MRI of GlycoNOE in the human liver using GraspNOE-Dixon.

PURPOSE: The objective of this study was to develop a new MRI technique for non-invasive, free-breathing imaging of glycogen in the human liver using the nuclear Overhauser effect (NOE). METHODS: The proposed method, called GraspNOE-Dixon, uses a novel MRI sequence that combines steady-state saturation-transfer preparation with multi-echo golden-angle radial stack-of-stars sampling. Multi-echo acquisition enables fat/water-separated imaging for quantification of water-specific NOE. Image reconstruction is performed using the improved golden-angle radial sparse parallel imaging (GRASP-Pro) technique to exploit spatiotemporal correlations in dynamic images. To evaluate the proposed technique, imaging experiments were first performed on glycogen phantoms, followed by in vivo studies involving healthy volunteers and patients with fatty liver disease. In addition, a comparative assessment of signal changes before and after a 12-h fasting period was performed. RESULTS: Evaluation experiments on glycogen phantoms showed a robust linear correlation between the NOE signal and glycogen concentration. In vivo experiments demonstrated motion-robust NOE-weighted images, with potential for further acceleration. In subjects with varying liver fat content, the fat/water separation approach resulted in distortion-free Z-spectra, enabling the quantification of glycogen NOE. An approximately one-third reduction in the NOE signal was observed following a 12-h fasting period, consistent with a decrease in glycogen level. CONCLUSION: This study introduces a clinically feasible imaging technique, GraspNOE-Dixon, for free-breathing volumetric multi-echo imaging of hepatic glycogen at 3 T. The motion robust imaging technique developed here may also have applications in other body areas beyond liver imaging.

Pressure Sensors for Evaluating Hand Grasp and Pinch.

This study addresses the need for highly sensitive tools to evaluate hand strength, particularly grasp and pinch strength, which are vital for diagnosing and rehabilitating conditions affecting hand function. Current devices like the Jamar dynamometer and Martin Vigorimeter, although reliable, fail to measure extremely low force or pressure values required for individuals with severe hand impairments. This research introduces a novel device, a modified Martin Vigorimeter, utilizing an ultra-soft latex chamber and differential pressure measurement to detect minute pressure changes, thus significantly enhancing sensitivity. The device offers a cost-effective solution, making advanced hand strength evaluation more accessible for clinical and research applications. Future research should validate its accuracy across diverse populations and settings, exploring its broader implications for hand rehabilitation and occupational health.

Variations in Clustering of Multielectrode Local Field Potentials in the Motor Cortex of Macaque Monkeys during a Reach-and-Grasp Task.

There is experimental evidence of varying correlation among the elements of the neuromuscular system over the course of the reach-and-grasp task. The aim of this study was to investigate if modifications in correlations and clustering can be detected in the local field potential (LFP) recordings of the motor cortex during the task. To this end, we analyzed the LFP recordings from a previously published study on monkeys that performed a reach-and-grasp task for targets with a vertical or horizontal orientation. LFP signals were recorded from the motor and premotor cortex of macaque monkeys as they performed the task. We found very robust changes in the correlations of the multielectrode LFP recordings that corresponded to task epochs. Mean LFP correlation increased significantly during reach and then decreased during grasp. This pattern was very robust for both left and right arm reaches irrespective of target orientation. A hierarchical cluster analysis also demonstrated similar changes. In focusing on correlations, our study has contributed new insights to the understanding of LFP signals and their relationship to movement. A sliding window computation of the number of clusters was performed to probe the capacities of the LFP clusters for detecting upcoming task events. For a very high percentage of trials (97.89%), there was a downturn in cluster number following the Pellet Drop (GO signal) that reached a minimum preceding the Start of grasp, hence indicating that cluster analyses of LFPs could contribute to signaling an increased probability of the Start of grasp.

DCE-MRI of the liver with sub-second temporal resolution using GRASP-Pro with navi-stack-of-stars sampling.

Respiratory motion-induced image blurring and artifacts can compromise image quality in dynamic contrast-enhanced MRI (DCE-MRI) of the liver. Despite remarkable advances in respiratory motion detection and compensation in past years, these techniques have not yet seen widespread clinical adoption. The accuracy of image-based motion detection can be especially compromised in the presence of contrast enhancement and/or in situations involving deep and/or irregular breathing patterns. This work proposes a framework that combines GRASP-Pro (Golden-angle RAdial Sparse Parallel MRI with imProved performance) MRI with a new radial sampling scheme called navi-stack-of-stars for free-breathing DCE-MRI of the liver without the need for explicit respiratory motion compensation. A prototype 3D golden-angle radial sequence with a navi-stack-of-stars sampling scheme that intermittently acquires a 2D navigator was implemented. Free-breathing DCE-MRI of the liver was conducted in 24 subjects at 3T including 17 volunteers and 7 patients. GRASP-Pro reconstruction was performed with a temporal resolution of 0.34-0.45 s per volume, whereas standard GRASP reconstruction was performed with a temporal resolution of 15 s per volume. Motion compensation was not performed in all image reconstruction tasks. Liver images in different contrast phases from both GRASP and GRASP-Pro reconstructions were visually scored by two experienced abdominal radiologists for comparison. The nonparametric paired two-tailed Wilcoxon signed-rank test was used to compare image quality scores, and the Cohen's kappa coefficient was calculated to evaluate the inter-reader agreement. GRASP-Pro MRI with sub-second temporal resolution consistently received significantly higher image quality scores (P < 0.05) than standard GRASP MRI throughout all contrast enhancement phases and across all assessment categories. There was a substantial inter-reader agreement for all assessment categories (ranging from 0.67 to 0.89). The proposed technique using GRASP-Pro reconstruction with navi-stack-of-stars sampling holds great promise for free-breathing DCE-MRI of the liver without respiratory motion compensation.

Hand preference trajectories as predictors of language outcomes above and beyond SES: Infant patterns explain more variance than toddler patterns at 5 years of age.

Prior studies found hand preference trajectories predict preschool language outcomes. However, this approach has been limited to examining bimanual manipulation in toddlers. It is not known whether hand preference during infancy for acquiring objects (i.e., reach-to-grasp) similarly predicts childhood language ability. The current study explored this motor-language developmental cascade in 90 children. Hand preference for acquiring objects was assessed monthly from 6 to 14 months and language skill was assessed at 5 years. Latent class growth analysis identified three infant hand preference classes: left, early right, and late right. Infant hand preference classes predicted 5-year language skills. Children in the left and early right classes, who were categorized as having a consistent hand preference, had higher expressive and receptive language scores relative to children in the inconsistent late right class. Consistent classes did not differ from each other on language outcomes. Infant hand preference patterns explained more variance for expressive and receptive language relative to previously reported toddler hand preference patterns, above and beyond socioeconomic status (SES). Results suggest that hand preference, measured at different time points across development using a trajectory approach, is reliably linked to later language.

Time-independent relationship between digits closure velocity and hand transport acceleration during reach-to-grasp movements.

Prehension movements in primates have been extensively studied for decades, and hand transport and hand grip adjustment are usually considered as the main components of any object reach-to-grasp action. Evident temporal patterns were found for the velocity of the hand during the transport phase and for the digits kinematics during pre-shaping and enclosing phases. However, such kinematics were always analysed separately in regard to time, and never studied in terms of dependence one from another. Nevertheless, if a reliable one-to-one relationship is proven, it would allow reconstructing the digit velocity (and position) simply by knowing the hand acceleration during reaching motions towards the target object, ceasing the usual dependence seen in literature from time of movement and distance from the target. In this study, the aim was precisely to analyse reach-to-grasp motions to explore if such relationship exists and how it can be formulated. Offline and real-time results not only seem to suggest the existence of a time-independent, one-to-one relationship between hand transport and hand grip adjustment, but also that such relationship is quite resilient to the different intrinsic and extrinsic properties of the target objects such as size, shape and position.

Characteristic brain functional activation and connectivity during actual and imaginary right-handed grasp.

We used 34-channel functional near infrared spectroscopy to investigate and compare changes in oxyhemoglobin concentration of brain networks in bilateral prefrontal cortex, sensorimotor cortex, and occipital lobe of 22 right-handed healthy adults during executive right-handed grasp (motor execution task) and imagined right-handed grasp (motor imagery task). Then calculated lateral index and functional contribution degree, and measured functional connectivity strength between the regions of interest. In the motor executive block task, there was a significant increase in oxyhemoglobin concentration in regions of interest except for right occipital lobe (P<0.05), while in the motor imagery task, all left regions of interest's oxyhemoglobin concentration increased significantly (P<0.05). Except the prefrontal cortex in motor executive task, the left side of the brain was dominant. Left sensorimotor cortex played a major role in these two tasks, followed by right sensorimotor cortex. Among all functional contribution degree, left sensorimotor cortex, right sensorimotor cortex and left occipital lobe ranked top three during these tasks. In continuous acquisition tasks, functional connectivity on during motor imagery task was stronger than that during motor executive task. Brain functions during two tasks of right-hand grasping movement were partially consistent. However, the excitability of brain during motor imagery was lower, and it was more dependent on the participation of left prefrontal cortex, and its synchronous activity of the whole brain was stronger. The trend of functional contribution degree was basically consistent with oxyhemoglobin concentration and lateral index, and can be used as a novel index to evaluate brain function. [ChiCTR2200063792 (2022-09-16)].

Free-breathing time-resolved 4D MRI with improved T1-weighting contrast.

This work proposes MP-Grasp4D (magnetization-prepared golden-angle radial sparse parallel 4D) MRI, a free-breathing, inversion recovery (IR)-prepared, time-resolved 4D MRI technique with improved T1-weighted contrast. MP-Grasp4D MRI acquisition incorporates IR preparation into a radial gradient echo sequence. MP-Grasp4D employs a golden-angle navi-stack-of-stars sampling scheme, where imaging data of rotating radial stacks and navigator stacks (acquired at a consistent rotation angle) are alternately acquired. The navigator stacks are used to estimate a temporal basis for low-rank subspace-constrained reconstruction. This allows for the simultaneous capture of both IR-induced contrast changes and respiratory motion. One temporal frame of the imaging volume in MP-Grasp4D MRI is reconstructed from a single stack and an adjacent navigator stack on average, resulting in a nominal temporal resolution of 0.16 seconds per volume. Images corresponding to the optimal inversion time (TI) can be retrospectively selected for providing the best image contrast. Reader studies were conducted to assess the performance of MP-Grasp4D MRI in liver imaging across 30 subjects in comparison with standard Grasp4D MRI without IR preparation. MP-Grasp4D MRI received significantly higher scores (P < 0.05) than Grasp4D in all assessment categories. There was a moderate to almost perfect agreement (kappa coefficient from 0.42 to 0.9) between the two readers for image quality assessment. When the scan time is reduced, MP-Grasp4D MRI preserves image contrast and quality, demonstrating additional acceleration capability. MP-Grasp4D MRI improves T1-weighted contrast for free-breathing time-resolved 4D MRI and eliminates the need for explicit motion compensation. This method is expected to be valuable in different MRI applications such as MR-guided radiotherapy.

Development and Investigation of a Grasping Analysis System with Two-Axis Force Sensors at Each of the 16 Points on the Object Surface for a Hardware-Based FinRay-Type Soft Gripper.

The FinRay soft gripper achieves passive enveloping grasping through its functional flexible structure, adapting to the contact configuration of the object to be grasped. However, variations in beam position and thickness lead to different behaviors, making it important to research the relationship between structure and force. Conventional research using FEM simulations has tested various virtual FinRay models but replicating phenomena such as buckling and slipping has been challenging. While hardware-based methods that involve installing sensors on the gripper and the object to analyze their states have been attempted, no studies have focused on the tangential contact force related to slipping. Therefore, we developed a 16-way object contact force measurement device incorporating two-axis force sensors into each of the 16 segmented objects and compared the normal and tangential components of the enveloping grasping force of the FinRay soft gripper under two types of contact friction conditions. In the first experiment, the proposed device was compared with a device containing a six-axis force sensor in one segmented object, confirming that the proposed device has no issues with measurement performance. In the second experiment, comparisons of the proposed device were made under various conditions: two contact friction states, three object contact positions, and two object motion states. The results demonstrated that the proposed device could decompose and analyze the grasping force into its normal and tangential components for each segmented object. Moreover, low friction conditions result in a wide contact area with lower tangential frictional force and a uniform normal pushing force, achieving effective enveloping grasping.

Detecting Transitions from Stability to Instability in Robotic Grasping Based on Tactile Perception.

Robots execute diverse load operations, including carrying, lifting, tilting, and moving objects, involving load changes or transfers. This dynamic process can result in the shift of interactive operations from stability to instability. In this paper, we respond to these dynamic changes by utilizing tactile images captured from tactile sensors during interactions, conducting a study on the dynamic stability and instability in operations, and propose a real-time dynamic state sensing network by integrating convolutional neural networks (CNNs) for spatial feature extraction and long short-term memory (LSTM) networks to capture temporal information. We collect a dataset capturing the entire transition from stable to unstable states during interaction. Employing a sliding window, we sample consecutive frames from the collected dataset and feed them into the network for the state change predictions of robots. The network achieves both real-time temporal sequence prediction at 31.84 ms per inference step and an average classification accuracy of 98.90%. Our experiments demonstrate the network's robustness, maintaining high accuracy even with previously unseen objects.

GDNF improves the cognitive ability of PD mice by promoting glycosylation and membrane distribution of DAT.

The core of clinic treatment of Parkinson's disease (PD) is to enhance dopamine (DA) signaling within the brain. The regulation of dopamine transporter (DAT) is integral to this process. This study aims to explore the regulatory mechanism of glial cell line-derived neurotrophic factor (GDNF) on DAT, thereby gaining a profound understanding its potential value in treating PD. In this study, we investigated the effects of GDNF on both cellular and mouse models of PD, including the glycosylation and membrane transport of DAT detected by immunofluorescence and immunoblotting, DA signal measured by neurotransmitter fiber imaging technology, Golgi morphology observed by electron microscopic, as well as cognitive ability assessed by behavior tests. This study revealed that in animal trials, MPTP-induced Parkinson's Disease (PD) mice exhibited a marked decline in cognitive function. Utilizing ELISA and neurotransmitter fiber imaging techniques, we observed a decrease in dopamine levels and a significant reduction in the intensity of dopamine signal release in the Prefrontal Cortex (PFC) of PD mice induced by MPTP. Intriguingly, these alterations were reversed by Glial Cell Line-Derived Neurotrophic Factor (GDNF). In cellular experiments, following MPP + intervention, there was a decrease in Gly-DAT modification in both the cell membrane and cytoplasm, coupled with an increase in Nongly-DAT expression and aggregation of DAT within the cytoplasm. Conversely, GDNF augmented DAT glycosylation and facilitated its membrane transport in damaged dopaminergic neurons, concurrently reversing the effects of GRASP65 depletion and Golgi fragmentation, thereby reducing the accumulation of DAT in the Golgi apparatus. Furthermore, overexpression of GRASP65 enhanced DAT transport in PD cells and mice, while suppression of GRASP65 attenuated the efficacy of GDNF on DAT. Additionally, GDNF potentiated the reutilization of neurotransmitters by the PFC presynaptic membrane, boosting the effective release of dopamine following a single electrical stimulation, ultimately ameliorating the cognitive impairments in PD mice.Therefore, we propose that GDNF enhances the glycosylation and membrane trafficking of DAT by facilitating the re-aggregation of the Golgi apparatus, thereby amplifying the utilization of DA signals. This ultimately leads to the improvement of cognitive abilities in PD mouse models. Our study illuminates, from a novel angle, the beneficial role of GDNF in augmenting DA utilization and cognitive function in PD, providing fresh insights into its therapeutic potential.

Comparison of golden-angle radial sparse parallel (GRASP) and conventional cartesian sampling in 3D dynamic contrast-enhanced mri for bladder cancer: a preliminary study.

PURPOSE: To compare the image quality, inter-reader agreement, and diagnostic capability for muscle-invasive bladder cancer (MIBC) of the reconstructed images in sections orthogonal to the bladder tumor obtained by 3D Dynamic contrast-enhanced (DCE)-MRI using the Golden-angle Radial Sparse Parallel (GRASP) technique with the images directly captured using the Cartesian sampling. MATERIALS AND METHODS: This study involved 68 initial cases of bladder cancer examined with DCE-MRI (GRASP: n = 34, Cartesian: n = 34) at 3 Tesla. Four radiologists conducted qualitative evaluations (overall image quality, absence of motion artifact, absence of streak artifact, and tumor conspicuity) using a five-point Likert scale (5 = Excellent/None) and quantitative signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements. The areas under the receiver-operating characteristic curves (AUCs) for the Vesical Imaging-Reporting and Data System (VI-RADS) DCE score for MIBC assessment were calculated. Inter-reader agreement was also assessed. RESULTS: GRASP notably enhanced overall image quality (pooled score: GRASP 4 vs. Cartesian 3, P < 0.0001), tumor conspicuity (5 vs. 3, P < 0.05), SNR (Median 38.2 vs. 19.0, P < 0.0001), and CNR (7.9 vs. 6.0, P = 0.005), with fewer motion artifacts (5 vs. 3, P < 0.0001) and minor streak artifacts (5 vs. 5, P > 0.05). Although no significant differences were observed, the GRASP group tended to have higher AUCs for MIBC (pooled AUCs: 0.92 vs. 0.88) and showed a trend toward higher inter-reader agreement (pooled kappa-value: 0.70 vs. 0.63) compared to the Cartesian group. CONCLUSIONS: Using the GRASP for 3D DCE-MRI, the reconstructed images in sections orthogonal to the bladder tumor achieved higher image quality and improve the clinical work flow, compared to the images directly captured using the Cartesian. GRASP tended to have higher diagnostic ability for MIBC and showed a trend toward higher inter-reader agreement compared to the Cartesian.

Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer.

Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial-mesenchymal transition (EMT) were investigated with explorative shotgun proteomics complemented by a Random Forest (RF) machine-learning approach. Deep and superficial tumor regions and distant-site non-tumor samples from the same patients (n = 16) were analyzed. Among the 2009 proteins analyzed, 91 proteins, including 23 novel potential CRC hallmarks, showed significant quantitative changes. In addition, a 98.4% accurate classification of the three analyzed tissues was obtained by RF using a set of 21 proteins. Subunit E1 of 2-oxoglutarate dehydrogenase (OGDH-E1) was the best classifying factor for the superficial tumor region, while sorting nexin-18 and coatomer-beta protein (beta-COP), implicated in protein trafficking, classified the deep region. Down- and up-regulations of metabolic checkpoints involved different proteins in superficial and deep tumors. Analogously to immune checkpoints affecting the TME, cytoskeleton and extracellular matrix (ECM) dynamics were crucial for EMT. Galectin-3, basigin, S100A9, and fibronectin involved in TME-CRC-ECM crosstalk were found to be differently variated in both tumor regions. Different metabolic strategies appeared to be adopted by the two CRC regions to uncouple the Krebs cycle and cytosolic glucose metabolism, promote lipogenesis, promote amino acid synthesis, down-regulate bioenergetics in mitochondria, and up-regulate oxidative stress. Finally, correlations with the Dukes stage and budding supported the finding of novel potential CRC hallmarks and therapeutic targets.

Feasibility of Adjunct Therapy with a Robotic Hand Orthosis after Botulinum Toxin Injections in Persons with Spasticity: A Pilot Study.

Upper-limb spasticity, frequent after central nervous system lesions, is typically treated with botulinum neurotoxin type A (BoNT-A) injections to reduce muscle tone and increase range of motion. However, performing adjunct physical therapy post-BoNT-A can be challenging due to residual weakness or spasticity. This study evaluates the feasibility of hand therapy using a robotic hand orthosis (RELab tenoexo) with a mobile phone application as an adjunct to BoNT-A injections. Five chronic spastic patients participated in a two-session pilot study. Functional (Box and Block Test (BBT), Action Research Arm Test (ARAT)), and muscle tone (Modified Ashworth Scale (MAS)) assessments were conducted to assess functional abilities and impairment, along with usability evaluations. In the first session, subjects received BoNT-A injections, and then they performed a simulated unsupervised therapy session with the RELab tenoexo in a second session a month later. Results showed that BoNT-A reduced muscle tone (from 12.2 to 7.4 MAS points). The addition of RELab tenoexo therapy was safe, led to functional improvements in four subjects (two-cube increase in BBT as well as 2.8 points in grasp and 1.3 points in grip on ARAT). Usability results indicate that, with minor improvements, adjunct RELab tenoexo therapy could enhance therapy doses and, potentially, long-term outcomes.

Comparing the Pre-writing Skills of Diplegic Cerebral Palsy Children to Those of Normal Children.

INTRODUCTION: The pencil grasp and drawing patterns are specific to different age levels. So, if one knows a certain pattern for that particular age, it will guide the intervention plan for children with cerebral palsy (CP). The chances of improvement in diplegic CP are possible with the help of early intervention; therefore, early intervention is only possible if one knows the areas of delay and the age at which the intervention should be started. MATERIAL AND METHODS: It was a cross-sectional, case-control study. A total of 60 children were selected for the study, of which 30 (50%) were normal and 30 (50%) had diplegic cerebral palsy. A convenient sampling method is used for evaluation. RESULTS: The t-value for pencil grasp between the two groups, i.e., normal and CP diplegic, was 3.515 (P=0.001), revealing a significant difference in the grasp pattern of the two groups. Similarly, the t-value for drawing patterns between the two groups, i.e., normal and CP diplegic, was 5.796 (P = 0.001). A significant difference was found in the drawing patterns of both groups. CONCLUSION: Our study found that diplegic CP children performed lower on the Erhardt Developmental Prehension Assessment (EDPA) and showed larger variation in the pencil grasp and drawing than the normal children.

Extensor Carpi Radialis Brevis Tendon Transfer for Thumb and Finger Flexion Reconstruction after Failed Extensor Carpi Radialis Brevis Motor Branch Transfer in a Tetraplegic Patient.

Distal nerve transfers can restore precise motor control in tetraplegic patients. When nerve transfers are not successful, tendon transfers may be used for subsequent reconstruction. In this case, an extensor carpi radialis brevis (ECRB) tendon transfer was used to restore thumb and finger flexion following an unsuccessful ECRB to anterior interosseous nerve transfer in a young tetraplegic patient. Twelve months following tendon transfer, the patient demonstrated functional grip and pinch strength and was using both hands for daily activities. Level of Evidence: Level V (Therapeutic).

Real-time visual feedback can cue changes in grip force during electric hand tool operation.

Objectives. Grip force applied during repetitive hand tool use varies amongst individuals and some apply more force than necessary. Augmented feedback may help modify grip force to reduce the risk of developing cumulative trauma disorders but has been scarcely investigated during electric hand tool operation. This study evaluated the feasibility of using real-time visual feedback to modify grip force and forearm electromyography (EMG) during electric hand tool operation. A secondary objective was to evaluate the effect of hand and tool orientation on any effects of visual feedback. Methods. Grip force and forearm muscle EMG were recorded as participants fastened bolts at three locations (low, high and overhead) using an electric pistol-grip nut-runner, without and with visual feedback. Results. Feedback decreased grip force (36.1% decrease; p < 0.001) and EMG of three wrist flexor muscles (22.8-33.0%; p < 0.008). Grip force and EMG also differed between fastening locations, but there were no interactions with condition (baseline and feedback; p > 0.266), suggesting that visual feedback can modify grip force across varying hand and tool orientations. Conclusion. Visual feedback can successfully modify grip force during hand tool operation. However, further investigation is needed to understand how to appropriately implement visual feedback during hand tool operation.

Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach.

Grasp classification is pivotal for understanding human interactions with objects, with wide-ranging applications in robotics, prosthetics, and rehabilitation. This study introduces a novel methodology utilizing a multisensory data glove to capture intricate grasp dynamics, including finger posture bending angles and fingertip forces. Our dataset comprises data collected from 10 participants engaging in grasp trials with 24 objects using the YCB object set. We evaluate classification performance under three scenarios: utilizing grasp posture alone, utilizing grasp force alone, and combining both modalities. We propose Glove-Net, a hybrid CNN-BiLSTM architecture for classifying grasp patterns within our dataset, aiming to harness the unique advantages offered by both CNNs and BiLSTM networks. This model seamlessly integrates CNNs' spatial feature extraction capabilities with the temporal sequence learning strengths inherent in BiLSTM networks, effectively addressing the intricate dependencies present within our grasping data. Our study includes findings from an extensive ablation study aimed at optimizing model configurations and hyperparameters. We quantify and compare the classification accuracy across these scenarios: CNN achieved 88.09%, 69.38%, and 93.51% testing accuracies for posture-only, force-only, and combined data, respectively. LSTM exhibited accuracies of 86.02%, 70.52%, and 92.19% for the same scenarios. Notably, the hybrid CNN-BiLSTM proposed model demonstrated superior performance with accuracies of 90.83%, 73.12%, and 98.75% across the respective scenarios. Through rigorous numerical experimentation, our results underscore the significance of multimodal grasp classification and highlight the efficacy of the proposed hybrid Glove-Net architectures in leveraging multisensory data for precise grasp recognition. These insights advance understanding of human-machine interaction and hold promise for diverse real-world applications.

Design and Control of a Tendon-Driven Robotic Finger Based on Grasping Task Analysis.

To analyze the structural characteristics of a human hand, data collection gloves were worn for typical grasping tasks. The hand manipulation characteristics, finger end pressure, and finger joint bending angle were obtained via an experiment based on the Feix grasping spectrum. Twelve types of tendon rope transmission paths were designed under the N + 1 type tendon drive mode, and the motion performance of these 12 types of paths applied to tendon-driven fingers was evaluated based on the evaluation metric. The experiment shows that the designed tendon path (d) has a good control effect on the fluctuations of tendon tension (within 0.25 N), the tendon path (e) has the best control effect on the joint angle of the tendon-driven finger, and the tendon path (l) has the best effect on reducing the friction between the tendon and the pulley. The obtained tendon-driven finger motion performance model based on 12 types of tendon paths is a good reference value for subsequent tendon-driven finger structure design and control strategies.

Synaptic correlates of the corticocortical circuit in motor learning.

Rodents actively learn new motor skills for survival in reaction to changing environments. Despite the classic view of the primary motor cortex (M1) as a simple muscle relay region, it is now known to play a significant role in motor skill acquisition. The secondary motor cortex (M2) is reported to be a crucial region for motor learning as well as for its role in motor execution and planning. Although these two regions are known for the part they play in motor learning, the role of direct connection and synaptic correlates between these two regions remains elusive. Here, we confirm M2 to M1 connectivity with a series of tracing experiments. We also show that the accelerating rotarod task successfully induces motor skill acquisition in mice. For mice that underwent rotarod training, learner mice showed increased synaptic density and spine head size for synapses between activated cell populations of M2 and M1. Non-learner mice did not show these synaptic changes. Collectively, these data suggest the potential importance of synaptic plasticity between activated cell populations as a potential mechanism of motor learning. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.