Cyborg and bionic systems (Washington, D.C.)最新文献

Cockroaches can traverse unknown obstacle-terrain, self-right on the ground and climb above the obstacle. However, they have limited motion, such as less activity in light/bright areas and lower temperatures. Therefore, the movement of the cyborg cockroaches needs to be optimized for the utilization of the cockroach as a cyborg insect. This study aims to increase the search rate and distance traveled by cockroaches and reduce the stop time by utilizing automatic stimulation from machine learning. Multiple machine learning classifiers were applied to classify the offline binary classification of the cockroach movement based on the inertial measuring unit input signals. Ten time-domain features were chosen and applied as the classifier inputs. The highest performance of the classifiers was implemented for the online motion recognition and automatic stimulation provided to the cerci to trigger the free walking motion of the cockroach. A user interface was developed to run multiple computational processes simultaneously in real time such as computer vision, data acquisition, feature extraction, automatic stimulation, and machine learning using a multithreading algorithm. On the basis of the experiment results, we successfully demonstrated that the movement performance of cockroaches was importantly improved by applying machine learning classification and automatic stimulation. This system increased the search rate and traveled distance by 68% and 70%, respectively, while the stop time was reduced by 78%.

Field-controlled microrobots have attracted extensive research in the biological and medical fields due to the prominent characteristics including high flexibility, small size, strong controllability, remote manipulation, and minimal damage to living organisms. However, the fabrication of these field-controlled microrobots with complex and high-precision 2- or 3-dimensional structures remains challenging. The photopolymerization technology is often chosen to fabricate field-controlled microrobots due to its fast-printing velocity, high accuracy, and high surface quality. This review categorizes the photopolymerization technologies utilized in the fabrication of field-controlled microrobots into stereolithography, digital light processing, and 2-photon polymerization. Furthermore, the photopolymerized microrobots actuated by different field forces and their functions are introduced. Finally, we conclude the future development and potential applications of photopolymerization for the fabrication of field-controlled microrobots.

In this paper, we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement learning. Specifically, we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat interactions. The novelty of our method lies in using the temporal difference (TD) algorithm to optimize the state decision process, which enables the robots to make informed decisions about their behavior choices. To assess the similarity between robot and rat behavior, we use Pearson correlation. We then use TD-λ to update the state value function and make state decisions based on probability. The robots execute these decisions using our dynamics-based controller. Our results demonstrate that our method can generate rat-like behaviors on both short- and long-term timescales, with interaction information entropy comparable to that between real rats. Overall, our approach shows promise for controlling robots in robot-rat interactions and highlights the potential of using reinforcement learning to develop more sophisticated robotic systems.

In neurorehabilitation, motor performances may improve if patients could accomplish the training by overcoming mechanical loads. When the load inertia is increased, it has been found to trigger linear responses in motor-related cortices. The cortical responses, however, are unclear whether they also correlate to changes in muscular patterns. Therefore, it remains difficult to justify the magnitude of load during rehabilitation because of the gap between cortical and muscular activation. Here, we test the hypothesis that increases in load inertia may alter the muscle synergies, and the change in synergy may correlate with cortical activation. Twelve healthy subjects participated in the study. Each subject lifted dumbbells (either 0, 3, or 15 pounds) from the resting position to the armpit repetitively at 1 Hz. Surface electromyographic signals were collected from 8 muscles around the shoulder and the elbow, and hemodynamic signals were collected using functional near-infrared spectroscopy from motor-related regions Brodmann Area 4 (BA4) and BA6. Results showed that, given higher inertia, the synergy vectors differed farther from the baseline. Moreover, synergy similarity on the vector decreased linearly with cortical responses in BA4 and BA6, which associated with increases in inertia. Despite studies in literature that movements with similar kinematics tend not to differ in synergy vectors, we show a different possibility that the synergy vectors may deviate from a baseline. At least 2 consequences of adding inertia have been identified: to decrease synergy similarity and to increase motor cortical activity. The dual effects potentially provide a new benchmark for therapeutic goal setting.

Caenorhabditis elegans (C. elegans) has been a popular model organism for several decades since its first discovery of the huge research potential for modeling human diseases and genetics. Sorting is an important means of providing stage- or age-synchronized worm populations for many worm-based bioassays. However, conventional manual techniques for C. elegans sorting are tedious and inefficient, and commercial complex object parametric analyzer and sorter is too expensive and bulky for most laboratories. Recently, the development of lab-on-a-chip (microfluidics) technology has greatly facilitated C. elegans studies where large numbers of synchronized worm populations are required and advances of new designs, mechanisms, and automation algorithms. Most previous reviews have focused on the development of microfluidic devices but lacked the summaries and discussion of the biological research demands of C. elegans, and are hard to read for worm researchers. We aim to comprehensively review the up-to-date microfluidic-assisted C. elegans sorting developments from several angles to suit different background researchers, i.e., biologists and engineers. First, we highlighted the microfluidic C. elegans sorting devices' advantages and limitations compared to the conventional commercialized worm sorting tools. Second, to benefit the engineers, we reviewed the current devices from the perspectives of active or passive sorting, sorting strategies, target populations, and sorting criteria. Third, to benefit the biologists, we reviewed the contributions of sorting to biological research. We expect, by providing this comprehensive review, that each researcher from this multidisciplinary community can effectively find the needed information and, in turn, facilitate future research.

Hyperthermia can be induced to exploit the thermal intolerance of cancer cells, which is worse than that of normal cells, as a potential noninvasive cancer treatment. To develop an effective hyperthermia treatment, thermal cytotoxicity of cells should be comprehensively investigated. However, to conduct such investigations, the culture temperature must be accurately regulated. We previously reported a culture system in which the culture temperature could be accurately regulated by employing metallic culture vessels. However, appropriate temperature conditions for hyperthermia depend on the cell species. Consequently, several experiments need to be conducted, which is a bottleneck of inducing hyperthermia. Hence, we developed a cell culture system with temperature gradation on a metallic culture surface. Michigan Cancer Foundation-7 cells and normal human dermal fibroblasts were used as cancer and normal cell models, respectively. Normal cells showed stronger thermal tolerance; this was because the novel system immediately exhibited a temperature gradation. Thus, the developed culture system can be used to investigate the optimum thermal conditions for effective hyperthermia treatment. Furthermore, as the reactions of cultured cells can be effectively assessed with the present results, further research involving the thermal stimulation of cells is possible.

In the robot-assisted minimally invasive surgery, if a collision occurs, the robot system program could be damaged, and normal tissues could be injured. To avoid collisions during surgery, a 3-dimensional collision avoidance method is proposed in this paper. The proposed method is predicated on the design of 3 strategic vectors: the collision-with-instrument-avoidance (CI) vector, the collision-with-tissues-avoidance (CT) vector, and the constrained-control (CC) vector. The CI vector demarcates 3 specific directions to forestall collision among the surgical instruments. The CT vector, on the other hand, comprises 2 components tailored to prevent inadvertent contact between the robot-controlled instrument and nontarget tissues. Meanwhile, the CC vector is introduced to guide the endpoint of the robot-controlled instrument toward the desired position, ensuring precision in its movements, in alignment with the surgical goals. Simulation results verify the proposed collision avoidance method for robot-assisted minimally invasive surgery. The code and data are available at https://github.com/cynerelee/collision-avoidance.

On-orbit assembly has become a crucial aspect of space operations, where the manipulator frequently and directly interacts with objects in a complex assembly process. The traditional manipulator control has limitations in adapting to diverse assembly tasks and is vulnerable to vibration, leading to assembly failure. To address this issue, we propose a human-like variable admittance control method based on the variable damping characteristics of the human arm. By collecting the velocity and contact force of human arm operations in assembly, we analyze the damping change of human arm and establish the active compliance model based on S-type damping variation rule in assembly. Furthermore, 3 passive contact models are proposed between the end of the human arm and the environment: one-sided bevel contact, both sides bevel contact, and pin-hole contact. On the basis of these active and passive models, a typical space assembly task for a robot is designed, and a human-like variable admittance controller is established and simulated. Finally, we build a ground verification platform and complete different assembly tasks, thereby successfully verifying the safety, robustness, and adaptability of the human-like variable admittance control method.

Moral elevation, the emotion that arises when individuals observe others' moral behaviors, plays an important role in determining moral behaviors in real life. While recent research has demonstrated the potential to decode basic emotions with brain signals, there has been limited exploration of affective computing for moral elevation, an emotion related to social cognition. To address this gap, we recorded electroencephalography (EEG) signals from 23 participants while they viewed videos that were expected to elicit moral elevation. More than 30,000 danmaku comments were extracted as a crowdsourcing tagging method to label moral elevation continuously at a 1-s temporal resolution. Then, by employing power spectra features and the least absolute shrinkage and selection operator regularized regression analyses, we achieved a promising prediction performance for moral elevation (prediction r = 0.44 ± 0.11). Our findings indicate that it is possible to decode moral elevation using EEG signals. Moreover, the small-sample neural data can predict the continuous moral elevation experience conveyed in danmaku comments from a large population.

Wearable body sensor nodes require massive data transmission under limited energy. However, it suffers from drastically varying channel loss, which limits its energy efficiency in practical scenarios. This paper presents a power-driven body-channel transceiver (TRX), whose power consumption can be adaptively tuned against varying channel loss. An out-band programmable gain amplifier (PGA) is proposed to save power and generate a quasi-linear correlation between PGA gain and power. By using the quasi-linear gain-power relationship, we propose an auto gain/power control technique to realize on-demand power consumption. In addition, a differential balanced transmitter is designed to eliminate base-band harmonics in on-off keying modulation and increase the power delivered by the transmitter (TX). The TX and receiver (RX) of the prototype were integrated into 1 chip and fabricated in a 55-nm complementary metal oxide semiconductor process. During the measurement, 2 chips were configured as TX and RX, respectively. Both the TX and the RX were wearable, powered by lithium batteries, and attached to the subject's hands. The prototype achieved a 5.25-Mbps data rate with 16-pJ/bit energy efficiency at a 1.5-m straight-line ground path distance. Furthermore, the proposed TRX maintained stable communication within a 1.5-m distance, while dynamically reducing power consumption.