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In this study, we introduce a novel design for a three-dimensional (3D) controller, which incorporates the omni-purpose stretchable strain sensor (OPSS sensor). This sensor exhibits both remarkable sensitivity, with a gauge factor of approximately 30, and an extensive working range, accommodating strain up to 150%, thereby enabling accurate 3D motion sensing. The 3D controller is structured such that its triaxial motion can be discerned independently along the X, Y, and Z axes by quantifying the deformation of the controller through multiple OPSS sensors affixed to its surface. To ensure precise and real-time 3D motion sensing, a machine learning-based data analysis technique was implemented for the effective interpretation of the multiple sensor signals. The outcomes reveal that the resistance-based sensors successfully and accurately track the 3D controller's motion. We believe that this innovative design holds the potential to augment the performance of 3D motion sensing devices across a diverse range of applications, encompassing gaming, virtual reality, and robotics. [ABSTRACT FROM AUTHOR]

Image-based cell sorting is essential in biological and biomedical research. The sorted cells can be used for downstream analysis to expand our knowledge of cell-to-cell differences. We previously demonstrated a user-friendly image-activated microfluidic cell sorting technique using an optimized and fast deep learning algorithm. Real-time isolation of cells was carried out using this technique with an inverted microscope. In this study, we devised a recently upgraded sorting system. The cell sorting techniques shown on the microscope were implemented as a real system. Several new features were added to make it easier for the users to conduct the real-time sorting of cells or particles. The newly added features are as follows: (1) a high-resolution linear piezo-stage is used to obtain in-focus images of the fast-flowing cells; (2) an LED strobe light was incorporated to minimize the motion blur of fast-flowing cells; and (3) a vertical syringe pump setup was used to prevent the cell sedimentation. The sorting performance of the upgraded system was demonstrated through the real-time sorting of fluorescent polystyrene beads. The sorter achieved a 99.4% sorting purity for 15 μ m and 10 μ m beads with an average throughput of 22.1 events per second (eps). [ABSTRACT FROM AUTHOR]

Featured Application: Recently upgraded inject-and-transfer system will improve beamtime efficiency for serial femtosecond crystallography. Serial femtosecond crystallography (SFX) using an X-ray free-electron laser (XFEL) can be applied to determine the room-temperature structure of target molecules while minimizing radiation damage and visualizing molecular dynamics. In SFX, a sample delivery system is required to deliver microcrystals to the XFEL beam path in a serial manner. We recently developed a sample delivery method, the combined inject-and-transfer system (BITS), which is a hybrid method based on the injector and fixed-target scanning approach. In this study, we introduced recently upgraded hardware to move the injection needle in the direction of the XYZ-axis and a graphic user interface for user motion control. Furthermore, we report that the viscous solution containing 10% (w/v) PEG 3350 or PEG 6000 that is widely used for protein crystallization can be stably deposited on polyimide film with a hydrophobic surface without any special treatment. Moreover, the development of an inject-and-diffuse method for time-resolved studies with liquid applications in the BITS and its preliminary results are reported. This study provides up-to-date instrument information to SFX users using BITS and provides insights to instrument developers for SFX. [ABSTRACT FROM AUTHOR]

Featured Application: Our results provide insight into the material selection and directions to pursue in developing sample delivery devices used in XFEL studies. A crystal delivery system is essential in serial femtosecond crystallography experiments using an X-ray free-electron laser (XFEL). Investigating the XFEL-induced radiation damage to materials potentially applicable to sample delivery devices is vital for developing a sample delivery system. In this study, we investigated the radiation damage caused by an XFEL to polydimethylsiloxane (PDMS) and polyimide (PI), which are widely used as sample delivery materials in synchrotron X-rays. Upon XFEL exposure, the PDMS film produced irregularly shaped and sized holes, whereas the PI film produced relatively regular shaped and sized holes. When XFELs were exposed to the channel of the PDMS-based microfluidic device, holes were generated on the film by the radiation damage and the microfluidic device and the internal channel region were structurally destroyed. The PI-based microfluidic device experienced no structural destruction, except for the holes generated by the XFEL. However, as the XFELs were continuously exposed, bubbles generated from the solution due to radiation damage; the accumulation of these bubbles interfered with the path of the inner channel of the microfluidic device. Our results will not only help understand the phenomenon of radiation damage of PDMS and PI films by XFEL, but also provide insight into the directions to pursue in developing applications of PDMS and PI films in XFEL studies. [ABSTRACT FROM AUTHOR]

Ensuring the safety of a teleoperation system is crucial, and optimization-based control approaches are an effective solution to ensure that the robot satisfies the multiple safety constraints. However, the control input reshaping via optimization can make a system nonpassive. Therefore, this study proposes a new optimization method for ensuring both the safety and passivity of a teleoperation system by integrating it with the task scaling method. Additionally, the energy tank method is implemented to modulate the tradeoff between dissipativity and control performance. The experiments demonstrated that the proposed method ensures the safety and passivity of the teleoperated system for all robot configurations and any operator’s command inputs. [ABSTRACT FROM AUTHOR]

Purpose: To measure needle insertion force and change in intraocular pressure (IOP) in real-time during intravitreal injection (IVI). The effects of needle size, insertion speed, and injection rate to IOP change were investigated. Methods: Needle insertion and fluid injection were performed on 90 porcine eyeballs using an automatic IVI device. The IVI conditions were divided according to needle sizes of 27-gauge (G), 30G, and 33G; insertion speeds of 1, 2, and 5 mm/s; and injection rates of 0.01, 0.02, and 0.05 mL/s. Insertion force and IOP were measured in real-time using a force sensor and a pressure transducer. Results: The peak IOP was observed when the needle penetrated the sclera; the average IOP elevation was 96.3, 67.1, and 59.4 mmHg for 27G, 30G, and 33G needles, respectively. An increase in insertion speed caused IOP elevation at the moment of penetration, but this effect was reduced as needle size decreased: 109.8–85.9 mmHg in 27G for 5–1 mm/s (p = 0.0149) and 61.8–60.7 mmHg in 33G for 5–1 mm/s (p = 0.8979). Injection speed was also related to IOP elevation during the stage of drug injection: 16.65 and 11.78 mmHg for injection rates of 0.05 and 0.01 mL/s (p < 0.001). Conclusion: The presented data offers an understanding of IOP changes during each step of IVI. Slow needle insertion can reduce IOP elevation when using a 27G needle. Further, the injection rate must be kept low to avoid IOP elevations during the injection stage. [ABSTRACT FROM AUTHOR]

Image-activated cell sorting is an essential biomedical research technique for understanding the unique characteristics of single cells. Deep learning algorithms can be used to extract hidden cell features from high-content image information to enable the discrimination of cell-to-cell differences in image-activated cell sorters. However, such systems are challenging to implement from a technical perspective due to the advanced imaging and sorting requirements and the long processing times of deep learning algorithms. Here, we introduce a user-friendly image-activated microfluidic sorting technique based on a fast deep learning model under the TensorRT framework to enable sorting decisions within 3 ms. The proposed sorter employs a significantly simplified operational procedure based on the use of a syringe connected to a piezoelectric actuator. The sorter has a 2.5 ms latency. The utility of the sorter was demonstrated through real-time sorting of fluorescent polystyrene beads and cells. The sorter achieved 98.0%, 95.1%, and 94.2% sorting purities for 15 μm and 10 μm beads, HL-60 and Jurkat cells, and HL-60 and K562 cells, respectively, with a throughput of up to 82.8 events per second (eps). [ABSTRACT FROM AUTHOR]

In corneal transplantation, 16 submillimeter-sized sutures are generated around the circular-shaped graft cornea. A major challenge in corneal transplantation is the generation of uniformly shaped sutures, where the suture shapes need to be changed depending on the patient. In this study, a corneal suturing robot that can produce sutures of the desired shape with high uniformity is described. The proposed robot manipulates the corneal tissue deformation before inserting the needle for suture shape control. A simulation using the finite element method was proposed to predict the suture shape. The suturing experiment was conducted on a porcine model, and the result was compared with the simulation. As a result, the proposed robot was able to generate sutures with a standard deviation of 108  $\mu$ m in length and 36  $\mu$ m in depth. The mean absolute error between the simulation and the experiment was 95  $\mu$ m in length and 31  $\mu$ m in depth. This is the first study to suggest a method for controlling the suture shape and quantitatively analyzing it in ophthalmic surgery. [ABSTRACT FROM AUTHOR]

Serial femtosecond crystallography (SFX) enables the determination of the room‐temperature crystal structure of macromolecules, as well as providing time‐resolved molecular dynamics data in pump–probe experiments. Fixed‐target SFX (FT‐SFX) can minimize sample consumption and physical effects on crystals during sample delivery. In FT‐SFX studies, having a sample holder that can stably fix crystal samples is one of the key elements required for efficient data collection. Hence, development of sample holders from new materials capable of supporting various crystal sizes and shapes may expand the applications of FT‐SFX. Here, a viscous‐media‐based crystal support in a sample holder for FT‐SFX is introduced. Crystal samples were embedded in viscous media, namely gelatin and agarose, which were enclosed in a polyimide film. In the vertically placed sample holder, 10–15%(w/v) viscous gelatin and 1–4%(w/v) agarose gel stably supported crystals between two polyimide films, thereby preventing the crystals from descending owing to gravity. Using this method, FT‐SFX experiments were performed with glucose isomerase and lysozyme embedded in gelatin and agarose, respectively. The room‐temperature crystal structures of glucose isomerase and lysozyme were successfully determined at 1.75 and 1.80 Å resolutions, respectively. The glucose isomerase and lysozyme diffraction analyses were not impeded by excessive background scattering from the viscous media. This method is useful for delivering crystal samples of various sizes and shapes in FT‐SFX experiments. [ABSTRACT FROM AUTHOR]

A direct, ready-to-use surface electromyogram (sEMG) pattern classification algorithm that does not require prerequisite training, regardless of the user, is proposed herein. In addition to data collection, conventional supervised learning approaches for sEMG require labeling and segmenting the data and additional time for the learning algorithm. Consequently, these approaches cannot cope well with sEMG patterns during motion transitions of various movement speeds. The proposed unsupervised and self-adaptive method employs an iterative self-adaptive procedure realized by the probabilistic methods of diffusion, updating, and registration to cluster the activation patterns simultaneously in real time, and classify the current sEMG as new clustered patterns. Experiments demonstrated that even for the same motion, the proposed method could autonomously detect changes in muscular activation patterns varying with the speed of motion. Furthermore, some patterns of both steady- and transient-state motions could be distinguished. In addition, it was verified that the classified sEMG pattern could be correlated consistently with the actual motion, thereby realizing a high level of motion classification. [ABSTRACT FROM AUTHOR]

Microcrystal delivery methods are pivotal in the use of serial femtosecond crystallography (SFX) to resolve the macromolecular structures of proteins. Here, the development of a novel technique and instruments for efficiently delivering microcrystals for SFX are presented. The new method, which relies on a one‐dimensional fixed‐target system that includes a microcrystal container, consumes an extremely low amount of sample compared with conventional two‐dimensional fixed‐target techniques at ambient temperature. This novel system can deliver soluble microcrystals without highly viscous carrier media and, moreover, can be used as a microcrystal growth device for SFX. Diffraction data collection utilizing this advanced technique along with a real‐time visual servo scan system has been successfully demonstrated for the structure determination of proteinase K microcrystals at 1.85 Å resolution. [ABSTRACT FROM AUTHOR]

Range sensors based on electromagnetic (EM) waves attenuation along the target distance yield precise distance estimation with a high resolution, depending on the distance. However, their application in a structured underwater environment is difficult because the characteristics of EM waves attenuation in such environments are not considered. In this study, characteristics of EM waves propagation and signal interference effects due to structures are analyzed, and an EM waves distance-attenuation model for a structured underwater environment is proposed, along with sensor installation guidelines. The characteristics of EM waves propagation and the proposed sensor model are verified by several experiments, and the proposed sensor model yields greater accuracy positioning results compared to the previous model. [ABSTRACT FROM AUTHOR]

This article proposes a disturbance observer (DOB)-based compliance control strategy for electrohydrostatic actuators (EHAs), particularly those with high gear reductions and long hydraulic pipelines, which could lead to a high performance interactive robot system. EHAs suffer significantly from internal leakage and friction, which hampers the application of existing compliance control methods to EHAs. Therefore, a two-degree-of-freedom (DoF) DOB is introduced to compensate for both undesirable effects separately; one degree of freedom handles friction observations and the other monitors internal leakage. Then, a compliance controller is designed without affecting the closed-loop stability. To this end, the state of the nominal plant, not the real plant, is used in the designs of the internal leakage observer and the compliance controller as it guarantees closed-loop stability. The asymptotic convergence of the closed-loop system is evaluated via simulations and experiments. [ABSTRACT FROM AUTHOR]

Displacement information is essential in many robotic applications involving contact, especially with viscoelastic objects. In this paper, we provide a novel displacement estimation method using contact pressure distribution. Our method can estimate displacement using only a typical tactile sensor, which can be shared by a force measurement. As a result, our method can reduce the number of required sensors for stiffness estimation, so it is suitable for stiffness-required applications with strict spatial constraints. Simulation and experimental results demonstrate the performance of our method. [ABSTRACT FROM AUTHOR]

The demand for high-performance impedance control in electro-hydraulic actuation systems is a mainstream issue in the robot actuation research community. Although various nonlinear model-based impedance controllers have been developed and showed good performance in recent years, they remain hindered by the high cost of force sensors, and accurate internal dynamics models need to be derived to overcome the non-backdrivability and complex dynamics of hydraulic systems. As a solution to these problems, this paper presents an impedance control approach for hydraulic systems that require no external force sensors or chamber pressure sensors with a pressure control servovalve or backdrivable servovalve. First, we show that a backdrivable servovalve brings inherent backdrivability to hydraulic systems, such that high-performance impedance control can be implemented without requirement of force sensors and exact knowledge on the dynamics of hydraulic chambers, owing to its torque-source property and low effective valve inertia on the link side. Second, utilizing the obtained backdrivability, we develop a passivity-guaranteed impedance controller. A momentum-based external torque observation algorithm is incorporated to render desired impedance over a wide range, without using force/torque sensor. The performance of the proposed backdrivable servovalve and impedance controller was verified through extensive experimental results. [ABSTRACT FROM AUTHOR]

This paper presents an admittance controller based on the passivity theory for a powered upper-limb exoskeleton robot, which is governed by the nonlinear equation of motion. Passivity allows us to include a human operator and environmental interaction in the control loop. The robot interacts with the human operator via force/torque (F/T) sensor and interacts with the environment mainly via end-effectors. Although the environmental interaction cannot be detected by any sensors (hence unknown), passivity allows us to have natural interaction. An analysis shows that the behavior of the actual system mimics that of a nominal model as the control gain goes to infinity, which implies that the proposed approach is an admittance controller. However, because the control gain cannot grow infinitely in practice, the performance limitation according to the achievable control gain is also analyzed. The result of this analysis indicates that the performance in the sense of infinite norm increases linearly with the control gain. In the experiments, the proposed properties were verified using 1-DoF testbench, and an actual powered upper-limb exoskeleton was used to lift and maneuver the unknown payload. [ABSTRACT FROM AUTHOR]

Impedance control allows robots to manipulate physical interactions delicately. However, issues associated with path planning and impedance remain unresolved. Herein we propose a path and impedance planning method for impedance control in a robot based on programming by demonstration through telemanipulation using a surface electromyogram. We considered a task that requires quick and precise adjustment of path and impedance, that is, ball trapping. We implemented a teleoperated robot that can deliver an operator's impedance as well as position during the ball trapping task to the slave side. The operators were asked to perform demonstrations of ball-trapping tasks using the implemented teleoperated robot, where the slave side is a vertical robot with one degree of freedom. The path and impedance were recorded and programmed as control input profiles from a set of successful demonstrations using Gaussian mixture regression. The result showed that using the human demonstration, the robot could learn how to catch a dropped ball without rebounding. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) measurements have demonstrated the potential to recognize complex hand motions. In addition, sEMG enables natural recognition without disturbing movements, and thus, can be used in various fields such as teleoperation, assistant robots, and prosthetic hands. However, sEMG signals highly depend on electrode placements due to the complex muscle structures. A shift of the electrode can lead to inconsistent signal measurement. Thus, sEMG-based recognition is not practical for applications that require long-term and repeated usage. This paper proposes compensation of sEMG interface rotation for robust motion recognition. Once the relationship between sEMG signals and motions is trained, additional training for different electrode configurations is not necessary for a band-type interface. The proposed process is simple and fast. The interface rotation can be compensated for by performing only a single motion for approximately 2 s. The single motion for compensation is dependent on the muscle properties of the user. Generally, ulnar deviation may work. To demonstrate the proposed compensation, recognition of five hand motions is conducted. The experimental results indicate that the proposed compensation can cover the overall range of rotation. In addition, the proposed compensation is validated with a transradial amputee. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical roadmap (HRM) and its construction process to efficiently represent navigable areas in an indoor environment. HRM is adopted to solve the path‐planning problems of mobile robots in indoor environments. HRM has a multi‐layered graphical structure that enables it to abstract and cover navigable areas using a smaller number of nodes and edges than a probabilistic roadmap. During the incremental process of constructing HRM, information on navigable areas is abstracted using a sonar gridmap when the mobile robot navigates an unexplored area. The HRM‐based planner efficiently searches for paths to answer queries by reducing the search space size using the multi‐layered graphical structure. The benefits of the proposed HRM are experimentally verified in real indoor environments. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) signals reflect muscle contraction and hence, can provide information regarding a user's movement intention. High-density sEMG systems have been proposed to measure muscle activity in small areas and to estimate complex motion using spatial patterns. However, conventional systems based on wet electrodes have several limitations. For example, the electrolyte enclosed in wet electrodes restricts spatial resolution, and these conventional bulky systems limit natural movements. In this paper, a microneedle-based high-density electrode array on a circuit integrated flexible substrate for sEMG is proposed. Microneedles allow for high spatial resolution without requiring conductive substances, and flexible substrates guarantee stable skin-electrode contact. Moreover, a compact signal processing system is integrated with the electrode array. Therefore, sEMG measurements are comfortable to the user and do not interfere with the movement. The system performance was demonstrated by testing its operation and estimating motion using a Gaussian mixture model-based, simplified 2D spatial pattern. [ABSTRACT FROM AUTHOR]

For highly-integrated microfluidic systems, an actuation system is necessary to control the flow; however, the bulk of actuation devices including pumps or valves has impeded the broad application of integrated microfluidic systems. Here, we suggest a microfluidic process control method based on built-in microfluidic circuits. The circuit is composed of a fluidic timer circuit and a pneumatic logic circuit. The fluidic timer circuit is a serial connection of modularized timer units, which sequentially pass high pressure to the pneumatic logic circuit. The pneumatic logic circuit is a NOR gate array designed to control the liquid-controlling process. By using the timer circuit as a built-in signal generator, multi-step processes could be done totally inside the microchip without any external controller. The timer circuit uses only two valves per unit, and the number of process steps can be extended without limitation by adding timer units. As a demonstration, an automation chip has been designed for a six-step droplet treatment, which entails 1) loading, 2) separation, 3) reagent injection, 4) incubation, 5) clearing and 6) unloading. Each process was successfully performed for a pre-defined step-time without any external control device. [ABSTRACT FROM AUTHOR]

In this paper, an underwater 3-D spatial attenuation model of electromagnetic waves is proposed to establish a position recognition system in underwater 3-D space using distance estimation. The distance estimation is based on signal attenuation characteristics of electromagnetic waves radiated through several omnidirectional antennas. Positions in underwater environments have been predominantly estimated by an ultrasonic position recognition system using travel time and phase difference. However, such a system provides inaccurate estimation on account of the multipath effect in a structured environment or complex environment with many obstacles. A position estimation method that uses signal attenuation of electromagnetic waves has been proposed to overcome this limitation. That method can precisely estimate position on a structured 2-D plane. In this paper, an existing underwater position estimation system based on electromagnetic waves is expanded into 3-D space using the Friis formula and plane wave equation, thereby classifying attenuation characteristics of electromagnetic waves into the effects of medium, radiation, and antenna. These effects are summarized to deduce the signal attenuation characteristics of electromagnetic waves in 3-D space. In addition, the relative position (R, { \Theta}, { \Phi}) and attitude ( \phi, \theta, $\psi$) of transceiver antennas are used to define a coordinate system for 3-D estimation; moreover, an attenuation model is defined for individual factors in the coordinate system. A generalized attenuation model of an omnidirectional antenna in 3-D space is presented, and the validity of the proposed model is demonstrated through experiments. Based on the results, the proposed model demonstrates the potential application to an omnidirectional antenna and expansion into an attenuation model based on the 3-D position between random antennas. [ABSTRACT FROM PUBLISHER]

In this paper, we discuss a novel underwater short-range sensor using electromagnetic (EM) wave attenuation. We use the revised Friis–Shelkunoff formula to calculate the EM wave attenuation underwater as a function of distance. This requires knowledge of the antenna gain underwater, which is very different from the gain in air, and also the attenuation constant which depends on the water conductivity. We calibrated the gain and attenuation in a ranging experiment and also in a 2-D localization experiment. Both methods agreed, confirming that in situ calibration of a 2-D localization experiment is feasible. The localization results show good accuracy, validating the sensor model and showing that multipath effects can be made negligible in such an experiment. [ABSTRACT FROM PUBLISHER]

This paper proposes a robust PD control scheme for flexible-joint robots based on a disturbance observer (DOB). In this paper, the DOB is applied only to the motor-side dynamics of the robot, and the uncertainties on the motor-side are successfully eliminated. It is shown that the proposed DOB-based approach guarantees global asymptotic stability. To this end, two special treatments are required. First, unlike the typical configuration of the DOB, nominal states of the motor-side are fed back to the PD controller. Second, a control input that makes the nominal states stable is additionally introduced. The proposed approach was verified using multi-degree-of-freedom experiments. [ABSTRACT FROM PUBLISHER]

This paper proposes a framework called nonlinear robust internal-loop compensator that enables us to bring nonlinear \mathcal H_\infty optimality to robot controllers in a unified and simple way. Using the framework, a controller designed for the nominal plant can achieve additional robustness by simply adding PID-type auxiliary input to the original control law. Robust performance is guaranteed by the nonlinear \mathcal H_\infty optimality and robust stability is guaranteed by proving the extended disturbance input-to-state stability. Moreover, the framework preserves the passivity property of the original controller. Finally, the performance bound can be predicted and leads to the gain tuning rules. By virtue of the tuning rules, the performance can be tuned using only a single variable. The proposed method was validated through the simulations and experiments. [ABSTRACT FROM PUBLISHER]