Multi-Channel FES Gait Rehabilitation Assistance System Based on Adaptive sEMG Modulation.

Functional electrical stimulation (FES) can be used to stimulate the lower-limb muscles to provide walking assistance to stroke patients. However, the existing surface electromyography (sEMG)-based FES control methods mostly only consider a single muscle with a fixed stimulation intensity and frequency. This study proposes a multi-channel FES gait rehabilitation assistance system based on adaptive myoelectric modulation. The proposed system collects sEMG of the vastus lateralis muscle on the non-affected side to predict the sEMG values of four targeted lower-limb muscles on the affected side using a bidirectional long short-term memory (BILSTM) model. Next, the proposed system modulates the real-time FES output frequency for four targeted muscles based on the predicted sEMG values to provide muscle force compensation. Fifteen healthy subjects were recruited to participate in an offline model-building experiment conducted to evaluate the feasibility of the proposed BILSTM model in predicting the sEMG values. The experimental results showed that the [Formula: see text] value of the best-obtained prediction result reached 0.85 using the BILSTM model, which was significantly higher than that using traditional prediction methods. Moreover, two patients after stroke were recruited in the online assisted-walking experiment to verify the effectiveness of the proposed walking-assistance system. The experimental results showed that the activation of the target muscles of the patients was higher after FES, and the gait movement data were significantly different before and after FES. The proposed system can be effectively applied to walking assistance for stroke patients, and the experimental results can provide new ideas and methods for sEMG-controlled FES rehabilitation applications.

Effects of the Interactive Features of Virtual Partner on Individual Exercise Level and Exercise Perception.

BACKGROUND: We designed an exercise system in which the user is accompanied by a virtual partner (VP) and tested bodyweight squat performance with different interactive VP features to explore the comprehensive impact of these VP features on the individual's exercise level (EL) and exercise perception. METHODS: This experiment used three interactive features of VP, including body movement (BM), eye gaze (EG), and sports performance (SP), as independent variables, and the exercise level (EL), subjective exercise enjoyment, attitude toward the team formed with the VP, and local muscle fatigue degree of the exerciser as observational indicators. We designed a 2 (with or without VP's BM) × 2 (with or without VP's EG) × 2 (with or without VP's SP) within-participants factorial experiment. A total of 40 college students were invited to complete 320 groups of experiments. RESULTS: (1) Regarding EL, the main effects of BM and SP were significant (p < 0.001). The pairwise interaction effects of the three independent variables on EL were all significant (p < 0.05). (2) Regarding exercise perception, the main effects of BM (p < 0.001) and EG (p < 0.001) on subjective exercise enjoyment were significant. The main effect of BM on the attitude toward the sports team formed with the VP was significant (p < 0.001). The interaction effect of BM and SP on the attitude toward the sports team formed with the VP was significant (p < 0.001). (3) Regarding the degree of local muscle fatigue, the main effects of BM, EG, and SP and their interaction effects were not significant (p > 0.05). CONCLUSION: BM and EG from the VP elevate EL and exercise perception during squat exercises, while the VP with SP inhibited the EL and harmed exercise perception. The conclusions of this study can provide references to guide the interactive design of VP-accompanied exercise systems.

Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix.

(1) Objective: The objective of this study was to experimentally obtain the ideal pressure distribution model of buttock and thigh support for office workers in forward-leaning and upright sitting postures, reproduce the support provided by mesh materials with elastic materials, and propose an effective seat design scheme to improve the comfort of office workers. (2) Method: Based on the seven most popular mesh chairs on the market, pressure distribution experiments, and the fuzzy clustering algorithm, the relatively ideal body pressure distribution matrices were generated for office workers under two common sitting postures, and the corresponding partitioned sitting support surfaces were obtained. A prototype chair was created and validated by combining the ergonomics node coordinates and the physical properties of the materials. (3) Result: An ideal support model of four zones was constructed, and prototype pads were designed and produced according to this model. Subjects were recruited to test the ability of the prototypes to reproduce the ideal pressure distribution maps. (4) Conclusion: The four-zone ideal support model is capable of effectively representing the buttock and thigh support requirements in forward-leaning and upright sitting postures, and it is useful for the development of related products. Studying sitting postures and pressure values generated by different activities of office workers will help to refine the needs of office personnel and provide new ideas for the design of office chairs.

Effects of Cavity Thickness on the Replication of Micro Injection Molded Parts with Microstructure Array.

Parts with microstructure arrays have been widely used in biotechnologies and optical technologies, and their performances are affected by replication uniformity. The uniformity of the microstructure is still a challenge in micro-injection molded parts and is greatly affected by the cavity thickness and process parameters. In this study, the replication uniformity of microstructures is experimentally investigated. The relationship between the replication uniformity and cavity thickness was explored through single-factor experiments. Additionally, the impacts of the process parameters on the replication uniformity were also studied through uniform design experiments. A regression equation was established to describe the quantitative relationship between the important parameters and replication uniformity. The results showed that the replication uniformity of microstructures increases by 39.82% between the cavity with the thickness of 0.5 mm and a cavity of 0.7 mm. In addition, holding time is the most significant factor influencing the replication uniformity, followed by mold temperature, melt temperature, and injection speed. It is concluded that the thickness of cavity and the process parameters have significant influence on the replication uniformity. The experimental results provide important data on how to improve the replication uniformity of parts with microstructure arrays.

Research on the Recognition of Various Muscle Fatigue States in Resistance Strength Training.

Instantly and accurately identifying the state of dynamic muscle fatigue in resistance training can help fitness trainers to build a more scientific and reasonable training program. By investigating the isokinetic flexion and extension strength training of the knee joint, this paper tried to extract surface electromyogram (sEMG) features and establish recognition models to classify muscle states of the target muscles in the isokinetic strength training of the knee joint. First, an experiment was carried out to collect the sEMG signals of the target muscles. Second, two nonlinear dynamic indexes, wavelet packet entropy (WPE) and power spectrum entropy (PSE), were extracted from the obtained sEMG signals to verify the feasibility of characterizing muscle fatigue. Third, a convolutional neural network (CNN) recognition model was constructed and trained with the obtained sEMG experimental data to enable the extraction and recognition of EMG deep features. Finally, the CNN recognition model was compared with multiple support vector machines (Multi-SVM) and multiple linear discriminant analysis (Multi-LDA). The results showed that the CNN model had a better classification accuracy. The overall recognition accuracy of the CNN model applied to the test data (91.38%) was higher than that of the other two models, which verified that the CNN dynamic fatigue recognition model based on subjective and objective information feedback had better recognition performance. Furthermore, training on a larger dataset could further improve the recognition accuracy of the CNN recognition model.

A Design Framework of Medical Wayfinding Signs for the Elderly: Based on the Situational Cognitive Commonness.

Older people in China have a poor understanding of hospital signage. To address this problem, in this study, we combined the theories of situated cognition and cognitive commonness in order to introduce the three main factors that affect the generation of situational cognitive commonness: composition of the situation, familiarity, and concreteness. We used these theories to construct a methodological framework for the design of geriatric hospital wayfinding signs that were based on situational cognitive commonness. The design of nine healthcare signs for Chinese national standards were used as examples in the study. First, users who were familiar with medical scenarios were asked to draw concrete cognitive conception graphics for the purposes of individual wayfinding targets from both physical and social situations. Next, we coded and grouped the generated graphics based on their situational features in order to extract groups of representative common graphics. Finally, we reorganized the common graphics and developed concrete designs, which were tested by the judgment test. The wayfinding signs designed according to the methodological framework of this study effectively improved the understanding of hospital signage among older Chinese people. This study took geriatric hospital wayfinding signs as the examples to provide a feasible theoretical basis and research reference for symbol design.

A Study on the Design of Vision Protection Products Based on Children's Visual Fatigue under Online Learning Scenarios.

The rate of myopia in children is increasing rapidly under online learning scenarios. One of the important reasons for this is incorrect reading and writing posture. Three screen view parameters (viewing angle, viewing height, and viewing distance) are selected as significant influencing factors and blink rating is used as a sign of visual fatigue through literature analysis to study the influence factors of myopia in children, and their correlation. Children's visual fatigue is evaluated by subjective evaluation and is recording using an eye tracker for changes in the three factors through online learning scenario simulation experiment. An optimal regression model is constructed that illustrates the relationship between the three variables and the visual fatigue levels. The aim of this study is to confirm the quantitative relationship between the screen view parameters and visual fatigue, and to design a child vision protection product on this basis. The test results show there is a linear positive correlation between the viewing angle, viewing height, and viewing distance. A vision protection device has been designed based on this model and was verified through function prototype testing. The result of this study quantified the relationship among screen view parameters and children's visual fatigue, which provides a theoretical basis for the design of a children's visual protection device.

How Do Older Adults Process Icons in Visual Search Tasks? The Combined Effects of Icon Type and Cognitive Aging.

Considering the differences in cognitive aging among older adults, this study examined how older adults process different types of graphic icons in visual search tasks. Fifty-four medical-related icons, including flat icons (FIs), FIs plus text (FIs + text), skeuomorphic icons (SIs), and SIs plus text (SIs + text), were created. The participants were divided into two groups-cognitively normal (CN) and mild cognitive impairment (MCI)-to complete a visual search task. According to the eye-tracking data of the participants, the search performance of the CN group was significantly better than that of the MCI group. In terms of icon types, all older adults performed better at searching for the combinations of icon and text, especially SI + text, which showed the smallest difference in the search performance between the MCI and CN groups. All older adults performed poorly when searching for FIs. The findings of this study considered the differences in cognitive aging among older adults and provided a useful reference for the icon and interface design of graphical user interfaces.

The Effect of Music Tempo on Fatigue Perception at Different Exercise Intensities.

Background: This study aimed to clarify the effect of music tempo on runners' perception of fatigue at different exercise intensities and while listening to music of different tempos through running experiments. Methods: This study used a within-subject two-factor experimental design with music tempo (fast music, slow music, no music) and exercise intensity (high intensity, low intensity) as independent variables and the time to fatigue perception (TFP), the difference in heart rate (HR) and the difference in the median frequency (MF) of surface electromyography (sEMG) signals as observation indexes. Eighteen participants completed a total of 108 sets of running experiments. Results: (1) The main effect of music tempo on the TFP was significant (p < 0.001). (2) The main effect of exercise intensity on the TFP was significant (p < 0.001), and the main effect on the difference in HR was significant (p < 0.001). (3) The interaction effect of music tempo and exercise intensity on the TFP was significant (p < 0.05). Conclusions: Exercisers' subjective perception of fatigue was affected by music tempo and the interaction between music tempo and exercise intensity, and exercisers' objective fatigue perception was influenced mostly by exercise intensity. The findings of this study provide guidance for runners' choice of music at different intensities of exercise. Whether it is low-intensity exercise or high-intensity exercise, listening to fast music while exercising can help runners perform better mentally and physically during their runs.

Pillow Support Model with Partitioned Matching Based on Body Pressure Distribution Matrix.

(1) Objective: Sleep problems have become one of the current serious public health issues. The purpose of this research was to construct an ideal pressure distribution model for head and neck support through research on the partitioned support surface of a pillow in order to guide the development of ergonomic pillows. (2) Methods: Seven typical memory foam pillows were selected as samples, and six subjects were recruited to carry out a body pressure distribution experiment. The average value of the first 10% of the samples in the comfort evaluation was calculated to obtain the relative ideal body pressure distribution matrix. Fuzzy clustering was performed on the ideal matrix to obtain the support surface partition. The ideal body pressure index of each partition was calculated, and a hierarchical analysis of each partition was then performed to determine the pressure sensitivity weight of each partition. Using these approaches, the key ergonomic node coordinates of the partitions of four different groups of people were extracted. The ergonomic node coordinates and the physical characteristics of the material were used to design a pillow prototype. Five subjects were recruited for each of the four groups to repeat the body pressure distribution experiment to evaluate the pillow prototype. (3) Results: An ideal support model with seven partitions, including three partitions in the supine position and four partitions in the lateral position, was constructed. The ideal body pressure distribution matrix and ideal body pressure indicators and pressure sensitivity weights for each partition were provided. The pillow that was designed and manufactured based on this model reproduced the ideal pressure distribution matrix evaluated by various groups of people. (4) Conclusion: The seven-partition ideal support model can effectively describe the head and neck support requirements of supine and lateral positions, which can provide strong support for the development of related products.

Work-Function-Tunable Electron Transport Layer of Molecule-Capped Metal Oxide for a High-Efficiency and Stable p-i-n Perovskite Solar Cell.

The composite electron transporting layer (ETL) of metal oxide with [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) prevents perovskite from metal electrode erosion and increases p-i-n perovskite solar cell (PVSC) stability. Although the oxide exhibits protective function, an additional work function modifier is still needed for good device performance. Usually, complicated multistep synthesis is employed to have a highly crystalline film that increases manufacturing cost and inhibits scalability. We report a facile synthesis of a novel organic-molecule-capped metal oxide nanoparticle film for the composite ETL. The nanoparticle film not only has a dual function of electron transport and protection but also exhibits work function tunability. Solvothermal-prepared SnO2 nanoparticles are capped with tetrabutylammonium hydroxide (TBAOH) through ligand exchange. The resulting TBAOH-SnO2 nanoparticles disperse well in ethanol and form a uniform film on PCBM. The power conversion efficiency of the device dramatically increases from 14.91 to 18.77% using this layer because of reduced charge accumulation and aligned band structure. The PVSC thermal stability is significantly enhanced by adopting this layer, which prevents migration of I- and Ag. The ligand exchange method extends to other metal oxides, such as TiO2, ITO, and CeO2, demonstrating its broad applicability. These results provide a cornerstone for large-scale manufacture of high-performance and stable PVSCs.

Rapid template-free synthesis of nanostructured conducting polymer films by tuning their morphology using hyperbranched polymer additives.

Nanostructures in conducting polymer films can enhance charge carrier and ion transfer, provide porosity with high specific area and confer unique optoelectronic properties for potential applications. A general and facile synthesis has been developed to prepare nanostructured conducting polymer films without the need for using templates. This simple approach employs hyperbranched polymers as additives to tune the morphology of conducting polymer films into a continuous nanofibril network. Nanostructured conducting polymer films with improved crystallinity exhibit good charge carrier transport and stable nanofibril network, without sacrificing either property upon removing residual additives. Polymer field-effect transistor sensors have been used to demonstrate the benefits of the large surface area provided by the nanofibril network. The sensors with porous nanostructures exhibit lower detection limits (two times lower) and faster response times (33% faster) compared to the sensors without nanostructures. This general approach can advance the knowledge and development of nanostructured conducting polymer films for energy harvesting and storage, electronics, catalysts, sensors and biomedical applications.

Highly Conductive 2D Metal-Organic Framework Thin Film Fabricated by Liquid-Liquid Interfacial Reaction Using One-Pot-Synthesized Benzenehexathiol.

Metal-organic frameworks (MOF) are studied extensively in applications like catalysts, gas storage, and sensors due to their various functional groups and structures. Two-dimensional (2D) MOFs such as triphenylene-based materials show excellent charge transport properties, but thin-film fabrication and organic ligand synthesis are difficult. In this work, we synthesize thiol-based organic ligand, benzenehexathiol (BHT), by a simple one-pot reaction. This facile method is safer and faster than conventional synthesis procedure that requires using liquid ammonia as solvent. Two novel 2D MOF materials, Ag3BHT2 and Au3BHT2, are fabricated by coordinating BHT with either silver (Ag) or gold (Au) ions through liquid-liquid interfacial reaction. The Ag3BHT2 thin film reaches a high electrical conductivity of 363 S cm-1, which has potential applications in electronic devices and sensors.

Improved Solar-Driven Photocatalytic Performance of Highly Crystalline Hydrogenated TiO2 Nanofibers with Core-Shell Structure.

Hydrogenated titanium dioxide has attracted intensive research interests in pollutant removal applications due to its high photocatalytic activity. Herein, we demonstrate hydrogenated TiO2 nanofibers (H:TiO2 NFs) with a core-shell structure prepared by the hydrothermal synthesis and subsequent heat treatment in hydrogen flow. H:TiO2 NFs has excellent solar light absorption and photogenerated charge formation behavior as confirmed by optical absorbance, photo-Kelvin force probe microscopy and photoinduced charge carrier dynamics analyses. Photodegradation of various organic dyes such as methyl orange, rhodamine 6G and brilliant green is shown to take place with significantly higher rates on our novel catalyst than on pristine TiO2 nanofibers and commercial nanoparticle based photocatalytic materials, which is attributed to surface defects (oxygen vacancy and Ti3+ interstitial defect) on the hydrogen treated surface. We propose three properties/mechanisms responsible for the enhanced photocatalytic activity, which are: (1) improved absorbance allowing for increased exciton generation, (2) highly crystalline anatase TiO2 that promotes fast charge transport rate, and (3) decreased charge recombination caused by the nanoscopic Schottky junctions at the interface of pristine core and hydrogenated shell thus promoting long-life surface charges. The developed H:TiO2 NFs can be helpful for future high performance photocatalysts in environmental applications.

Conjugated polymer/nanoparticles nanocomposites for high efficient and real-time volatile organic compounds sensors.

The present work demonstrates a high efficient and low cost volatile organic compounds (VOCs) sensor. Nowadays, VOCs, which are typically toxic, explosive, flammable, and an environmental hazard, are extensively used in R&D laboratories and industrial productions. Real-time and accurately monitoring the presence of harmful VOC during the usage, storage, or transport of VOCs is extremely important which protects humans and the environment from exposure in case of an accident and leakage of VOCs. The present work utilizes conducting polymer/nanoparticles blends to sense various VOCs by detecting the variation of optical properties. The novel sensor features high sensitivity, high accuracy, quick response, and very low cost. Furthermore, it is easy to fabricate into a sensing chip and can be equipped anywhere such as a laboratory or a factory where the VOCs are either used or produced and on each joint between transporting pipes or each switch of VOC storage tanks. Real-time sensing is achievable on the basis of the instant response to VOC concentrations of explosive limits. Therefore, an alarm can be delivered within a few minutes for in time remedies. This research starts from investigating fundamental properties, processing adjustments, and a performance test and finally extends to real device fabrication that practically performs the sensing capability. The demonstrated results significantly advance the current sensor technology and are promising in commercial validity in the near future for human and environmental safety concerns against hazardous VOCs.