Precise Movements Research Articles

Peripheral cranio-spinal nerve communication for trapezius muscle control using axonal profiling through immunostaining

Accessory nerve (CNXI) has been known to be the primary conduit for motor control of the trapezius, while the supplementary cervical nerves (C3 and C4) are responsible for processing sensory information from muscle. However, the lack of substantial direct evidence has led to these conclusions being regarded as mere speculation. This study used immunostaining (using antibodies against neurofilament 200 for all axons, choline acetyltransferase for cholinergic axons, tyrosine hydroxylase for sympathetic axons, and alpha 3 sodium potassium ATPase for proprioceptive afferent axons) of human samples to verify the functional contributions of nerves. Study highlights the pivotal role of C3 and C4 in regulating precise movements of trapezius, contributing to motor control, proprioceptive feedback, and sympathetic modulation. CNXI is composed primarily of somatic efferent fibers, with significant numbers of sympathetic or sensory fibers. Furthermore, C3-4 have both cholinergic and non-cholinergic axons, suggesting their involvement in proprioceptive feedback and somatic efferent functions. Although less common, mechanosensors such as nociceptive sensor and sympathetic fibers are also supplied by these cervical nerves. The study demonstrated that these nerves contain motor fibers and significant proprioceptive and sympathetic axons, challenging the long-held notion that CNXI are motor and upper spinal nerves are sensory.

Grasp with push policy for multi-finger dexterity hand based on deep reinforcement learning

When interacting with the external environment, dexterous hands face various challenges, including interference in cluttered environments and difficulty in accurately locating target objects. We observe that the human hand is often at ease in the face of complex unstructured environments: pushing objects that can rearrange clutter, locating target objects, and creating space for fingers. In addition, the gripping action complements the push by achieving the precise movement of unrelated objects. Taking inspiration from this, to enable manipulators to perform accurate grasping tasks in complex environments, we propose a new data-driven grasping approach for robotic dexterous hands: the push-fit grasping approach. This method combines human grasping with model-free deep reinforcement learning to realize the robot's collaborative grasping ability. An end-to-end conditional converter grasping network is first trained, which takes the visual point cloud input to the action output. We use DQN algorithms for strategy training, further enhanced by fine-tuning methods for real-world learning. The experimental results show that the push strategy we learned significantly improves the grasping performance, and the success rate of cooperative grasping is increased by 8 %. It is worth noting that this fine-tuning method significantly reduces the actual training time, with the real world training taking up only one-fifth of the time in the simulated world. Even in demanding scenarios characterized by confusion and complexity, it facilitates rapid learning. This study provides new insights for effectively addressing complex challenges involving multi-fingered dexterous hands and human-computer interaction. Our code is available in the github repository.

High-resolution motion compensation for brain PET imaging using real-time electromagnetic motion tracking.

Substantial improvements in spatial resolution in brain positron emission tomography (PET) scanners have greatly reduced partial volume effect, making head movement the main source of image blur. To achieve high-resolution PET neuroimaging, precise real-time estimation of both head position and orientation is essential for accurate motion compensation. A high-resolution electromagnetic motion tracking (EMMT) system with an event-by-event motion correction is developed for PET-CTscanners. EMMT is comprised of a source, an array of sensors, and a readout electronic unit (REU). The source acts as a transmitter and emits an EM dipole field. It is placed in close proximity to the sensor array and detects changes in EM flux density due to sensor movement. The REU digitizes signals from each sensor and captures precise rotational and translational movements in real time. Tracked motion in the EMMT coordinate system is synchronized with the PET list-mode data and transformed into the scanner coordinate system by locating paired positions in both systems. The optimal rigid motion is estimated using singular value decomposition. The rigid motion and depth-of-interaction (DOI) parallax effect are corrected by event-by-event rebinning of mispositioned lines-of-response (LORs). We integrated the EMMT with our recently developed ultra-high resolution Prism-PET prototype brain scanner and a commercial Siemens Biograph mCT PET-CT scanner. We assessed the imaging performance of the Prism-PET/EMMT system using multi-frame motion of point sources and phantoms. The mCT/EMMT system was validated using a set of point sources attached to both a mannequin head and a human volunteer, for simulating multiframe and continuous motions, respectively. Additionally, a human subject for [18F]MK6240 PET imaging wasincluded. The tracking accuracy of the Prism-PET/EMMT system was quantified as a root-mean-square (RMS) error of 0.49 for 100 axial rotations, and an RMS error of 0.15 mm for 100 mm translations.The percent difference (%diff) in average full width at half maximum (FWHM) of point source between motion-corrected and static images, within a motion range of and 10 mm from the center of the scanner's field-of-view (FOV), was 3.9%. The measured recovery coefficients of the 2.5-mm diameter sphere in the activity-filled partial volume correction phantom were 23.9%, 70.8%, and 74.0% for the phantom with multi-frame motion, with motion and motion compensation, and without motion, respectively. In the mCT/EMMT system, the %diff in average FWHM of point sources between motion-corrected and static images, within a motion range of and 10 mm from the center of the FOV, was 14%. Applying motion correction to the [18F]MK6240 PET imaging reduced the motion-induced spill-in artifact in the lateral ventricle region, lowering its standardized uptake value ratio (SUVR) from 0.70 to 0.34. The proposed EMMT system is a cost-effective, high frame-rate, and none-line-of-sight alternative to infrared camera-based tracking systems and is capable of achieving high rotational and translational tracking accuracies for mitigating motion-induced blur in high-resolution brain dedicated PETscanners.

Enhanced transanal surgery training through a 4K 3D surgical exoscope: a novel approach for transanal surgery.

Recently, exoscope was introduced as a more ergonomic alternative to microscope, mainly in nerve and spinal surgery. Exoscope use in general surgery is still experimental and just few reports are present in literature. Here, we describe for the first time its application in transanal surgery, specifically during the transanal transection and single-stapled anastomosis in ileal-pouch anal anastomosis. After completing the proctectomy and pouch formation laparoscopically, two surgeons performed the transanal transection and single-stapled anastomosis using the vision provided by the ORBEYE™ exoscope system with a 3D 4K orbital camera and a 55-inches 3D screen. The transanal procedure was carried out with the surgeons looking at the 3D screen rather than at the operating field. The system subjectively provided excellent operative view thanks to the magnification capacity and the high resolution. The ergonomics was improved compared to classical transanal surgery, allowing the operators and observers to have the same view in a comfortable position. In particular, the exoscope magnified vision allowed for clearer demonstration of techniques to trainees. This is the first report on the intraoperative application of the ORBEYE™ surgical exoscope in transanal surgery. The magnified vision allowed precise movements and the system appeared potentially a ground-breaking tool for surgical training. The ability to project high-quality images to observers make it ideal for teaching complex transanal procedures. Further studies are encouraged to validate this approach into standard colorectal practice.

A two-layer economic resilience model for distribution network restoration after natural disasters

Improving the resilience of energy networks and minimizing outages is crucial, making the development of self-healing strategies essential for ensuring a continuous power supply and boosting resilience. As decentralized prosumers become more integrated into smart grids, innovative coordination methods are required to fully leverage their potential and improve the system's self-healing capabilities. Hence, in this paper, we present a decentralized two-layer model for active distribution networks (ADNs) incorporating commercial energy hubs, Parking lots (PLs), hydrogen refueling stations, and mobile units (MUs). This model aims to maximize the flexible capacities of flexible prosumers under emergencies and includes a dynamic mechanism for transporting hydrogen to refueling stations via trucks. In the first layer of the model, the AND operator provides the required services to flexible prosumers, including commercial energy hubs, PLs and hydrogen refueling stations. During this layer, the movement paths of mobile units, such as battery-based mobile storage units (MSUs) and mobile hydrogen units (MHUs), are determined. In the second layer, prosumers independently plan and decide the extent of their service contributions. Subsequently, with the actual service capacities established, the AND operator re-optimizes the initial planning to finalize the system schedule and precise movement paths of the mobile units. The proposed model was tested on a modified 83-bus distribution network using the CPLEX solver in GAMS. Simulation results demonstrate a 54.9 % reduction in forced load shedding (FLS) due to the dispatch of mobile units and a further 84.4 %% reduction in FLS from leveraging the flexible capacities of commercial energy hubs and PLs.

Structuring of electrorheological fluids in polymer matrices for miniature actuators

Miniature actuators are utilized in various application fields, from robotics to medical devices, where compact dimensions, precise movements, and cost-effectiveness are crucial factors. Particularly for applications like braille displays, there is a critical demand for lightweight, portable, and affordable actuators to integrate into daily life for visually impaired people. However, existing actuation technologies such as electroactive polymers, electrorheological materials, and piezoelectric elements often do not meet the specific requirements of miniature actuators, especially for braille displays. Therefore, this study investigates the behavior of electrorheological fluids incorporated into polymer matrices of cellulose and proteins for miniature actuators to overcome the primary challenge of sedimentation through the structuring of the liquid. The gel formulations are tested in three distinct setups: the V-shaped, horizontal plates, and valve system. These experiments demonstrated immediate structural changes in the gel formulations, achieving reversible movement. Furthermore, the valve setup even enabled the analysis of the strength of the hardened mixtures by the resistance against applied air pressure. The results demonstrate that incorporating electrorheological fluids into polymer matrices is not only feasible but also preserves the characteristic behavior of electrorheological fluids under electrical field exposure. This behavior validates the applicability and suitability of modified electrorheological fluid mixtures in miniature actuators.

Tactile stimulation designs adapted to clinical settings result in reliable fMRI-based somatosensory digit maps

Movement constraints in stroke survivors are often accompanied by additional impairments in related somatosensory perception. A complex interplay between the primary somatosensory and motor cortices is essential for adequate and precise movements. This necessitates investigating the role of the primary somatosensory cortex in movement deficits of stroke survivors. The first step towards this goal could be a fast and reliable functional Magnetic Resonance Imaging (fMRI)-based mapping of the somatosensory cortex applicable for clinical settings. Here, we compare two 3 T fMRI-based somatosensory digit mapping techniques adapted for clinical usage in seven neurotypical volunteers and two sessions, to assess their validity and retest-reliability. Both, the traveling wave and the blocked design approach resulted in complete digit maps in both sessions of all participants, showing the expected layout. Similarly, no evidence for differences in the volume of activation, nor the activation overlap between neighboring activations could be detected, indicating the general feasibility of the clinical adaptation and their validity. Retest-reliability, indicated by the Dice coefficient, exhibited reasonable values for the spatial correspondence of single digit activations across sessions, but low values for the spatial correspondence of the area of overlap between neighboring digits across sessions. Parameters describing the location of the single digit activations exhibited very high correlations across sessions, while activation volume and overlap only exhibited medium to low correlations. The feasibility and high retest-reliabilities for the parameters describing the location of the single digit activations are promising concerning the implementation into a clinical context to supplement diagnosis and treatment stratification in upper limb stroke patients.

Design of an Optimal Multivariable PID Controller for a Two-Link Robot Arm

Incorporating manipulator robots into various industries has revolutionized automation and manufacturing processes. Manipulator robots are versatile machines equipped with robotic arms and end-effectors, enabling them to handle complex tasks with precision and efficiency. This research aims to design an optimal Mutivariable PID (MPID) controller that ensures precise and accurate movements of two-link robot arm. Theoretical foundations of the MPID controller are discussed together with its relevance to robotic arm systems, and the challenges associated with its implementation. The research methodology involves mathematical modelling of the two-link robot arm dynamics, and the use of an optimization algorithm to determine the optimal MPID controller coefficients. Simulation results demonstrate performance enhancement and productivity of the two-link robot arm through the improved MPID controller.

Enhancing Youth Cricket Performance: Insights From Field-Based Assessments of Strength, Endurance, and Agility

Background The physical demands of cricket, particularly in youth players, encompass critical components of strength, endurance, and agility, which are essential for optimal performance and maintaining competitive success. Strength, endurance, and agility are vital in enhancing youth cricketers' overall physical fitness and performance levels, directly influencing their ability to sustain high-intensity efforts, execute precise movements, and recover effectively during matches and training sessions. Aims: This research aimed to evaluate the field-based performance levels of young cricketers in Belagavi through innovative assessments: the wall squat, 2km time trial, and Run-a-three tests, highlighting their importance in enhancing player fitness and performance.Methods: A cohort of 100 young cricketers (aged 18-24) with a minimum of 2 years experience underwent comprehensive assessments using the wall squat, 2km time trial, and Run-a-three tests across various cricket grounds in Belagavi. Statistical analyses provided insights into their fitness levels across different player categories (batsmen, bowlers, all-rounders, and wicketkeepers).Results: Significant variations in fitness levels were observed among player categories, with wall squat endurance being the most notable area for improvement, as the mean performance was 51.54 ± 20.79 seconds. The average 2km trial was completed in 10.03 ± 1.42 minutes, while the Run-a-three drill averaged 11.86 ± 1.33 seconds. These findings highlight the critical need for targeted fitness interventions to enhance lower body endurance across all roles.Conclusion: This study underscores the imperative for tailored fitness regimens to address deficiencies in strength, endurance, and agility among young cricketers in Belagavi. These targeted interventions can enhance their competitive readiness and support long-term athletic development. Future research should explore the specific impact of these fitness interventions on performance metrics and injury prevention, providing further insights into optimizing youth cricket training programs.

Minimizing Defects in Additive Manufacturing and Laser Welding Through Energy Coupling Experiments and Dynamic Modelling

Additive manufacturing is a revolutionary technology that produces complex components as a single piece, replacing traditional assemblies and reducing waste. Laser powder bed fusion, a type of additive manufacturing, allows for limitless design freedom by building intricate parts layer-by-layer through melting and fusing metal powder. However, build quality remains inconsistent, with deformations like pores and spattering occurring. To improve modelling of the behaviour of melted metal, thus minimizing defects, an experiment which determined the metal’s absorptance of laser energy through integrating sphere radiometry was conducted. The integrating sphere, which spatially integrated a fraction of measured light to calculate full radiance, had to sit above the build plate and not interfere with powder spreading. I designed two parts which attached the integrating sphere to the motorized powder spreading blade. Utilizing small ridges in the enclosure as weight-bearing tracks, the blade’s torque was reduced while allowing precise movement of the sphere. Through implementing these parts, the experiment was conducted, whose results will aid in our understanding of laser-metal interactions. Defects like spattering also occur during laser welding, due to the vaporization of unstable liquid metal. To combat this, novel beam shapes have been seen to increase the stability of the keyhole. To model this effect, I created a phenomenological, dynamic model of the keyhole depth during a copper weld. Two differential equations were created to model the keyhole depth’s rate of change using a dual mode and single mode laser, depending on absorptance and incident laser intensity. The dynamic depth of the keyhole for both modes was numerical solved in Python and iterated using existing copper weld data. Through better quantitative understanding of energy coupling and numerical modelling of the resulting dynamics, defects in laser welding and additive manufacturing can be minimized.

Design, realization, and operative tests of a fine steering tip/tilt mechanism for space telescopes

Positioning mechanisms are critical components in advanced optical systems, such as Earth observation telescopes. They are used to adjust the position of one or more optical elements to account for various factors, including thermal effects, settling due to launch or environmental loads, thermo-elastic deformations, or the need to compensate for spacecraft microvibrations or jitter.In this context, the paper presents the design, implementation, and testing of a tip/tilt positioning mechanism. The paper describes in detail the various components of the mechanism, which is driven by four multilayer piezoelectric actuators, each preloaded by a compliant mechanical amplifier. It then presents the finite element model that simulates the mechanical behavior of the mechanism, and the series of tests carried out on the prototype. The primary objective of this mechanism is to enable and control the precise movement of an optical payload in three degrees of freedom: a translation along its optical axis and two rotations about axes located on its optical surface.

Novel murine closed-loop auditory stimulation paradigm elicits macrostructural sleep benefits in neurodegeneration.

Boosting slow-wave activity (SWA) by modulating slow waves through closed-loop auditory stimulation (CLAS) might provide a powerful non-pharmacological tool to investigate the link between sleep and neurodegeneration. Here, we established mouse CLAS (mCLAS)-mediated SWA enhancement and explored its effects on sleep deficits in neurodegeneration, by targeting the up-phase of slow waves in mouse models of Alzheimer's disease (AD, Tg2576) and Parkinson's disease (PD, M83). We found that tracking a 2 Hz component of slow waves leads to highest precision of non-rapid eye movement (NREM) sleep detection in mice, and that its combination with a 30° up-phase target produces a significant 15-30% SWA increase from baseline in wild-type (WTAD)and transgenic (TGAD) mice versus a mock stimulation group. Conversely, combining 2 Hz with a 40° phase target yields a significant increase ranging 30-35% in WTPD and TGPD mice. Interestingly, these phase-target-triggered SWA increases are not genotype dependent but strain specific. Sleep alterations that may contribute to disease progression and burden were described in AD and PD lines. Notably, pathological sleep traits were rescued by mCLAS, which elicited a 14% decrease of pathologically heightened NREM sleep fragmentation in TGAD mice, accompanied by a steep decrease in microarousal events during both light and dark periods. Overall, our results indicate that model-tailored phase targeting is key to modulate SWA through mCLAS, prompting the acute alleviation of key neurodegeneration-associated sleep phenotypes and potentiating sleep regulation and consolidation. Further experiments assessing the long-term effect of mCLAS in neurodegeneration may majorly impact the establishment of sleep-based therapies.

Interactive Control of a Robotic Arm using Voice Recognition

This research focuses on interactive control of a robotic arm using voice recognition, providing a user-friendly approach to controlling robotic systems through voice commands. The system is built on Arduino, integrating key components such as servo motors for precise movements, Bluetooth for wireless communication and motor drivers for higher torque applications. The HC-05 Bluetooth module supports voice recognition, enabling external devices to control the robotic arm through voice commands. This setup allows for quick responses and minimal human intervention. The proposed robotic arm supports actions such as pick and place, moving forward, backward, right, and left.

Research on the difference in plantar biomechanics among dance majors

Dance majors’ plantar biomechanics studies the functional and structural dynamics of their feet as they perform different dance moves and techniques. The primary objective is to comprehend which distinct dancing styles and approaches affect plantar biomechanics to possibly identify risk factors for injuries and guide dancers on how to prevent them. Dancing requires precise body alignment and movement, which leads to certain foot biomechanical variations that are vital for preventing injuries and improving performance. Distinct plantar biomechanics within dance majors (ballet and jazz) are examined to identify novel biomechanical factors. One hundred and fifty all fifty jazz dancers, fifty ballet dancers, and fifty non-dancers participated in the study. A 3D foot scanner and pressure measuring system are utilized for assessing variables such as arch elevation (AE), plantar pressure dispersion (PPD), and foot position (FP). Additionally, tests of gait ability using distinct foot biomechanics are carried out in various dance-related motions. For comparative assessment of such dancer groups, statistical techniques like Anova and Kruskal-wallis tests are used. Types of dance show different PPD formations, with jazz dancers including maximum midfoot pressure (MFP) and ballet dancers including maximum forefoot pressure (FFP), and both dancer groups have stronger ankle flexibility and toe flexion. Future research needs to assess the consequences of training plans and long-term modifications to gain an improved comprehension of how the biomechanically unique feet of dance majors necessitate targeted interventions for injury prevention and performance improvement.

Research on Artificial Intelligence Technology in Accurate Recognition of Sports Training Actions

In sports training, accurate identification of athletes' movements is helpful to judge whether athletes' actions are standard or not, thus providing precise movement data for training and improving athletes' levels. The convolutional neural network VGG model was constructed based on artificial intelligence technology to extract image features and accurately recognize actions automatically. Weizmann data set was used to train and verify the model. The results of this study showed that the motion recognition algorithm based on the convolutional neural network could achieve high recognition accuracy.

The impact of Playdough games on the development of oral motor skills in preschool children with childhood apraxia of speech

The relevant challenges are the use of innovative approaches that conserve both the speech therapist’s and the child’s resources while addressing multiple goals in speech therapy. The authors of this article have adopted such an approach to develop oral motor skills, which are crucial for speech development in preschoolers, particularly those with childhood apraxia of speech. This study aimed to evaluate the effectiveness of an author-developed therapy using Playdough games for preschool children with childhood apraxia of speech. A controlled design with repeated measures was employed. The primary diagnosis of CAS was established based on clinical assessment. A comparative evaluation of two groups (control and experimental) was conducted using a developed methodology for assessing the level of manual and oral motor skills in preschool children before and after the author-developed therapy using Playdough games. Researchers discovered that the systematic use of their author-developed Playdough games positively impacted the motor skills of children with CAS. Children in the experimental group, who participated in Playdough therapy, demonstrated significant improvements in both manual and oral motor skills, increased precision and focus in movement execution, and enhanced accuracy and speed of articulatory movements. There was a reduction in delays and incorrect movement sequences during finger movement tasks. Children required less additional time and significantly less assistance from the speech therapist, indicating a positive impact of using Playdough in therapy. The following skills improved: transitions between articulatory positions, which helped children avoid coarticulation difficulties; planning of movement sequences; and smooth transitions between sounds and syllables. The practical significance of this study lies in the effectiveness of using Playdough games for significantly improving oral motor skills, movement precision, and concentration in children with childhood apraxia of speech, thereby reducing the need for additional speech therapy support

Lateralization of Feeding Behaviour in White-Fronted Lemur (Eulemur albifrons) and Ring-Tailed Lemur (Lemur catta) in Captivity

Introduction: Functional cerebral asymmetry is reflected in the lateralization of some behavioural patterns in many vertebrate species. In primates, behavioural lateralization has been related to both life style and age and sex, and it affects behaviours such as feeding and other tasks that require precision movements. Methods: We have studied feeding lateralization concerning the use of right and left hand to take the food in two species of lemurs in captivity, the mainly arboreal white-fronted lemur and the more terrestrial ring-tailed lemur, taking also account the age and the sex of the individuals. We calculated for each individual the hand preference (if it was the case) by means of z scores, and the strength of such preference using the handedness index (HI). Finally, we determined for each species the existence of right/left bias at the group level with the t Student test. Results: Half of the white-fronted lemurs (7 of 14) showed lateralization in feeding, while only a few ring-tailed lemurs (3 of 19) showed it. In the first species, a light bias seems to emerge (5 individuals used mostly the right hand for taking the food, while only 2 used mainly the left hand), while in the second species no bias could really be appreciated. Conclusion: Feeding lateralization was more accentuated in white-fronted lemur, in which a light bias towards the use of the right hand seems to be evidenced. No clear effect of age and sex on the presence and direction of lateralization could be evidenced. The results somehow contrast with what the postural theory of lateralization postulates about the preferential use of the right hand in terrestrial species.

Biofeedback and Exercise Load Affect Accuracy of Tongue Strength Exercise Performance.

Rehabilitative exercises require precise movement coordination and target accuracy for optimal effectiveness. This paper explores the impact of tongue strength exercises (TSE) performance accuracy on exercise outcomes, adherence, and participant confidence and motivation. An 8-week randomized clinical trial included 84 typically aging participants divided into four groups defined by access to biofeedback (present/absent) and TSE intensity dosing (maximal/submaximal) during a home exercise program (HEP). Retention, training, and HEP accuracy were tracked at biweekly visits and during HEP for participants with access to a biofeedback device. Associations with tongue strength outcomes, participant factors, biofeedback, and intensity dosing were analyzed. Exercise accuracy measures did not contribute to tongue strength outcomes at the end of 8weeks. Increased training accuracy (less practice required to achieve competency) was associated with higher participant confidence and better adherence to the HEP. The presence of biofeedback was associated with reduced adherence but better retention accuracy, while maximal intensity was associated with improvements in all accuracy measures compared to submaximal intensity exercise. These findings in typically aging participants suggest the need for tailored approaches in swallowing-related exercise programs, given the effects of biofeedback and exercise intensity on motor learning and exercise retention. Accuracy performance and its effect on clinical outcomes warrants study in clinical populations with dysphagia and with various rehabilitative approaches.Trial Registration Clincialtrials.gov: NCT04809558.

Simulation of the behavior of fine and gross motor skills of an individual with motor disabilities

We have developed a neural network model that imitates the central nervous system’s control of motor sensors (Sánchez-Torres and Rodríguez-Romo in Neurocomputing 581:127511, 2024). Our research explored various levels of connectivity in our neural network related to neuroplasticity in the central nervous system. We have conducted a study comparing healthy individuals to those with motor impairments by utilizing reinforcement learning and transfer entropy. In our previous research (Sánchez-Torres and Rodríguez-Romo in Neurocomputing 581:127511, 2024), we have simulated human walking while encountering obstacles as an instance of gross motor activities. Now, we have used the same model to simulate fine motor activities. Our goal is to identify differences in information transmission between gross and fine motor activities among healthy individuals and those with motor impairments by evaluating the effective connectivity of our network. To regulate learning accuracy in our model, we introduced a variable called numClusterToFire. However, we discovered that the value for this variable requires careful calibration. If the value is too small, agent exploration is insufficient, and network learning is inefficient. Conversely, learning times increase exponentially, often unnecessarily if the value is too large. We conducted simulations for gross and fine motor skills using three different numClusterToFire values and found that as we increased numClusterToFire, the time required for the network to memorize the outputs for each of the objects in the test set also increased. Our findings indicate that in gross motor skills, which do not require precision, changes in the numClusterToFire variable do not affect information transfer behavior. Conversely, in fine motor skills, information transfer decreases as numClusterToFire increases. On the other hand, our model revealed that for healthy and disabled individuals, the transfer of information between the input layer and the first hidden layer is higher for fine motor skills; this important biological fact suggests the influence of external cues in performing this activity successfully. Additionally, our neural network model showed that movements that do not require precision do not necessarily require a high level of neuroplasticity. Increasing neuroplasticity may cause some neurons to transmit more information than others. Whereas, increasing neuroplasticity through practice is essential for precise movements like fine motor skills. We also found that information transfer in the network’s hidden layers is similar for fine and gross motor activities, as we observed identical patterns. However, the distribution and proportion of these patterns differ, concluding that more neurons are involved in fine motor activities, and more information is transferred compared to gross motor activities. Finally, a pattern was observed in the transfer of information in the last hidden layer, which is only present in fine motor skills. This pattern is associated with the precision of the movements.

Precision of trunk movement in people with chronic low back pain

BackgroundMotor control exercise is commonly applied in people with chronic low back pain (CLBP), but possibly not all people with CLBP have motor control impairments. We suggest movement precision as measure to identify motor control impairments. Movement precision has been operationalized as trunk movement variability (TMV) and as trunk tracking error(s) (TTE). Objectives: To compare the known-group validity and the responsiveness of TMV and TTE. DesignWe used a case-control comparison (Healthy controls (n = 30) vs CLBP (n = 60)) to assess the known-group validity. A cohort study, (measurements in week 3 and week 12 of treatment), was used to assess responsiveness. MethodsTMV (temporal (CyclSD) and spatial (MeanSD)) was analyzed during standing, repetitive flexion and rotation tasks (35x). TTE was measured during movement target tracking tasks, again in flexion and rotation. Participants with CLBP followed a multidisciplinary intervention and both measures were assessed in week 3 and week 12 of treatment. 2-way MANOVA and 2-way ANOVA were used to assess the effect of Group (CLBP vs healthy controls) and direction (flexion vs rotation) on TMV and TTE. For responsiveness, 2-way MANOVA and 2-way ANOVA were used to assess the effect of treatment and direction on both measures. FindingsAt baseline, TMV was not different between groups, while TTE was higher in the people with CLBP (p = 0.005, np2 = 0.09). Treatment strongly decreased temporal TMV (p = 0.025, np2 = 0.33) and TTE (p < 0.001, np2 = 0.844). ConclusionsThese results demonstrate that TTE is more sensitive to CLBP and more responsive to treatment than TMV.