial movements. Regulatory acceptance of clinical outcomes collected in this way will be subject to comprehensive assessment of validity and clinical relevance, and this will require good quality peer-reviewed publications of scientific evidence

Fixtureless automated incremental sheet metal forming

Die-based forming is a technology used by many industries to form metal panels. However, this method of forming lacks flexibility and cost effectiveness. In such cases, manual panel beating is typically undertaken for incremental forming of metal panels. Manual panel forming is a highly skilled operation with very little documentation and is disappearing due to non-observance and a lack of interest. Confederation of British Metal forming (CBM) and Institution of Sheet Metal Engineering (ISME) have realised the need for capturing and understanding manual skills used by panel beaters to preserve the knowledge. At the same time, industries seek for alternative panel forming solutions to produce high quality and cost-effective parts at low volume and reduce the repetitive, yet adaptive parts of the panel forming process to free up skilled workers to concentrate on the forming activities that are more difficult to automate. Incremental forming technologies, currently in practice, lack adaptability as they require substantial fixtures and dedicated tools. In this research a new proof-of-concept fixtureless automated sheet metal forming approach was developed on the basis of human skills captured from panel beaters. The proposed novel approach, named Mechatroforming®, consists of integrated mechanisms to form simple sheet metal parts by manipulating the workpiece using a robotic arm under a repetitive hammering tool. Predictive motion planning based on FEA was analysed and the manual forming skills were captured using a motion capture system. This facilitated the coordinated hammering and motion of the part to produce the intended shape accurately. A 3D measurement system with a vertical resolution of 50μm was also deployed to monitor the formation of the parts and make corrections to the forming path if needed. Therefore, the developed mechatronic system is highly adjustable by robotic motion and was closed loop via the 3D measurement system. The developed automated system has been tested rigorously, initially for bowl shape parts to prove the principle. The developed system which is 98% repeatable for depth and diameter, is able to produce targeted bowl shape parts with ±1% dimensional accuracy, high surface quality, and uniform material thickness of 0.95mm when tested with aluminium. It is envisaged that by further research, the proposed approach can be extended to form irregular and more complicated shapes that are highly in demand in various industries

Opportunities for improving animal welfare in rodent models of epilepsy and seizures

Animal models of epilepsy and seizures, mostly involving mice and rats, are used to understand the pathophysiology of the different forms of epilepsy and their comorbidities, to identify biomarkers, and to discover new antiepileptic drugs and treatments for comorbidities. Such models represent an important area for application of the 3Rs (replacement, reduction and refinement of animal use). This report provides background information and recommendations aimed at minimising pain, suffering and distress in rodent models of epilepsy and seizures in order to improve animal welfare and optimise the quality of studies in this area. The report includes practical guidance on principles of choosing a model, induction procedures, in vivo recordings, perioperative care, welfare assessment, humane endpoints, social housing, environmental enrichment, reporting of studies and data sharing. In addition, some model-specific welfare considerations are discussed, and data gaps and areas for further research are identified. The guidance is based upon a systematic review of the scientific literature, survey of the international epilepsy research community, consultation with veterinarians and animal care and welfare officers, and the expert opinion and practical experience of the members of a Working Group convened by the United Kingdom's National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs)

A randomized controlled trial on the effects induced by robot-assisted and usual-care rehabilitation on upper limb muscle synergies in post-stroke subjects

Muscle synergies are hypothesized to reflect connections among motoneurons in the spinal cord activated by central commands and sensory feedback. Robotic rehabilitation of upper limb in post-stroke subjects has shown promising results in terms of improvement of arm function and motor control achieved by reassembling muscle synergies into a set more similar to that of healthy people. However, in stroke survivors the potentially neurophysiological changes induced by robot-mediated learning versus usual care have not yet been investigated. We quantified upper limb motor deficits and the changes induced by rehabilitation in 32 post-stroke subjects through the movement analysis of two virtual untrained tasks of object placing and pronation. The sample analyzed in this study is part of a larger bi-center study and included all subjects who underwent kinematic analysis and were randomized into robot and usual care groups. Post-stroke subjects who followed robotic rehabilitation showed larger improvements in axial-to-proximal muscle synergies with respect to those who underwent usual care. This was associated to a significant improvement of the proximal kinematics. Both treatments had negative effects in muscle synergies controlling the distal district. This study supports the definition of new rehabilitative treatments for improving the neurophysiological recovery after stroke

The use of mechanical redundancy for fault detection in non-stationary machinery

The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.Master's These