i-MYO: A multi-grasp prosthetic hand control system based on gaze movements, augmented reality, and myoelectric signals.

BACKGROUND: Controlling a multi-grasp prosthetic hand still remains a challenge. This study explores the influence of merging gaze movements and augmented reality in bionics on improving prosthetic hand control. METHODS: A control system based on gaze movements, augmented reality, and myoelectric signals (i-MYO) was proposed. In the i-MYO, the GazeButton was introduced into the controller to detect the grasp-type intention from the eye-tracking signals, and the proportional velocity scheme based on the i-MYO was used to control hand movement. RESULTS: The able-bodied subjects with no prior training successfully transferred objects in 91.6% of the cases and switched the optimal grasp types in 97.5%. The patient could successfully trigger the EMG to control the hand holding the objects in 98.7% of trials in around 3.2 s and spend around 1.3 s switching the optimal grasp types in 99.2% of trials. CONCLUSIONS: Merging gaze movements and augmented reality in bionics can widen the control bandwidth of prosthetic hand. With the help of i-MYO, the subjects can control a prosthetic hand using six grasp types if they can manipulate two muscle signals and gaze movement.

Quantitative proteomics analysis reveals the key proteins related to semen quality in Niangya yaks.

BACKGROUND: Proteins related to sperm motility and sperm morphology have an important impact on sperm function such as metabolism, motility and fertilisation etc. An understanding of the key proteins related to semen quality in Niangya yaks would help to provide support for breeding. However, the key proteins that affect semen quality in Niangya yaks remain unclear. METHODS: Herein, we applied tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry (LC‒MS/MS) to analyze the expression levels of sperm proteins in groups of high- and low-quality semen from Niangya yaks. And fifteen differentially expressed proteins (DEPs) were randomly selected for expression level validation by parallel reaction monitoring (PRM). RESULTS: Of the 2,092 quantified proteins, 280 were identified as DEPs in the high-quality group versus the low-quality group. Gene Ontology (GO) analysis revealed that in terms of biological pathways, the DEPs were mainly involved in metabolic processes, cell transformation processes, and single organism metabolic processes. In terms of cell composition, the DEPs were mainly located in the cell membrane, organelle, molecular complex. In terms of molecular functions, the most abundant functions of the DEPs were catalytic activity, binding activity, transport activity, and enzyme regulation activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the DEPs were mainly involved in the cytokine and cytokine receptor interaction, notch signaling pathway, lysine biosynthesis, renal function-related protein and proteasome pathway. From protein-protein interaction (PPI) analysis of DEPs involved in important pathways, 6 related proteins affecting the semen quality of Niangya yaks were identified. And the results of the PRM and TMT analysis were consistent. CONCLUSIONS: The differential sperm proteomic analysis of high- and low-quality semen from Niangya yaks, revealed 6 proteins (PSMC5, PSMD8, PSMB3, HSP90AA1, UGP2 and HSPB1), were mainly concentrated in energy production and metabolism, might play important roles in semen quality, which could serve as candidates for the selection and breeding of Niangya yaks.

Fingertip Proximity-Based Grasping Pattern Prediction of Transradial Myoelectric Prosthesis.

For transradial amputees, especially those with insufficient residual muscle activity, it is challenging to quickly obtain an appropriate grasping pattern for a multigrasp prosthesis. To address this problem, this study proposed a fingertip proximity sensor and a grasping pattern prediction method base on it. Rather than exclusively utilizing the EMG of the subject for the grasping pattern recognition, the proposed method used fingertip proximity sensing to predict the appropriate grasping pattern automatically. We established a five-fingertip proximity training dataset for five common classes of grasping patterns (spherical grip, cylindrical grip, tripod pinch, lateral pinch, and hook). A neural network-based classifier was proposed and got a high accuracy (96%) within the training dataset. We assessed the combined EMG/proximity-based method (PS-EMG) on six able-bodied subjects and one transradial amputee subject while performing the "reach-and-pick up" tasks for novel objects. The assessments compared the performance of this method with the typical pure EMG methods. Results indicated that able-bodied subjects could reach the object and initiate prosthesis grasping with the desired grasping pattern on average within 1.93 s and complete the tasks 7.30% faster on average with the PS-EMG method, relative to the pattern recognition-based EMG method. And the amputee subject was, on average, 25.58% faster in completing tasks with the proposed PS-EMG method relative to the switch-based EMG method. The results showed that the proposed method allowed the user to obtain the desired grasping pattern quickly and reduced the requirement for EMG sources.

A Repair Method for Damage in Aluminum Alloy Structures with the Cold Spray Process.

Aluminum alloy structures may be damaged due to wear or corrosion while in service. These damages will bring about huge financial costs, as well as a huge amount of energy consumption. There is an urgent need to search for an appropriate repair method in order to solve this problem. In this research, the cold spray process was used to repair the damages by using a mixture of powders with Al and Al2O3. A 7N01-T4 aluminum alloy plate with a factitious pit was regarded as the damaged sample. The microstructure, mechanical properties, and corrosion behavior were studied. The results showed that there were no visible perforative pores or cracks in the repaired areas. The microhardness of the repaired areas was in the range of 57.4-63.2 HV and was lower than that of the 7N01-T4 aluminum alloy. The tensile strength of the repaired samples was markedly improved compared with the unrepaired samples. The alternate immersion test results indicated that the repaired samples had the lowest rate of mass loss compared with 7N01-T4 and the unrepaired samples. After alternate immersion tests for 504 h, the repaired samples were covered with dense corrosion products. The repaired samples had a superior corrosion resistance compared to that of 7N01-T4. Thus, the cold spray process is a method of repairing damage in aluminum alloy structures.

Computer Vision-Based Grasp Pattern Recognition With Application to Myoelectric Control of Dexterous Hand Prosthesis.

Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achieve suitable grasps over various objects, a novel computer vision-based classification method assorting objects into different grasp patterns is proposed in this paper. This method can be applied in the autonomous control of the multi-fingered prosthetic hand, as it can help users rapidly complete "reach-and-pick up" tasks on various daily objects with low demand on the myoelectric control. Firstly, an RGB-D image database (121 objects) was established according to four important grasp patterns (cylindrical, spherical, tripod, and lateral). The image samples in the RGB-D dataset were acquired on a large variety of daily objects of different sizes, shapes, postures (16), as well as different illumination conditions (4) and camera positions (4). Then, different inputs and structures of the discrimination model (multilayer CNN) were tested in terms of the classification success rate through cross-validation. Our results showed that depth data play an important role in grasp pattern recognition. The bimodal data (Gray-D) integrating both grayscale and depth information about the objects can improve the classification accuracy acquired from the RGB images (> 10%) effectively. Within the database, the network could achieve the classification with high accuracy (98%); it also has a strong generalization capability on novel samples (93.9 ± 3.0%). We finally applied the method on a dexterous prosthetic hand and tested the whole system on performing the "reach-and-pick up" tasks. The experiments showed that the proposed computer vision-based myoelectric control method (Vision-EMG) could significantly improve the control effectiveness (6.4 s), with comparison to the traditional coding-based myoelectric control method (Coding-EMG, 13 s ).

Laser-CMT Hybrid Welding-Brazing of Al/Steel Butt Joint: Weld Formation, Intermetallic Compounds, and Mechanical Properties.

6A01-T5 aluminum alloy and SUS301L-DLT austenitic stainless steel sheets were welded by a laser-cold metal transfer (CMT) hybrid welding-brazing method with ER5183 filler wire. We researched the weld forming, intermetallic compounds, and mechanical character, which are influenced by laser power, wire feeding speed, and welding speed. Well-formed joints with uniformly distributed interface layers were obtained under certain parameters. The spreading and wetting distance on the steel upper surface increased initially and then decreased as the laser power increased, and increased progressively as the wire feeding speed increased or welding speed decreased. There were both Fe2Al5 and Fe4Al13 in the interfacial intermetallic compounds (IMCs) layer. The thickness was controlled to within 2.0-6.9 µm. The thickness of the IMCs layer increased as the heat input increased; however, the increasing rate decreased gradually. The tensile strength of the joints was not only completely dependent on the thickness of the IMCs, but also on the spreading and wetting distance on the steel surface. The highest tensile strength could reach up to 188.7 MPa, which is about 77.1% of that of the base aluminum alloy. The tensile sample fracture occurred at the IMCs layer, and regional metallurgical bonding happened in the interface layer.

Corrosion Behavior of SMA490BW Steel and Welded Joints for High-Speed Trains in Atmospheric Environments.

Currently, high-speed trains work under various atmospheric environments, and the bogie as a key component suffers serious corrosion. To investigate the corrosion behavior of bogies in industrial atmospheric environments, the periodic immersion wet/dry cyclic corrosion test for SMA490BW steel and automatic metal active gas (MAG) welded joints used for bogies was conducted in the present work. Corrosion weight loss rate, structure, and composition of rust layers as well as electrochemistry parameters were investigated. The results showed that the corrosion weight loss rate decreased with increasing corrosion time; furthermore, the corrosion weight loss rate of the welded joints was lower than that of SMA490BW steel. The XRD results showed that the rust layers formed on SMA490BW steel and its welded joints were mainly composed of α-FeOOH, γ-FeOOH, Fe2O3, and Fe3O4. The observation of surface morphology indicated that the rust layers of the welded joints were much denser and had a much finer microstructure compared with those of SMA490BW steel. After corrosion for 150 h, the corrosion potential of the welded joints with rust layers was higher than that of SMA490BW steel. In short, the welded joints exhibited better corrosion resistance than SMA490BW steel because of the higher content of alloy elements, as shown in this work.