Advanced Robotics to Address the Translational Gap in Tendon Engineering

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Journal profile

The Open Access journal Cyborg and Bionic Systems, published in association with BIT, promotes the knowledge interchange and hybrid system codesign between living beings and robotic systems.

Editorial board

Cyborg and Bionic Systems’ editorial board is led by Toshio Fukuda (Beijing Institute of Technology) and is comprised of experts who have made significant and well recognized contributions to the field.

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Research Article

Efficacy of Biological and Physical Enhancement on Targeted Muscle Reinnervation

Targeted muscle reinnervation (TMR) is a microsurgical repair technique to reconstruct the anatomical structure between the distal nerve and the muscle stump to provide more myoelectric information to the artificially intelligent prosthesis. Postoperative functional electrical stimulation treatment of the patient’s denervated muscle or proximal nerve stump as well as nerve growth factor injection is effective in promoting nerve regeneration and muscle function recovery. In this experiment, we successfully established a TMR rat model and divided Sprague-Dawley (SD) adult male rats into TMR group, TMR + FES group, and TMR + NGF group according to TMR and whether they received FES treatment or NGF injection after surgery, and the recovery effect of rat neuromuscular function was assessed by analyzing EMG signals. Through the experiments, we confirmed that growth factor supplementation and low-frequency electrical stimulation can effectively promote the regeneration of the transplanted nerve as well as significantly enhance the motor function of the target muscle and have a positive effect on the regeneration of the transplanted nerve.

Research Article

Platelet Detection Based on Improved YOLO_v3

Platelet detection and counting play a greatly significant role in medical field, especially in routine blood tests which can be used to judge blood status and diagnose related diseases. Therefore, platelet detection is valuable for diagnosing related blood diseases such as liver-related diseases. Blood analyzers and visual microscope counting were widely used for platelet detection, but the experimental procedure took nearly 20 minutes and can only be performed by a professional doctor. In recent years, technological breakthroughs in artificial intelligence have made it possible to detect red blood cells through deep learning methods. However, due to the inaccessibility of platelet datasets and the small size of platelets, deep learning-based platelet detection studies are almost nonexistent. In this paper, we carried out experiments for platelet detection based on commonly used object detection models, such as Single Shot Multibox Detector (SSD), RetinaNet, Faster_rcnn, and You Only Look Once_v3 (YOLO_v3). Compared with the other three models, YOLO_v3 can detect platelets more effectively. And we proposed three ideas for improvement based on YOLO_v3. Our study demonstrated that YOLO_v3 can be adopted for platelet detection accurately and in real time. We also implemented YOLO_v3 with multiscale fusion, YOLO_v3 with anchor box clustering, and YOLO_v3 with match parameter on our self-created dataset and, respectively, achieved 1.8% higher average precision (AP), 2.38% higher AP, and 2.05% higher AP than YOLO_v3. The comprehensive experiments revealed that YOLO_v3 with the improved ideas performs better in platelet detection than YOLO_v3.

Review Article

Graphdiyne-Related Materials in Biomedical Applications and Their Potential in Peripheral Nerve Tissue Engineering

Graphdiyne (GDY) is a new member of the family of carbon-based nanomaterials with hybridized carbon atoms of sp and sp2, including α, β, γ, and (6,6,12)-GDY, which differ in their percentage of acetylene bonds. The unique structure of GDY provides many attractive features, such as uniformly distributed pores, highly π-conjugated structure, high thermal stability, low toxicity, biodegradability, large specific surface area, tunable electrical conductivity, and remarkable thermal conductivity. Therefore, GDY is widely used in energy storage, catalysis, and energy fields, in addition to biomedical fields, such as biosensing, cancer therapy, drug delivery, radiation protection, and tissue engineering. In this review, we first discuss the synthesis of GDY with different shapes, including nanotubes, nanowires, nanowalls, and nanosheets. Second, we present the research progress in the biomedical field in recent years, along with the biodegradability and biocompatibility of GDY based on the existing literature. Subsequently, we present recent research results on the use of nanomaterials in peripheral nerve regeneration (PNR). Based on the wide application of nanomaterials in PNR and the remarkable properties of GDY, we predict the prospects and current challenges of GDY-based materials for PNR.

Research Article

Implementing Monocular Visual-Tactile Sensors for Robust Manipulation

Tactile sensing is an essential capability for robots performing manipulation tasks. In this paper, we introduce a framework to build a monocular visual-tactile sensor for robotic manipulation tasks. Such a sensor is easy to manufacture with affordable ingredients and materials. Based on a marker-based detection method, the sensor can detect the contact positions on a flat or curved surface. In the case study, we have implemented a visual-tactile sensor design specifically through the framework proposed in this paper. The design is low cost and can be processed in a very short time, making it suitable for use as an exploratory study in the laboratory.

Research Article

Robotic Intracellular Electrochemical Sensing for Adherent Cells

Nanopipette-based observation of intracellular biochemical processes is an important approach to revealing the intrinsic characteristics and heterogeneity of cells for better investigation of disease progression or early disease diagnosis. However, the manual operation needs a skilled operator and faces problems such as low throughput and poor reproducibility. This paper proposes an automated nanopipette-based microoperation system for cell detection, three-dimensional nonovershoot positioning of the nanopipette tip in proximity to the cell of interest, cell approaching and proximity detection between nanopipette tip and cell surface, and cell penetration and detection of the intracellular reactive oxygen species (ROS). A robust focus algorithm based on the number of cell contours was proposed for adherent cells, which have sharp peaks while retaining unimodality. The automated detection of adherent cells was evaluated on human umbilical cord vein endothelial cells (HUVEC) and NIH/3T3 cells, which provided an average of 95.65% true-positive rate (TPR) and 7.59% false-positive rate (FPR) for in-plane cell detection. The three-dimensional nonovershoot tip positioning of the nanopipette was achieved by template matching and evaluated under the interference of cells. Ion current feedback was employed for the proximity detection between the nanopipette tip and cell surface. Finally, cell penetration and electrochemical detection of ROS were demonstrated on human breast cancer cells and zebrafish embryo cells. This work provides a systematic approach for automated intracellular sensing for adherent cells, laying a solid foundation for high-throughput detection, diagnosis, and classification of different forms of biochemical reactions within single cells.


The Inverse Problems for Computational Psychophysiology: Opinions and Insights