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Abstract The implementation of home-care robots is sometimes unsuccessful. This study aimed to explore factors explaining people’s willingness to use home-care robots, particularly among care recipients and caregivers. Surveys were conducted in Japan, Ireland, and Finland. The survey questionnaire comprised four categories (familiarity with robots, important points about home-care robots, functions expected from home-care robots, and ethically acceptable uses), with 48 items assessing users’ willingness to use home-care robots. The responses from 525 Japanese, 163 Irish, and 170 Finnish respondents were analyzed to identify common and distinct factors influencing their willingness to use these robots. Common factors across the countries included “willingness to participate in research and development,” “interest in robot-related news,” and “having a positive impression of robots”. The distinct factors for each country were: “convenience” in Japan; “notifying family members and support personnel when an unexpected change occurs in an older person” in Ireland; and “design” in Finland. Therefore, developers should determine potential users’ willingness to participate in the research and development of home-care robots and consider a system that involves them in the development process.

Abstract Background Hepatitis B virus (HBV) infection poses a substantial threat to human health, impacting not only infected individuals but also potentially exerting adverse effects on the health of their offspring. The underlying mechanisms driving this phenomenon remain elusive. This study aims to shed light on this issue by examining alterations in paternally imprinted genes within sperm. Methods A cohort of 35 individuals with normal semen analysis, comprising 17 hepatitis B surface antigen (HBsAg)-positive and 18 negative individuals, was recruited. Based on the previous research and the Online Mendelian Inheritance in Man database (OMIM, https://www.omim.org/ ), targeted promoter methylation sequencing was employed to investigate 28 paternally imprinted genes associated with various diseases. Results Bioinformatic analyses revealed 42 differentially methylated sites across 29 CpG islands within 19 genes and four differentially methylated CpG islands within four genes. At the gene level, an increase in methylation of DNMT1 and a decrease in methylation of CUL7, PRKAG2, and TP53 were observed. DNA methylation haplotype analysis identified 51 differentially methylated haplotypes within 36 CpG islands across 22 genes. Conclusions This is the first study to explore the effects of HBV infection on sperm DNA methylation and the potential underlying mechanisms of intergenerational influence of paternal HBV infection.

Abstract Upper limb prostheses are commonly propelled by pneumatic artificial muscles organized in an antagonistic arrangement. Nonetheless, the control of upper limb prostheses under changing/unknown situations is difficult and necessary for a variety of real-world applications. Adaptive control, learning-based control, and robust control have been studied to deal with such challenges. However, their adaptability is insufficient for prostheses used in daily life, which are exposed to variable task levels, user motor characteristics, and prosthetic features. This paper introduces a highly adaptive controller for the first time based on Generative Adversarial Nets and proportional–integral–derivative controller (G-PID controller). G-PID controller comprises a generator for generating compensation actions to enhance PID responsiveness when controlling the unknown/changing system. Moreover, it incorporates a discriminator that receives responses from both a user-preselected reference system and the compensated changing/unknown system, and simultaneously determines the source of these responses. Through continuous updates, the compensator modifies the response of unknown/changing system to align with the reference system, thereby facilitating adaptive control. The G-PID controller’s effectiveness is evaluated through 1-degree of freedom (DoF) joint and 2-DoF shoulder prostheses in simulation experiments, and further validated in prototype experiments focusing on online learning for unknown and time-varying payload. The results demonstrate its ability to deal with diverse types of unknowns/changes, marking a significant advancement towards incorporating prostheses seamlessly into daily life.

Objective A ballistocardiogram (BCG) is a vibration signal generated by the ejection of the blood in each cardiac cycle. The BCG has significant variability in amplitude, temporal aspects, and the deficiency of waveform components, attributed to individual differences, instantaneous heart rate, and the posture of the person being measured. This variability may make methods of extracting J-waves, the most distinct components of BCG less generalizable so that the J-waves could not be precisely localized, and further analysis is difficult. This study is dedicated to solving the variability of BCG to achieve accurate feature extraction. Methods Inspired by the generation mechanism of the BCG, we proposed an original method based on a profile of second-order derivative of BCG waveform (2ndD-P) to capture the nature of vibration and solve the variability, thereby accurately localizing the components especially when the J-wave is not prominent. Results In this study, 51 recordings of resting state and 11 recordings of high-heart-rate from 24 participants were used to validate the algorithm. Each recording lasts about 3 min. For resting state data, the sensitivity and positive predictivity of proposed method are: 98.29% and 98.64%, respectively. For high-heart-rate data, the proposed method achieved a performance comparable to those of low-heart-rate: 97.14% and 99.01% for sensitivity and positive predictivity, respectively. Conclusion Our proposed method can detect the peaks of the J-wave more accurately than conventional extraction methods, under the presence of different types of variability. Higher performance was achieved for BCG with non-prominent J-waves, in both low- and high-heart-rate cases.

Abstract Background The repair of bone defects caused by periodontal diseases is a difficult challenge in clinical treatment. Dental pulp stem cells (DPSCs) are widely studied for alveolar bone repair. The current investigation aimed to examine the specific mechanisms underlying the role of Zinc finger DHHC-type palmitoyl transferases 16 (ZDHHC16) in the process of osteogenic differentiation (OD) of DPSCs. Methods The lentiviral vectors ZDHHC16 or si-ZDHHC16 were introduced in the DPSCs and then the cells were induced by an odontogenic medium for 21 days. Subsequently, Quantitate Polymerase Chain Reaction (PCR), immunofluorescent staining, proliferation assay, ethynyl deoxyuridine (EdU) staining, and western blot analysis were used to investigate the specific details of ZDHHC16 contribution in OD of DPSCs. Results Our findings indicate that ZDHHC16 exhibited a suppressive effect on cellular proliferation and oxidative phosphorylation, while concurrently inducing ferroptosis in DPSCs. Moreover, the inhibition of ZDHHC16 promoted cell development and OD and reduced ferroptosis of DPSCs. The expression of p-CREB was suppressed by ZDHHC16, and immunoprecipitation (IP) analysis revealed that ZDHHC16 protein exhibited interconnection with cAMP-response element binding protein (CREB) of DPSCs. The CREB suppression reduced the impacts of ZDHHC16 on OD and ferroptosis of DPSCs. The activation of CREB also reduced the influences of si-ZDHHC16 on OD and ferroptosis of DPSCs. Conclusions These findings provide evidences to support a negative association between ZDHHC16 and OD of DPSCs, which might be mediated by ferroptosis of DPSCs via CREB.

Abstract With the increasing global aging population, dementia care has rapidly become a major social problem. Current diagnosis of Behavior and Psychological Symptoms of Dementia (BPSD) relies on clinical interviews, and behavioral rating scales based on a period of behavior observation, but these methods are not suitable for identification of occurrence of BPSD in the daily living, which is necessary for providing appropriate interventions for dementia, though, has been studied by few research groups in the literature. To address these issues, in this study developed a BPSD monitoring system consisting of a Psycho-Cognitive (PsyCo) BPSD model, a Behavior-Physio-Environment (BePhyEn) BPSD model, and an implementation platform. The PsyCo BPSD model provides BPSD assessment support to caregivers and care providers, while the BePhyEn BPSD model provides instantaneous alerts for BPSD enabled by a 24-hour home monitoring platform for early intervention, and thereby alleviation of burden to patients and caregivers. Data for acquiring the models were generated through extensive literature review and regularity determined. A mobile robot was utilized as the implementation platform for improving sensitivity of sensors for home monitoring, and elderly individual following algorithms were investigated. Experiments in a virtual home environment showed that, a virtual BPSD elderly individual can be followed safely by the robot, and BPSD occurrence could be identified accurately, demonstrating the possibility of modeling and identification of BPSD in home environment.

The simulation-to-reality (sim2real) problem is a common issue when deploying simulation-trained models to real-world scenarios, especially given the extremely high imbalance between simulation and real-world data (scarce real-world data). Although the cycle-consistent generative adversarial network (CycleGAN) has demonstrated promise in addressing some sim2real issues, it encounters limitations in situations of data imbalance due to the lower capacity of the discriminator and the indeterminacy of learned sim2real mapping. To overcome such problems, we proposed the imbalanced Sim2Real scheme (ImbalSim2Real). Differing from CycleGAN, the ImbalSim2Real scheme segments the dataset into paired and unpaired data for two-fold training. The unpaired data incorporated discriminator-enhanced samples to further squash the solution space of the discriminator, for enhancing the discriminator’s ability. For paired data, a term targeted regression loss was integrated to ensure specific and quantitative mapping and further minimize the solution space of the generator. The ImbalSim2Real scheme was validated through numerical experiments, demonstrating its superiority over conventional sim2real methods. In addition, as an application of the proposed ImbalSim2Real scheme, we designed a finger joint stiffness self-sensing framework, where the validation loss for estimating real-world finger joint stiffness was reduced by roughly 41% compared to the supervised learning method that was trained with scarce real-world data and by 56% relative to the CycleGAN trained with the imbalanced dataset. Our proposed scheme and framework have potential applicability to bio-signal estimation when facing an imbalanced sim2real problem.

In recent years, a proliferation of soft actuators tailored for hand rehabilitation has been observed. In particular, modular soft actuators have garnered particular interest due to their capacity for individual customization and joint-specific support, a feature often lacking in whole-finger soft actuators. Despite these advancements, a significant limitation persists: the majority of these actuators facilitate only finger flexion, neglecting the equally vital extension movements required for comprehensive hand rehabilitation. Traditional approaches to achieving multi-degree-of-freedom or bidirectional motion have relied on the integration of multiple chambers within soft actuators. However, this strategy has proven impractical for modular soft actuators, primarily due to spatial constraints within the finger joint. To address this challenge, we introduce a foldable pouch actuator (FPA). Designed as a flat, foldable structure composed of a single sheet, the FPA expands solely upon pressurization, generating the requisite force for finger extension. Notably, the FPA seamlessly integrates with existing modular soft actuators without compromising their structural integrity or functional capabilities, thereby enabling bidirectional support for individual joints. Evaluations using a synthetic finger model achieved a joint flexion torque of 0.17 Nm and estimated an overall extension torque of 0.12 Nm. These advancements were accomplished without compromising the traditional flexion functionality, adding individual joint extension support to the existing capabilities. This study constitutes a substantive leap forward in the utilization of soft actuators for clinical hand rehabilitation applications.

Soft actuators developed for hand rehabilitation show promise, but their practical application requires addressing individual differences and establishing suitable design rules. While joint modular soft actuators offer flexibility for diverse hand dimensions, existing performance validations have only examined a limited number of actuator sizes and neglected crucial factors like joint alignment. Customization efforts have lacked standardization, relying on a trial-and-error approach. Therefore, this study systematically evaluates the impact of actuator design parameters (size and mounting position) on joint range of motion (ROM) and torque, proposing novel design rules based on linear optimization. Experimental assessments, conducted on dummy fingers emulating human biomechanics, provide profound insights into the intricate interplay of design parameters and support performance. The findings strongly advocate maintaining a reference position for stable support, irrespective of actuator size, emphasizing the need to align the actuator with the joint center. The proposed design rules incorporate user-specific finger information, offering customized design rules. Proportionate actuator lengths to single-phalangeal length (PsPL), Proportionate actuator lengths to multi-phalangeal length (PmPL), Proportionate actuator lengths to Range of Motion (PROM), and the Traditional Method are systematically compared. Assistive performances (ROM and torque) and trajectory analysis reveal that the PsPL-designed actuator exhibits the most stable and natural assistive performance. This study emphasizes the importance of understanding actuator deformations for personalized adaptation, providing valuable insights for advancements in assistive and rehabilitative technologies.

The ability to stimulate deep brain regions in a focal manner brings new opportunities for treating brain disorders. Temporal interference (TI) stimulation has been suggested as a method to achieve focused stimulation in deep brain targets. Individual-level knowledge of the interferential currents has permitted personalizing TI montage via subject-specific digital human head models, facilitating the estimation of interferential electric currents in the brain. While this individual approach offers a high degree of personalization, the significant intra-and inter-individual variability among specific head models poses challenges when comparing electric-field doses. Furthermore, MRI acquisition to develop a personalized head model, followed by precise methods for placing the optimized electrode positions, is complex and not always available in various clinical settings. Instead, the registration of individual electric fields into brain templates has offered insights into population-level effects and enabled montage optimization using common scalp landmarks. However, population-level knowledge of the interferential currents remains scarce. This work aimed to investigate the effectiveness of targeting deep brain areas using TI in different populations. The results showed a trade-off between deep stimulation and unwanted cortical neuromodulation, which is target-dependent at the group level. A consistent modulated electric field appeared in the deep brain target when the same montage was applied in different populations. However, the performance in terms of focality and variability varied when the same montage was used among populations. Also, group-level TI exhibited greater focality than tACS, reducing unwanted neuromodulation volume in the cortical part by at least 1.5 times, albeit with higher variability. These results provide valuable population-level insights when considering TI montage selection.

Introduction: Minimally Invasive Surgery (MIS) offers targeted surgical access with reduced invasiveness; however, the maneuverability challenges of traditional instruments in this domain underscore the need for innovative solutions. Soft actuators activated by fluids or gases present a promising strategy for augmenting endoscopic capabilities, thereby enhancing the surgical precision in MIS. This study aimed to explore the intricate dynamics of the interactions between soft actuators and endoscopes, with an emphasis on the pivotal role of cross-sectional chamber shapes. While previous studies have touched on the influence of chamber shapes on bending properties, we provide a comprehensive exploration. We explore how these shapes modulate friction forces, which in turn influence the interactions governing bending, response, and stiffness adjustability, all of which are essential for enhancing endoscope maneuverability in MIS contexts.Methods: A novel bilateral symmetrical air chamber design was adopted to investigate various chamber shapes. We employed finite element analysis (FEA) simulations followed by prototype testing to evaluate the interactions driven by these chamber shapes and to discern their impact on actuator properties. Recognizing the pivotal role of friction in these interactions, we conducted dedicated friction experiments. These experiments further deepened our understanding of the relationship between chamber shape and friction, and how this synergy influences the properties of the actuator.Results: Our findings showed that actuators with wider chambers generate larger friction forces, thereby enhancing the interaction and improving the bending, response, and stiffness adjustability. Additionally, the soft actuator significantly improved the maneuverability and bending radius of the endoscope, demonstrating enhanced navigation capabilities in complex environments.Discussion: The shape of a cross-sectional chamber plays a pivotal role in designing soft actuators for MIS applications. Our research emphasizes the importance of this design component, offering key insights for the development of endoscope-supporting soft actuators that can effectively handle intricate actuator-endoscope interactions, thereby enhancing surgical outcomes.

The combination of smart soft composite structure based shape memory alloy (SMA) and exoskeleton technology has the advantages of light weight, energy saving, and great human-exoskeleton interaction. However, there are no relevant studies on the application of SMA-based soft composite structure (SSCS) in hand exoskeletons. The main difficulty is that directional mechanical properties of SSCS need to comply with fingers movement, and SSCS can deliver enough output torque and displacement to the relevant joints. This paper aims to study the application of SSCS for wearable rehabilitation gloves and explore its bionic driving mechanism. This paper proposes a soft wearable glove (Glove-SSCS) for hand rehabilitation actuated by the SSCS, based on finger force analysis under different drive modes. The Glove-SSCS can support five-finger flexion and extension, weighs only 120 g, and adopts modular design. Each drive module adopts a soft composite structure. And the structure integrates actuation, sensing and execution, including an active layer (SMA spring), a passive layer (manganese steel sheet), a sensing layer (bending sensor) and connection layers. To obtain a high-performance SMA actuators, the performance of SMA materials was tested in terms of temperature and voltage, temperature at the shortest length, pre-tensile length and load. And the human-exoskeleton coupling model of Glove-SSCS is established and analyzed from force and motion. The results show that the Glove-SSCS can realize bidirectional movements of fingers flexion and extension, with ranges of motion are 90–110° and 30–40°, and their cycles are 13–19 s and 11–13 s. During the use of Glove-SSCS, the temperature of gloves is from 25 to 67°C, and the surface temperature of hands is from 32 to 36°C. The temperature of Glove-SSCS can be kept at the lowest temperature of SMA operation without much impact on the human body.

Abstract Background C5aR has been extensively studied in recent years as an essential component of the complement system. However, the role of C5aR in tumors has not been sufficiently investigated and summarized. The aim of this meta-analysis was to investigate the prognostic value of C5aR in solid tumors as well as the correlation between C5aR and clinicopathological features. Methods Relevant study collection was performed in PubMed, Embase, Web of Science, BIOSIS Previews, Cochrane Library until July 10, 2021. Pooled hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were calculated. Sensitivity analyses were performed to assess the robustness of this study, while publication bias was tested by Begg’s and Egger’s tests. Results A total of 11 studies involving 1577 patients were included in the study. Our results suggest that the high-level C5aR expression in tumor tissue predicted unsatisfactory overall survival (OS) (HR = 1.92, 95% CI:1.47–2.50, P

In a telerehabilitation environment, it is difficult for a therapist to understand the condition of a patient’s finger joints because of the lack of direct assessment. In particular, not enabling the provision of spasticity evaluation significantly reduces the optimal performance of telerehabilitation. In a previous study, it has been proposed that finger stiffness could be estimated using an analytical model of a whole-finger soft actuator. However, because the whole-finger soft actuators require high air pressure for high bending performance and are costly to customize for each patient, using joint modular soft actuators for telerehabilitation turns to be a necessity, though stiffness estimation with joint modular soft actuators has not been studied yet. Another problem is caused by using a marker-based joint angle measurement, which requires the markers to be attached to the exact positions, and limits its application in telerehabilitation. In this study, we proposed a procedure of finger joint stiffness estimation that combines information acquired from a joint modular soft actuator and a marker-less hand joint position acquisition device. Correction parameters were added to the previous analytical model for -the bending analysis of a joint assisted using a joint modular soft actuator. Moreover, a multi-variate regression model was implemented for correcting joint angles obtained from the hand joint position acquisition device. As a result, a reasonable accuracy of stiffness estimation was achieved for rehabilitation with the joint modular soft actuators, which suggests the possibility of using the proposed method to evaluate the finger spasticity in a telerehabilitation environment. This is a big step forward towards optimal hand telerehabilitation.

Classification of pain levels from evoked electroencephalography (eEEG) has been achieved for the purpose of objective assessment of pain. However, differentiation of acute and chronic pain resulting from the activation of nociceptive nerves, the Aδ and C fibers, respectively, has remained unsolved, mainly due to the lack of effective features. Granger causality (GC) was applied to show the role of specific brain areas in the differentiation between pain and tactile sensation but yet was used to differentiate nociceptive fiber activations. The purpose of this study is two-fold: first, to develop pain perception classification systems using GC as features, and second, to identify causal connectivity for effective differentiation of nociceptive fiber activations. The eEEG responding to three stimulation waveforms, 1 Hz square waves, 5 Hz sine waves, both targeting C fibers, and 250 Hz sine waves, targeting Aδ, were recorded. Three GC categories based on channel areas, frequency bands, and stimulation waveforms were computed from the eEEG and used as features to classify nociceptive fiber activations and pain levels. It was found that GCs in the alpha band produced the highest average classification accuracy of 99.71%, followed by the gamma band, with 98.66%. Meanwhile, the GC feature contributing most to differentiating Aδ and C was found in the alpha band. The GC flow computed from the results of 5 Hz and 250 Hz stimulation had an important role in the prediction of mild pain and maximum pain, respectively. These results demonstrated the high potential of GC as features of pain-related information.

Hepatocellular carcinoma (HCC) is a common malignant tumor. LukS-PV is the S component of Panton-Valetine leukocidin (PVL), which is secreted by Staphylococcus aureus. This study investigated the effects of LukS-PV on the proliferation, apoptosis, and cell-cycle progression of HCC cells and the mechanisms of its activity. The HCC cells were treated with different LukS-PV concentrations in vitro. Cell Counting Kit-8 and 5-Ethynyl-2'-deoxyuridine (EdU) assays were used to study cell proliferation. Flow cytometry was used to measure apoptosis and cell-cycle progression. Quantitative reverse transcriptase PCR and western blot assays were used to determine mRNA and protein expression levels. Xenograft experiments were performed to determine the in vivo antitumor effect of LukS-PV. Immunostaining was performed to analyze Ki-67 and HDAC2 (histone deacetylase 2) expression. Our results showed that LukS-PV inhibited cell proliferation and induced apoptosis in a concentration-dependent manner in HCC cell lines. LukS-PV also can induce cell-cycle arrest. Moreover, we discovered that LukS-PV attenuated HDAC2 expression and upregulated PTEN; phosphorylated AKT was also reduced. Further studies demonstrated that LukS-PV treatment significantly reduced tumor growth in nude mice and suppressed Ki-67 and HDAC2 levels. Our data revealed a vital role of LukS-PV in suppressing HCC progression by downregulating HDAC2 and upregulating PTEN.

It has been reported that stimulating nociceptive unmyelinated C nerves (C) near the sarcolemma could induce the secretion of endogenous opioids that relieve chronic pain. However, a substantial concern remains: concomitant stimulation might cause acute pain to nociceptive myelinated Aδ nerves (Aδ), which generally have a lower activation threshold than the C. However, few studies have reported on C selectivity over Aδ (C-selectivity). In this study, the C and Aδ nerves were modeled using the Hodgkin-Huxley (HH) and McIntyre-Richardson-Grill (MRG) models, respectively. Two potential stimulation schemes, including bipolar square waves and burst modulated alternating current, together with a new stimulation scheme named inhibit-Aδ (i-Aδ) that inhibits the excitability of theAδ, were systematically investigated. Their stimuli were given to the C and Aδ nerves through point electrodes located near the nerve fibers. Simulation results revealed that i-Aδ presented the highest C-selectivity, which provides a basis for non-invasive effective chronic-pain relief.

To provide a stable surgical view in Minimally Invasive Surgery (MIS), it is necessary for a flexible endoscope applied in MIS to have adjustable stiffness to resist different external loads from surrounding organs and tissues. Pneumatic soft actuators are expected to fulfill this role, since they could feed the endoscope with an internal access channel and adjust their stiffness via an antagonistic mechanism. For that purpose, it is essential to estimate the external load. In this study, we proposed a neural network (NN)-based active load-sensing scheme and stiffness adjustment for a soft actuator for MIS support with antagonistic chambers for three degrees of freedom (DoFs) of control. To deal with the influence of the nonlinearity of the soft actuating system and uncertainty of the interaction between the soft actuator and its environment, an environment exploration strategy was studied for improving the robustness of sensing. Moreover, a NN-based inverse dynamics model for controlling the stiffness of the soft actuator with different flexible endoscopes was proposed too. The results showed that the exploration strategy with different sequence lengths improved the estimation accuracy of external loads in different conditions. The proposed method for external load exploration and inverse dynamics model could be used for in-depth studies of stiffness control of soft actuators for MIS support.

Electrical properties (EPs) of tissues facilitate early detection of cancerous tissues. Magnetic resonance electrical properties tomography (MREPT) is a technique to non-invasively probe the EPs of tissues from MRI measurements. Most MREPT methods rely on numerical differentiation (ND) to solve partial differential Equations (PDEs) to reconstruct the EPs. However, they are not practical for clinical data because ND is noise sensitive and the MRI measurements for MREPT are noisy in nature. Recently, Physics informed neural networks (PINNs) have been introduced to solve PDEs by substituting ND with automatic differentiation (AD). To the best of our knowledge, it has not been applied to MREPT due to the challenges in using PINN on MREPT as (i) a PINN requires part of ground-truth EPs as collocation points to optimize the network’s AD, (ii) the noisy input data disrupts the optimization of PINNs despite the noise-filtering nature of NNs and additional denoising processes. In this work, we propose a PINN-MREPT model based on a canonical analytic MREPT model. A reference padding layer with known EPs was added to surround the region of interest for providing additive collocation points. Moreover, an optimizable diffusion coefficient was embedded in the analytic MREPT model used in the PINN-MREPT. The noise robustness of the proposed PINN-MREPT for single-sample reconstruction was tested by using numerical phantoms of human brain with extra tumor-like tissues at different noise levels. The results of numerical experiments show that PINN-MREPT outperforms two typical numerical MREPT methods in terms of reconstruction accuracy, sensitivity to the extra tissues, and the correlations of line profiles in the regions of interest. The advantage of the PINN-MREPT is shown by the results of an experiment on phantom measurement, too. Moreover, it is found that the diffusion term plays an important role to achieve a noise-robust PINN-MREPT. This is an important step moving forward to a clinical application of MREPT.

Low-cost and portable magnetic resonance imaging (MRI) may make this imaging modality more accessible. Permanent-magnet-array is an option to supply a static magnetic field (B-field) with portability, low cost, and no power consumption. However, it has low field strength. Moreover, it does not have linear gradients, thus the signals and the images are not linked by the Fourier transformation as they are in a conventional system. The B-field generated by an array and called spatial-encoding-magnetic-field (SEM), is spatially non-linear and always on. Such an SEM, in terms of the field strength, direction, homogeneity, pattern and its field pattern variation, is related to the image quality. This relation is crucial because it can be used to guide the magnet and system design for high image quality and portability. However, it has not been systematically studied. In this paper, the characteristics of the SEMs from different magnet array designs are identified. Due to the non-linearity of the SEMs, local structural similarity (SSIM) index is proposed to evaluate the region-dependent image quality, and local k-space is applied to analyze the region-dependent effects of these SEMs on image reconstruction. Moreover, point spread function is applied to analyze the overall effect of the SEMs on the quality of reconstructed images. Besides the intrinsic effects of the SEMs, those of the external factors, e.g. the receive coil sensitivity, are analyzed. This study identifies the unique characteristics of the SEMs in a permanent-magnet-array-based MRI system, and offers methods to analyze the unique relation between the image quality and the field. It can not only guide the magnet designs but also trigger more design ideas, e.g., the design of the mechanical movement of the magnet array, and that of the static magnetic field shimming coils, paving the way towards a low-field MRI system with practical portability.

Abstract Background Cancer-associated fibroblasts (CAFs), one of the principal constituents of the tumor microenvironment, have a pivotal role in tumor progression. Dysregulation of microRNAs (miRNAs) in CAFs contributes to the tumor-promoting ability of CAFs. However, the mechanism underlying the involvement of miRNAs in CAFs of gastric cancer (GC) is not fully understood. This study aimed to explore the effects of miRNA-214 in CAFs on GC migration and invasion. Methods The primary CAFs and corresponding normal fibroblasts (NFs) were isolated. Cell counting kit-8, EdU cell proliferation staining and Transwell assays were used to determine the role of miRNA-214 in GC progression. Real-time polymerase chain reaction, Western blot analysis, and dual-luciferase reporter assay were performed to verify the target genes of miRNA-214. Immunofluorescence and Western blot analysis were applied to detect the expression of epithelial–mesenchymal transition (EMT) markers. Immunohistochemistry and in situ hybridization were implemented to analyze the fibroblast growth factor 9 (FGF9) and miRNA-214 expression in human GC tissues, respectively. Finally, to assess its prognostic relevance, Kaplan–Meier survival analysis was conducted. Results MiRNA-214 was significantly downregulated in CAFs of GC compared with NFs. The upregulation of miRNA-214 in CAFs inhibited GC cell migration and invasion in vitro but failed to affect proliferation. Moreover, GC cells cultured with conditioned medium from CAFs transfected with miR-214 mimic showed increased expression of E-cadherin and decreased expression of Vimentin, N-cadherin and Snail, indicating the suppression of EMT of GC cells. Furthermore, FGF9 was proved to be a direct target gene of miR-214. The expression of FGF9 was higher in CAFs than that in tumor cells not only in primary tumor but also in lymph node metastatic sites (30.0% vs 11.9%, P

Soft pneumatic actuators used in robotic rehabilitation gloves are classified into two types: whole-finger actuators with air chambers that cover the entire finger and modular actuators with chambers only above the finger joints. Most existing prototypes provide enough finger flexion support, but insufficient independent thumb abduction or opposition support. Even the latest modular soft actuator realized thumb abduction with a sacrifice of range of motion (RoM). Moreover, the advantages and disadvantages of using the two types of soft actuators for thumb assistance have not been made clear. Without an efficient thumb assist, patients’ options for hand function rehabilitation are very limited. Therefore, the objective of this study was to design a modular actuator (M-ACT) that could support multiple degrees of freedom, compare it with a whole-finger type of thumb actuator with three inner chambers (3C-ACT) in terms of the RoM, force output of thumb flexion, and abduction, and use an enhanced Kapandji test to measure both the kinematic aspect of the thumb (Kapandji score) and thumb-tip pinch force. Our results indicated superior single-DoF support capability of the M-ACT and superior multi-DoF support capability of the 3C-ACT. The use of the 3C-ACT as the thumb actuator and the M-ACT as the four-finger actuator may be the optimal solution for the soft robotic glove. This study will aid in the progression of soft robotic gloves for hand rehabilitation towards real rehabilitation practice.

Applying soft actuators to hand motion assist for rehabilitation has been receiving increasing interest in recent years. Pioneering research efforts have shown the feasibility of soft rehabilitation gloves (SRGs). However, one important and practical issue, the effects of users’ individual differences in finger size and joint stiffness on both bending performance (e.g., Range of motion (ROM) and torque) and the mechanical loads applied to finger joints when the actuators are placed on a patient’s hand, has not been well investigated. Moreover, the design considerations of SRGs for individual users, considering individual differences, have not been addressed. These, along with the inherent safety of soft actuators, should be investigated carefully before the practical use of SRGs. This work aimed to clarify the effects of individual differences on the actuator’s performance through a series of experiments using dummy fingers designed with individualized parameters. Two types of fiber-reinforced soft actuators, the modular type for assisting each joint and conventional (whole-finger assist) type, were designed and compared. It was found that the modular soft actuators respond better to individual differences set in the experiment and exhibit a superior performance to the conventional ones. By suitable connectors and air pressure, the modular soft actuators could cope with the individual differences with minimal effort. The effects of the individualized parameters are discussed, and design considerations are extracted and summarized. This study will play an important role in pushing forward the SRGs to real rehabilitation practice.

Reconstruction of a hand's motion with electroencephalography (EEG) signals is a challenging problem that has not been solved yet. Most related studies rely on a motion tracking system to record a sequence of hand coordinate values paired with biosignals, in order to train a mapping function between them. For amputees, this approach is not possible. There are also only a few studies about how different training techniques may affect the accuracy of a motion reconstruction system. A virtual avatar for presenting different upper limb motions was developed. Subjects were asked to follow the avatar's motion, while the subject's EEG and electromyography (EMG) signals were recorded and paired with avatar's hand trajectory values. This task was performed under three conditions: repeating the motion by memory, repeating the motion while watching it on a screen, and repeating the motion while seeing it in virtual reality (VR). We did not find any significant difference between the three conditions in terms of correlation values. Still, we found that using both EEG and EMG at the same time led to a better result than using only one of them. Additionally, significant differences were found in the EEG activity, suggesting that even if the task (moving the arm) was the same for the three conditions, the brain dynamics were different. Specifically, we found that using the VR resulted in a higher alpha desynchronization during the motion. Finally, our results, when only EEG signals were used, were comparable with other studies that have used a motion tracking system.

The VraSR two-component system is a vancomycin resistance-associated sensor/regulator that is upregulated in vancomycin-intermediate Staphylococcus aureus (VISA) and heterogeneous VISA (hVISA) strains. VISA/hVISA show reduced susceptibility to vancomycin and an increased ability to evade host immune responses, resulting in enhanced clinical persistence. However, the underlying mechanism remains unclear. Recent studies have reported that S. aureus strains have developed some strategies to survive within the host cell by using autophagy processes. In this study, we confirmed that clinical isolates with high vraR expression showed increased survival in murine macrophage-like RAW264.7 cells. We constructed isogenic vraSR deletion strain Mu3ΔvraSR and vraSR-complemented strain Mu3ΔvraSR-C to ascertain whether S. aureus uses the VraSR system to modulate autophagy for increasing intracellular survival in RAW264.7. Overall, the survival of Mu3ΔvraSR in RAW264.7 cells was reduced at all infection time points compared with that of the Mu3 wild-type strain. Mu3ΔvraSR-infected RAW264.7 cells also showed decreased transcription of autophagy-related genes Becn1 and Atg5, decreased LC3-II turnover and increased p62 degradation, and fewer visible punctate LC3 structures. In addition, we found that inhibition of autophagic flux significantly increased the survival of Mu3ΔvraSR in RAW264.7 cells. Together, these results demonstrate that S. aureus uses the VraSR system to modulate host-cell autophagy processes for increasing its own survival within macrophages. Our study provides novel insights into the impact of VraSR on bacterial infection and will help to further elucidate the relationship between bacteria and the host immune response. Moreover, understanding the autophagic pathway in vraSR associated immunity has potentially important implications for preventing or treating VISA/hVISA infection.

Point-of-care magnetic resonance imaging (MRI) requires clear images within a short scanning time, a small footprint of the scanner, and relatively low memory required for image reconstruction. A permanent magnet array (PMA)-based MRI system is a good candidate to supply a magnetic field due to its compactness and low power consumption. However, it has relatively inhomogeneous magnetic field and thus non-linear gradients, which results in location-dependent k-spaces (so called local k-spaces) and uneven signal point populations in the local k-spaces, compromising the image quality. Moreover, owing to the non-linearity, imaging reconstruction using Fourier transform does not work, which leads to an increase in the required computation memory. In this study, in order to improve the image quality, the approaches of compensating the uneven signal point population by increasing the numbers of sampling points or rotation angles are investigated in terms of their impacts on image quality improvement, acquisition time, image reconstruction time, and memory consumption. Both methods give a significant improvement on image image quality although they result in a large and dense encoding matrix and thus a large memory consumption. To lower the memory consumption, it is further proposed to transform such a matrix to frequency domain where the matrix could be sparse. Moreover, a row-wise truncation to the transformed encoding matrix is applied to further reduce the memory consumption. Through the results of numerical experiments, it is shown that the required memory for calculation can effectively be reduced by 71.6% while the image becomes clearer by increasing the number of sampling point and/or the number of rotation angles. With the successful demonstration where improved image quality and a lowered memory required can be obtained simultaneously, the proposed study is one step forward for a PMA-based MRI system towards its targeted point-of-care application scenario.

Variability in individual pain sensitivity is a major problem in pain assessment. There have been studies reported using pain-event related potential (pain-ERP) for evaluating pain perception. However, none of them has achieved high accuracy in estimating multiple pain perception levels. A major reason lies in the lack of investigation of feature extraction. The goal of this study is to assess four different pain perception levels through classification of pain-ERP, elicited by transcutaneous electrical stimulation on healthy subjects. Nonlinear methods: Higuchi’s fractal dimension, Grassberger-Procaccia correlation dimension, with auto-correlation, and moving variance functions were introduced into the feature extraction. Fisher score was used to select the most discriminative channels and features. As a result, the correlation dimension with a moving variance without channel selection achieved the best accuracies of 100% for both the two-level and the three-level classification but degraded to 75% for the four-level classification. The best combined feature group is the variance-based one, which achieved accuracy of 87.5% and 100% for the four-level and three-level classification, respectively. Moreover, the features extracted from less than 20 trials could not achieve sensible accuracy, which makes it difficult for an instantaneous pain perception levels evaluation. These results show strong evidence on the possibility of objective pain assessment using nonlinear feature-based classification of pain-ERP.

Predicting a hand’s position using only biosignals is a complex problem that has not been completely solved. The only reliable solutions currently available require invasive surgery. The attempts using non-invasive technologies are rare, and usually have led to lower correlation values between the real and the reconstructed position than those required for real-world applications. In this study, we propose a solution for reconstructing the hand’s position in three dimensions using EEG and EMG to detect from the shoulder area. This approach would be valid for most trans-humeral amputees. In order to find the best solution, we tested four different architectures for the system based on artificial neural networks. Our results show that it is possible to reconstruct the hand’s motion trajectory with a correlation value up to 0.809 compared to a typical value in the literature of 0.6. We also demonstrated that both EEG and EMG contribute jointly to the motion reconstruction. Furthermore, we discovered that the system architectures do not change the results radically. In addition, our results suggest that different motions may have different brain activity patterns that could be detected through EEG. Finally, we suggest a method to study non-linear relations in the brain through the EEG signals, which may lead to a more accurate system.

In developing a shoulder prosthesis, in addition to appropriate payload and range of motion under the constraints of weight and shape, impact absorption is very important for safe use. Hybridization of two different actuators (pneumatic elastic actuators with the features of lightness and intrinsic visco-elasticity, and servo motors that have stable torque and a large range of motion in combination with an antagonistic mechanism) was employed to achieve the development of the shoulder prosthesis. A two-link, two-degree-of-freedom arm was used to test the different hybridization configurations in order to investigate the impact absorption. A dynamic simulation platform based on four bimanual activities of daily living was established to obtain the required range of motion and torque for joints of a two-link, four-degree-of-freedom arm. The number of pneumatic elastic actuators required and the dimension of the antagonistic mechanism mechanical structures were optimized using the dynamic simulation platform. The best configuration of the two types of actuators was determined using the dynamic simulation based on the impact absorption results and other criteria. Moreover, a simplified prototype driven by hybrid actuation was made. It was shown that the pneumatic elastic actuator joint could improve impact absorption, and the actuator configuration of shoulder prostheses is activity of daily living dependent. The prototype could reproduce a certain activity of daily living motion, indicating its feasibility in daily living.

Fiber-reinforced fluid-driven elastomer actuators have enabled the production of simple, low-cost and safe hand rehabilitation devices. However, so far, the actuators support only finger flexion-extension, and little has been reported on abduction-adduction, which is essential for manipulation tasks and grasping larger objects. The technical design difficulty of realizing abduction-adduction lies in the suppression of interference effects between the metacarpophalangeal (MCP) joint’s two orthogonal motion axes, caused by the necessary multi-chamber actuator structure and its reinforcements, under strong spatial constraints. This problem has not been solved yet, regardless of research efforts on designing various actuator structures. In this study, our goal was to enable flexion of all three finger joints and abduction-adduction of the MCP joint, while minimizing the interference and realizing required ranges of motion. For this, we propose two new types of fiber reinforcements (separate single loops and two-directional hitching) and their combination to direct a multi-chamber structure’s expansion and strengthen its force output into the wanted directions. The reinforcements’ effects on actuator response were evaluated by attaching prototypes to a dummy finger and measuring its range of motion and related joint torques and forces. Results showed that the single loops provided length extension, while the hitching constrained it from the bottom at the centerline and strengthened flexion. When combined, they could be used to adjust the amount of length extension and flexion along the actuator, without detrimentally affecting the flexion or abduction-adduction functions. In conclusion, the two new reinforcement types have the potential of being a major design factor for fitting the actuators’ response for different users’ finger kinematics.

Most walking assist systems reported are not available for real world environments where frequent perturbations are caused by slips, uneven terrain, slopes and obstacles. It is evident that humans are able to cope with such perturbations with reflexes that cause unconscious, relatively fixed muscular response patterns to perturbations within a short period of time. In our previous study, we showed that artificial reflexes could improve the perturbation resistance for simulated walkers, though the roles of different reflexive mechanisms were not quantitatively clarified. In this study, we focused on the different roles of reflexive muscle responses and the CPG phase modulation mechanism. By proposing and evaluating two stability criteria through a series of simulation experiments, we revealed different roles for two mechanisms in the simulated walkers. These will not only further increase the possibility of realising artificial reflexes for paralysed individuals, but also bring new insights into the field of motor control.

Transhumeral and shoulder disarticulation amputees find it difficult to move their prostheses for goal-oriented movement using only their small residual limbs. Thus, spatial accessibility is especially important for shoulder prostheses. Moreover, because responding to external disturbances and absorbing impact using only the viscoelasticity and flexibility of the small residual limb is difficult, the intrinsic viscoelasticity of the shoulder prosthesis is indispensable for safety. In our previous work, we proposed a small pneumatic elastic actuator-driven parallel link mechanism for shoulder prostheses. In this paper, we propose two new devices, a sliding antagonistic mechanism and a soft backbone, to improve the spatial characteristics and disturbance responsiveness. We quantitatively evaluated a prosthetic arm with the two devices. The results showed that the two devices increased the arm's workspace and disturbance responsiveness.

Modern assistive devices are very sophisticated systems with multiple degrees of freedom. However, an effective and user-friendly control of these systems is still an open problem since conventional human-machine interfaces (HMI) cannot easily accommodate the system's complexity. In HMIs, the user is responsible for generating unique patterns of command signals directly triggering the device functions. This approach can be difficult to implement when there are many functions (necessitating many command patterns) and/or the user has a considerable impairment (limited number of available signal sources). In this study, we propose a novel concept for a general-purpose HMI where the controller and the user communicate bidirectionally to select the desired function. The system first presents possible choices to the user via electro-tactile stimulation; the user then acknowledges the desired choice by generating a single command signal. Therefore, the proposed approach simplifies the user communication interface (one signal to generate), decoding (one signal to recognize), and allows selecting from a number of options. To demonstrate the new concept the method was used in one particular application, namely, to implement the control of all the relevant functions in a state of the art commercial prosthetic hand without using any myoelectric channels. We performed experiments in healthy subjects and with one amputee to test the feasibility of the novel approach. The results showed that the performance of the novel HMI concept was comparable or, for some outcome measures, better than the classic myoelectric interfaces. The presented approach has a general applicability and the obtained results point out that it could be used to operate various assistive systems (e.g., prosthesis vs. wheelchair), or it could be integrated into other control schemes (e.g., myoelectric control, brain-machine interfaces) in order to improve the usability of existing low-bandwidth HMIs.

A high-efficiency, easy-to-use input device is not only important for data entry but also for human-computer interaction. To date, there has been little research on input devices with many degrees of freedom (DOF) that can be used by the handicapped. This paper presents the development of an electromyography (EMG)-based input device for forearm amputees. To overcome the difficulties in analysing EMG and realising high DOF from biosignals, the following were integrated: (1) an online learning method to cope with nonlinearity and the individual difference of EMG signals; (2) a smoothing algorithm to deal with noisy recognition results and transition states; and (3) a modified Huffman coding algorithm to generate the optimal code, taking expected error and input efficiency into consideration. Experiments showed the validity of the system and the possibility for development of a quiet, free-posture (no postural restriction) input device with many DOF for users, including forearm amputees.

During recent years, interest has been rising towards developing fluidic fiber-reinforced elastomer actuators for wearable soft robotics used in hand rehabilitation and power-assist. However, they do not enable finger abduction-adduction, which plays an important role in activities of daily living, when grasping larger objects. Furthermore, the developed gloves often do not have separate control of joints, which is important for doing various common rehabilitation motions. The main obstacle for the development of a fully-assisting glove is moving a joint with multiple degrees of freedom. If the functions are built into the same structure, they are naturally coupled and affect each other, which makes them more difficult to design and complex to control than a simple flexion-extension actuator. In this study, we explored the key design elements and fabrication of pneumatic multi-pocket elastomer actuators for a soft rehabilitation glove. The goal was to gain more control over the metacarpophalangeal joint’s response by increasing the degree of actuation. Three main functional designs were tested for achieving both flexion and abduction-adduction. Five prototypes, with four different actuator geometries and four different reinforcement types, were designed and fabricated. They were evaluated by recording their free motion with motion capture and measuring their torque output using a dummy finger. Results showed the strengths and weaknesses of each design in separating the control of the two functions. We discuss the different improvements that are needed in order to make each design plausible for developing an actuator that meets the requirements for full assist of the hand’s motions. In conclusion, we show that it is possible to produce multi-pocket actuators for assisting MCP joint motion in both flexion and abduction-adduction, although coupling between the separate functions is still problematic and should be considered further.

Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.

Human arms undertake most tasks in the activities of daily living (ADLs). When designing shoulder prostheses for high-level upper-limb amputees, we should consider not only how to realize high degrees of freedom under weight and shape constraints but also the user's individual task space in daily life. An appropriate mechanical structure that can make full use of state-of-the-art actuators and a scheme to optimize the structure's configuration to match users' spatial access and manipulability requirements are essential. In our previous research, a small pneumatic-actuator-driven parallel mechanism was studied as a shoulder prosthetic arm. In this paper, a systematic procedure is proposed to design the mechanism for a shoulder prosthesis considering force and spatial accessibility. This procedure includes ADL measurements to obtain the task spaces for individual subjects, indexes to evaluate the force and spatial accessibility and an optimization process based on kinematic and statics models. With this approach, the parallel mechanism was optimized for one important ADL task group, considering the trade-off between its required force and working space. Moreover, it was confirmed that the proposed design procedure could find solutions for various spatial specifications. That is, the approach could be used for individualized shoulder prosthesis design.