A Micromanipulation-Actuated Large-Scale Screening to Identify Optimized Microphysiological Model Parameters in Skeletal Muscle Regeneration.

Hydrogel-based 3D cell cultures are extensively utilized to create biomimetic cellular microstructures. However, there is still lack of effective method for both evaluation of the complex interaction of cells with hydrogel and the functionality of the resulting micro-structures. This limitation impedes the further application of these microstructures as microphysiological models (microPMs) for the screening of potential culture condition combinations to enhance the skeletal muscle regeneration.

Pattern Matching for Real-Time Extraction of Fast and Slow Spectral Components From sEMG Signals.

Previous studies have demonstrated the potential of surface electromyography (sEMG) spectral decomposition in evaluating muscle performance, motor learning, and early diagnosis of muscle conditions. However, decomposition techniques require large data sets and are computationally demanding, making their implementation in real-life scenarios challenging. Based on the hypothesis that spectral components will present low inter-subject variability, the present paper proposes the foundational principles for developing a real-time system for their extraction by utilizing a pre-defined library of components derived from an extensive data set to match new measurements.

Enriched sensory feedback delivered during a voluntary action boosts subjective time compression.

Introduction: The subjective experience of time can be influenced by various factors including voluntary actions. In our previous study, we found that the subjective time experience of an action outcome can be compressed when an individual performs a continuous action compared to a single action, suggesting that the sense of agency (SoA), the feeling of control over one's own action outcomes, contributes to the subjective time compression. We hypothesized that enhancing SoA by providing sensory feedback to participants would further compress the subjective time experience.

Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat.

In this paper, we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement learning. Specifically, we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat interactions. The novelty of our method lies in using the temporal difference (TD) algorithm to optimize the state decision process, which enables the robots to make informed decisions about their behavior choices.

Synergy-Space Recurrent Neural Network for Transferable Forearm Motion Prediction from Residual Limb Motion.

Transhumeral amputees experience considerable difficulties with controlling a multifunctional prosthesis (powered hand, wrist, and elbow) due to the lack of available muscles to provide electromyographic (EMG) signals. The residual limb motion strategy has become a popular alternative for transhumeral prosthesis control. It provides an intuitive way to estimate the motion of the prosthesis based on the residual shoulder motion, especially for target reaching tasks.

Artifact removal from sEMG signals recorded during fully unsupervised daily activities.

Objective: In this study, we propose a method for removing artifacts from superficial electromyography (sEMG) data, which have been widely proposed for health monitoring because they encompass the basic neuromuscular processes underlying human motion.

Methods: Our method is based on a spectral source decomposition from single-channel data using a non-negative matrix factorization. The algorithm is validated with two data sets: the first contained muscle activity coupled to artificially generated noises and the second comprised signals recorded under fully unsupervised conditions.

Demonstration experiment of telemedicine using ultrasonography and telerehabilitation with 5G communication system in aging and depopulated mountainous area.

Objective: The challenges of an aging population worldwide are the increased number of people needing medical and nursing care and inadequate medical resources. Information and communication technologies have progressed remarkably, leading to innovations in various areas. 5G communication systems are capable of high-capacity, high-speed communication with low latency and are expected to transform medicine.

Synergetic synchronized oscillation by distributed neural integrators to induce dynamic equilibrium in energy dissipation systems.

The synchronization phenomenon is common to many natural mechanical systems. Joint friction and damping in humans and animals are associated with energy dissipation. A coupled oscillator model is conventionally used to manage multiple joint torque generations to form a limit cycle in an energy dissipation system.

Quantification of the Swallowing Mechanism Through Muscle Synergy Analysis.

Decreased swallowing function increases the risk of choking and aspiration pneumonia. Videofluoroscopy and computed tomography allow for detailed observation of the swallowing movements but have radiation risks. Therefore, we developed a method using surface electromyography (sEMG) to noninvasively assess swallowing function without radiation exposure.

Telerehabilitation Based on Markerless Motion Capture and IMT-2020 (5G) Networks.

Eldercare programs such as health consultations and physiotherapy that improve the well-being and extend the life expectancy of people in rural or sparsely populated areas is a socially important though costly problem. We ran a pilot project to test the effectiveness potential of telerehabilitation using markerless motion capture technology integrated in a fast and low-latency IMT-2020 (5G) mobile network. Accelerating technological innovations and the surge in advances of telehealth will greatly impact conventional home visit or outpatient rehabilitation services, working in concert with or even supplanting them, given the potential lower cost and better utilization of time.

Accurate modulation of photoprinting under stiffness imaging feedback for engineering ECMs with high-fidelity mechanical properties.

Engineered extracellular matrices (ECMs) that replicate complex in-vivo features have shown great potential in tissue engineering. Biocompatible hydrogel microstructures have been widely used to replace these native ECMs for physiologically relevant research. However, accurate reproduction of the 3D hierarchical and nonuniform mechanical stiffness inside one integrated microstructure to mimic the complex mechanical properties of native ECMs presents a major challenge.

Quantification of high and low sEMG spectral components during sustained isometric contraction.

Superficial Electromyography (sEMG) spectrum contains aggregated information from several underlying physiological processes. Due to technological limitations, the isolation of these processes is challenging, and therefore, the interpretation of changes in muscle activity frequency is still controversial. Recent studies showed that the spectrum of sEMG signals recorded from isotonic and short-term isometric contractions can be decomposed into independent components whose spectral features recall those of motor unit action potentials.

Forearm muscle activity estimation based on anatomical structure of muscles.

Estimation of muscle activity using surface electromyography (sEMG) is an important non-invasive method that can lead to a deeper understanding of motor-control strategies in humans. Measurement using multiple active electrodes is necessary to estimate not only surface muscle activity but also deep muscle activity in dynamic motion. In this paper, we propose a method for estimating muscle activity of dynamic motions based on anatomical knowledge of muscle structures.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling.

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation.

Bio-inspired engineering of a perfusion culture platform for guided three-dimensional nerve cell growth and differentiation.

Collagen provides a promising environment for 3D nerve cell culture; however, the function of perfusion culture and cell-growth guidance is difficult to integrate into such an environment to promote cell growth. In this paper, we develop a bio-inspired design method for constructing a perfusion culture platform for guided nerve cell growth and differentiation in collagen. Based on the anatomical structure of peripheral neural tissue, a biomimetic porous structure (BPS) is fabricated by two-photon polymerization of IP-Visio.

Effects of Force Modulation on Large Muscles during Human Cycling.

Voluntary force modulation is defined as the ability to tune the application of force during motion. However, the mechanisms behind this modulation are not yet fully understood. In this study, we examine muscle activity under various resistance levels at a fixed cycling speed.

Subjective time compression induced by continuous action.

Increasing evidence indicates that voluntary actions can modulate the subjective time experience of its outcomes to optimize dynamic interaction with the external environment. In the present study, using a temporal reproduction task where participants reproduced the duration of an auditory stimulus to which they were previously exposed by performing different types of voluntary action, we examined how the subjective time experience of action outcomes changed with voluntary action types. Two experiments revealed that the subjective time experience of action outcomes was compressed, compared with physical time, if the action was performed continuously (Experiment 1), possibly enhancing the experience of controlling the action outcome, or if the action was added an extra task-unrelated continuous action (Experiment 2), possibly reflecting different underlying mechanisms from subjective time compression induced by the task-related continuous action.

Robotic assistive and rehabilitation devices leading to motor recovery in upper limb: a systematic review.

Purpose: Stroke, spinal cord injury and other neuromuscular disorders lead to impairments in the human body. Upper limb impairments, especially hand impairments affect activities of daily living (ADL) and reduce the quality of life. The purpose of this review is to compare and evaluate the available robotic rehabilitation and assistive devices that can lead to motor recovery or maintain the current motor functional level.

Electroencephalographic Functional Connectivity With the Tacit Learning System Prosthetic Hand: A Case Series Using Motor Imagery.

We previously created a prosthetic hand with a tacit learning system (TLS) that automatically supports the control of forearm pronosupination. This myoelectric prosthetic hand enables sensory feedback and flexible motor output, which allows users to move efficiently with minimal burden. In this study, we investigated whether electroencephalography can be used to analyze the influence of the auxiliary function of the TLS on brain function.

Haptic Adaptive Feedback to Promote Motor Learning With a Robotic Ankle Exoskeleton Integrated With a Video Game.

Robotic devices have been used to rehabilitate walking function after stroke. Although results suggest that post-stroke patients benefit from this non-conventional therapy, there is no agreement on the optimal robot-assisted approaches to promote neurorecovery. Here we present a new robotic therapy protocol using a grounded exoskeleton perturbing the ankle joint based on tacit learning control.

Emerging Cognitive Intervention Technologies to Meet the Needs of an Aging Population: A Systematic Review.

Cognitive training helps to promote healthy aging and ease activities of daily living for older adults. Recently, experiments have been conducted using robots to perform this cognitive training. A review was conducted to examine the effects of computer-based cognitive interventions for older adults who were either healthy or experiencing mild cognitive impairment (MCI).

Function Based Brain Modeling and Simulation of an Ischemic Region in Post-Stroke Patients using the Bidomain.

Background: Several studies have shown that post-stroke patients develop divergent activity in the sensorimotor areas of the affected hemisphere of the brain compared to healthy people during motor tasks. Proper mathematical models will help us understand this activity and clarify the associated underlying mechanisms. New Method.

Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors.

Background: Muscle synergies are now widely discussed as a method for evaluating the existence of redundant neural networks that can be activated to enhance stroke rehabilitation. However, this approach was initially conceived to study muscle coordination during learned motions in healthy individuals. After brain damage, there are several neural adaptations that contribute to the recovery of motor strength, with muscle coordination being one of them.