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Highlights This article summarizes the recent advances in wireless, batteryless, implantable electronics for continuous physiological monitoring. The critical factors that affect the design of implantable electronics for biosensing are discussed. The recent progress of material research for developing various implantable devices is summarized. This article reviews various biomedical applications of implantable devices for human healthcare.

Abstract Unlike ballistic arm movements such as reaching, the contribution of depth information to the performance of manual tracking movements is unclear. Thus, to understand how the brain handles information, we investigated how a required movement along the depth axis would affect behavioral tracking performance, postulating that it would be affected by the amount of depth movement. We designed a visually guided planar tracking task that requires movement on three planes with different depths: a fronto-parallel plane called ROT (0), a sagittal plane called ROT (90), and a plane rotated by 45° with respect to the sagittal plane called ROT (45). Fifteen participants performed a circular manual tracking task under binocular and monocular visions in a three-dimensional (3D) virtual reality space. As a result, under binocular vision, ROT (90), which required the largest depth movement among the tasks, showed the greatest error in 3D. Similarly, the errors (deviation from the target path) on the depth axis revealed significant differences among the tasks. Under monocular vision, significant differences in errors were observed only on the lateral axis. Moreover, we observed that the errors in the lateral and depth axes were proportional to the required movement on these axes under binocular vision and confirmed that the required depth movement under binocular vision determined depth error independent of the other axes. This finding implies that the brain may independently process binocular vision information on each axis. Meanwhile, the required depth movement under monocular vision was independent of performance along the depth axis, indicating an intractable behavior. Our findings highlight the importance of handling depth movement, especially when a virtual reality situation, involving tracking tasks, is generated.

Low-temperature additive manufacturing of magnesium (Mg) alloy implants is considered a promising technique for biomedical applications due to Mg’s inherent biocompatibility and 3D printing’s capability for patient-specific design. This study explores the influence of powder volume content, size, and morphology on the mechanical properties and viscosity of polylactic acid (PLA) matrix composite filaments containing in-house-produced magnesium–calcium (Mg-Ca) particles, with a focus on their application towards low-temperature additive manufacturing. We investigated the effects of varying the Mg-Ca particle content in a PLA matrix, revealing a direct correlation between volume content and bending strength. Particle size analysis demonstrated that smaller particles (D50: 57 μm) achieved a bending strength of 63.7 MPa, whereas larger particles (D50: 105 μm) exhibited 49.6 MPa at 20 vol.%. Morphologically, the filament containing spherical particles at 20 vol.% showed a bending strength that was 11.5 MPa higher than that of the filament with irregular particles. These findings highlight the critical role of particle content, size, and shape in determining the mechanical and rheological properties of Mg-Ca/PLA composite filaments for use in material extrusion additive manufacturing.

Abstract Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information. The physical effort represents the work hardness used to optimize wearable robotic systems. Thus, personalization and rapid optimization of the effort are critical. Although respirometry is the gold standard for estimating metabolic costs, this method requires a heavy, bulky, and rigid system, limiting the system’s field deployability. Here, this paper reports a soft, flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton, used to estimate metabolic costs and physical effort, demonstrating the potential for real-time wearable robot adjustments based on biofeedback. Data from a set of activities, including walking, running, and squatting with the biopatch and exoskeleton, determines the relationship between metabolic costs and heart rate variability root mean square of successive differences (HRV-RMSSD) (R = −0.758). Collectively, the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.

Independent component analysis (ICA) has been widely used for electroencephalography (EEG) analyses. However, ICA performance relies on several crucial assumptions about the data. Here, we focus on the granularity of data rank, i.e., the number of linearly independent EEG channels. When the data are rank-full (i.e., all channels are independent), ICA produces as many independent components (ICs) as the number of input channels (rank-full decomposition). However, when the input data are rank-deficient, as is the case with bridged or interpolated electrodes, ICA produces the same number of ICs as the data rank (forced rank deficiency decomposition), introducing undesired ghost ICs and indicating a bug in ICA. We demonstrated that the ghost ICs have white noise properties, in both time and frequency domains, while maintaining surprisingly typical scalp topographies, and can therefore be easily missed by EEG researchers and affect findings in unknown ways. This problem occurs when the minimum eigenvalue λmin of the input data is smaller than a certain threshold, leading to matrix inversion failure as if the rank-deficient inversion was forced, even if the data rank is cleanly deficient by one. We defined this problem as the effective rank deficiency. Using sound file mixing simulations, we first demonstrated the effective rank deficiency problem and determined that the critical threshold for λmin is 10−7 in the given situation. Second, we used empirical EEG data to show how two preprocessing stages, re-referencing to average without including the initial reference and non-linear electrode interpolation, caused this forced rank deficiency problem. Finally, we showed that the effective rank deficiency problem can be solved by using the identified threshold (λmin = 10−7) and the correct re-referencing procedure described herein. The former ensures the achievement of effective rank-full decomposition by properly reducing the input data rank, and the latter allows avoidance of a widely practiced incorrect re-referencing approach. Based on the current literature, we discuss the ambiguous status of the initial reference electrode when re-referencing. We have made our data and code available to facilitate the implementation of our recommendations by the EEG community.

Although several previous studies on laterality of upper limb motor control have reported functional differences, this conclusion has not been agreed upon. It may be conjectured that the inconsistent results were caused because upper limb motor control was observed in multi-joint tasks that could generate different inter-joint motor coordination for each arm. Resolving this, we employed a single wrist joint tracking task to reduce the effect of multi-joint dynamics and examined the differences between the dominant and non-dominant hands in terms of motor control. Specifically, we defined two sections to induce feedback (FB) and feedforward (FF) controls: the first section involved a visible target for FB control, and the other section involved an invisible target for FF control. We examined the differences in the position errors of the tracer and the target. Fourteen healthy participants performed the task. As a result, we found that during FB control, the dominant hand performed better than the non-dominant hand, while we did not observe significant differences in FF control. In other words, in a single-joint movement that is not under the influence of the multi-joint coordination, only FB control showed laterality and not FF control. Furthermore, we confirmed that the dominant hand outperformed the non-dominant hand in terms of responding to situations that required a change in control strategy.

Full-body motion capture is essential for the study of body movement. Video-based, markerless, mocap systems are, in some cases, replacing marker-based systems, but hybrid systems are less explored. We develop methods for coregistration between 2D video and 3D marker positions when precise spatial relationships are not known a priori. We illustrate these methods on three-ball cascade juggling in which it was not possible to use marker-based tracking of the balls, and no tracking of the hands was possible due to occlusion. Using recorded video and motion capture, we aimed to transform 2D ball coordinates into 3D body space as well as recover details of hand motion. We proposed four linear coregistration methods that differ in how they optimize ball-motion constraints during hold and flight phases, using an initial estimate of hand position based on arm and wrist markers. We found that minimizing the error between ball and hand estimate was globally suboptimal, distorting ball flight trajectories. The best-performing method used gravitational constraints to transform vertical coordinates and ball-hold constraints to transform lateral coordinates. This method enabled an accurate description of ball flight as well as a reconstruction of wrist movements. We discuss these findings in the broader context of video/motion capture coregistration.

Realizing an artificial camouflage device with a high spatial resolution by adapting to the surrounding environment in real-time is a challenging task, mainly associated with device fabrication and integration with sensor and control circuits. To overcome these limitations, the authors utilize thermochromic liquid crystal ink that reacts to the feedback control system of the vertically stacked silver nanowire heater.

This study addresses time intervals during robot control that dominate user satisfaction and factors of robot movement that induce satisfaction. We designed a robot control system using electromyography signals. In each trial, participants were exposed to different experiences as the cutoff frequencies of a low-pass filter were changed. The participants attempted to grab a bottle by controlling a robot. They were asked to evaluate four indicators (stability, imitation, response time, and movement speed) and indicate their satisfaction at the end of each trial by completing a questionnaire. The electroencephalography signals of the participants were recorded while they controlled the robot and responded to the questionnaire. Two independent component clusters in the precuneus and postcentral gyrus were the most sensitive to subjective evaluations. For the moment that dominated satisfaction, we observed that brain activity exhibited significant differences in satisfaction not immediately after feeding an input but during the later stage. The other indicators exhibited independently significant patterns in event-related spectral perturbations. Comparing these indicators in a low-frequency band related to the satisfaction with imitation and movement speed, which had significant differences, revealed that imitation covered significant intervals in satisfaction. This implies that imitation was the most important contributing factor among the four indicators. Our results reveal that regardless of subjective satisfaction, objective performance evaluation might more fully reflect user satisfaction.

In various experimental settings, electromyography (EMG) signals have been used to control robots. EMG-based robot control requires intrinsic parameters for control, which makes it difficult for users to understand the input protocol. When a proper input is not provided, the response time of the system varies; as such, the user’s subjective delay should be investigated regardless of the actual delay. In this study, we investigated the influence of the subjective perception of delay on brain activation. Brain recordings were taken while subjects used EMG signals to control a robot hand, which requires a basic processing delay. We used muscle synergy for the grip command of the robot hand. After controlling the robot by grasping their hand, one of four additional delay durations (0 ms, 50 ms, 125 ms, and 250 ms) was applied in every trial, and subjects were instructed to answer whether the delay was natural, additional, or whether they were not sure. We compared brain activity based on responses (“sure” and “not sure”). Our results revealed a significant power difference in the theta band of the parietal lobe, and this time range included the interval in which the subjects could not feel the delay. Our study provides important insights that should be considered when constructing an adaptive system and evaluating its usability.

Background/Aims This study was conducted to evaluate the recent prevalence and trend of anti-tuberculosis (TB) drug resistance with a focus on multidrug-resistance (MDR) and fluoroquinolone resistance in South Korea. Methods We retrospectively reviewed the drug susceptibility testing results of culture-confirmed Mycobacterium tuberculosis isolates collected from 2010 to 2014 at seven tertiary hospitals in South Korea. Results A total of 5,599 cases were included: 4,927 (88.0%) were new cases and 672 (12.0%) were previously treated cases. The MDR rate has significantly decreased from 6.0% in 2010 to 3.0% in 2014 among new cases, and from 28.6% in 2010 to 18.4% in 2014 among previously treated cases (p < 0.001 and p = 0.027, respectively). The resistance rate to any fluoroquinolone was 0.8% (43/5,221) in non-MDR-TB patients, as compared to 26.2% (99/378) in MDR-TB patients (p < 0.001). There was no significant change in the trend of fluoroquinolone resistance among both nonMDR-TB and MDR-TB patients. Among the 43 non-MDR-TB patients with fluoroquinolone resistance, 38 (88.4%) had fluoroquinolone mono-resistant isolates. Conclusions The prevalence of MDR-TB has significantly decreased from 2010 to 2014. The prevalence of fluoroquinolone resistance among non-MDR-TB patients was low, but the existence of fluoroquinolone mono-resistant TB may be a warning on the widespread use of fluoroquinolone in the community.

This article focuses on the development of polylactic acid– (PLA-) based thermoplastic composite filament for its use, once 3D printed via thermoplastic material extrusion (TME), as current collector at the negative electrode side of a lithium-ion battery or sodium-ion battery. High electronic conductivity is achieved through the introduction of Ag-coated Cu charges, while appropriate mechanical performance to allow printability was maintained through the incorporation of poly(ethylene glycol) dimethyl ether average Mn ∼ 500 (PEGDME500) as a plasticizer into the PLA polymer matrix. Herein, thermal, electrical, morphological, electrochemical, and printability characteristics are discussed thoroughly. While Ag-Li alloy formation is reported at 0.1V upon cycling, its use with active materials such as Li4Ti5O12 (LTO) or Li2-terephthalate (Li2TP) operating at a plateau at higher potential is demonstrated. Furthermore, its ability to be used with negative electrode active material of sodium-ion battery technology in a wide potential window is demonstrated.

Electrophysiology signals are crucial health status indicators as they are related to all human activities. Current demands for mobile healthcare have driven considerable interest in developing skin-mounted electrodes for health monitoring. Silver-Silver chloride-based (Ag-/AgCl) wet electrodes, commonly used in conventional clinical practice, provide excellent signal quality, but cannot monitor long-term signals due to gel evaporation and skin irritation. Therefore, the focus has shifted to developing dry electrodes that can operate without gels and extra adhesives. Compared to conventional wet electrodes, dry ones offer various advantages in terms of ease of use, long-term stability, and biocompatibility. This review outlines a systematic summary of the latest research on high-performance soft and dry electrodes. In addition, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, strategies to promote physical adhesion, methods for higher breathability, and their applications in wearable biomedical devices. Finally, we discuss the developmental challenges and advantages of various dry electrodes, while suggesting research directions for future studies.

The utility of premovement electroencephalography (EEG) for decoding movement intention during a reaching task has been demonstrated. However, the kind of information the brain represents regarding the intended target during movement preparation remains unknown. In the present study, we investigated which movement parameters (i.e., direction, distance, and positions for reaching) can be decoded in premovement EEG decoding. Eight participants performed 30 types of reaching movements that consisted of 1 of 24 movement directions, 7 movement distances, 5 horizontal target positions, and 5 vertical target positions. Event-related spectral perturbations were extracted using independent components, some of which were selected via an analysis of variance for further binary classification analysis using a support vector machine. When each parameter was used for class labeling, all possible binary classifications were performed. Classification accuracies for direction and distance were significantly higher than chance level, although no significant differences were observed for position. For the classification in which each movement was considered as a different class, the parameters comprising two vectors representing each movement were analyzed. In this case, classification accuracies were high when differences in distance were high, the sum of distances was high, angular differences were large, and differences in the target positions were high. The findings further revealed that direction and distance may provide the largest contributions to movement. In addition, regardless of the parameter, useful features for classification are easily found over the parietal and occipital areas.

Many previous studies on brain-machine interfaces (BMIs) have focused on electroencephalography (EEG) signals elicited during motor-command execution to generate device commands. However, exploiting pre-execution brain activity related to movement intention could improve the practical applicability of BMIs. Therefore, in this study we investigated whether EEG signals occurring before movement execution could be used to classify movement intention. Six subjects performed reaching tasks that required them to move a cursor to one of four targets distributed horizontally and vertically from the center. Using independent components of EEG acquired during a premovement phase, two-class classifications were performed for left vs. right trials and top vs. bottom trials using a support vector machine. Instructions were presented visually (test) and aurally (condition). In the test condition, accuracy for a single window was about 75%, and it increased to 85% in classification using two windows. In the control condition, accuracy for a single window was about 73%, and it increased to 80% in classification using two windows. Classification results showed that a combination of two windows from different time intervals during the premovement phase improved classification performance in the both conditions compared to a single window classification. By categorizing the independent components according to spatial pattern, we found that information depending on the modality can improve classification performance. We confirmed that EEG signals occurring during movement preparation can be used to control a BMI.

Several antimicrobial peptides (AMPs) have been discovered, developed, and purified from natural sources and peptide engineering; however, the clinical applications of these AMPs are limited owing to their lack of abundance and side effects related to cytotoxicity, immunogenicity, and hemolytic activity. Accordingly, to improve cell selectivity for pseudin-2, an AMP from Pseudis paradoxa skin, in mammalian cells and pathogenic fungi, the sequence of pseudin-2 was modified by alanine or lysine at each position of two amino acids within the leucine-zipper motif. Alanine-substituted variants were highly selective toward fungi over HaCaT and erythrocytes and maintained their antifungal activities and mode of action (membranolysis). However, the antifungal activities of lysine-substituted peptides were reduced, and the compound could penetrate into fungal cells, followed by induction of mitochondrial reactive oxygen species and cell death. In vivo antifungal assays of analogous peptide showed excellent antifungal efficiency in a Candida tropicalis skin infection mouse model. Our results demonstrated the usefulness of selective amino acid substitution in the repeated sequence of the leucine-zipper motif for the design of AMPs with potent antimicrobial activities and low toxicity.

Selective laser sintering of metal nanoparticle ink is an attractive technology for the creation of metal layers at the microscale without any vacuum deposition process, yet its application to elastomer substrates has remained a highly challenging task. To address this issue, we introduced the shear-assisted laser transfer of metal nanoparticle ink by utilizing the difference in thermal expansion coefficients between the elastomer and the target metal electrode. The laser was focused and scanned across the absorbing metal nanoparticle ink layer that was in conformal contact with the elastomer with a high thermal expansion coefficient. The resultant shear stress at the interface assists the selective transfer of the sintered metal nanoparticle layer. We expect that the proposed method can be a competent fabrication route for a transparent conductor on elastomer substrates.