Development and Evaluation of Refreshable Braille Display and Active Touch-Reading System for Digital Reading of the Visually Impaired.

The traditional way of reading through Braille books is constraining the reading experience of blind or visually impaired (BVI) in the digital age. In order to improve the reading convenience of BVI, this paper proposes a low-cost and refreshable Braille display device, and solves the problems of high energy consumption and low latching force existing in existing devices. Further, the Braille display device was combined with the 3D Systems Touch device to develop an active Braille touch-reading system for digital reading of BVI with the help of the CHAI3D virtual environment. Firstly, according to the actual needs of BVI to touch and read the Braille dots, this paper utilizes the beam structure to provide a full latching function for the raised Braille dot without energy consumption. Through theoretical derivation and finite element analysis, the performance of the Braille dot actuator is optimized to provide sufficient feedback force and latching force for finger's touch-reading. Then, this paper designs a virtual Braille interactive environment based on the CHAI3D, and combines the sense of touch with audio to effectively improve the recognition accuracy and reading efficiency of BVI for Braille through the multi-modal presentation of Braille information. The performance test results of the device show that the average lifting force of the Braille dot actuator is 101.67 mN, the latching force is over 5 N, and the average refresh frequency is 17.1 Hz, which meets the touch-reading needs of BVI. User experiments show that the average accuracy rate of BVI subjects in identifying digitized Braille is 95.5%, and subjects have a high subjective evaluation of the system.

Stretchable, Flexible, Breathable, Self-Adhesive Epidermal Hand sEMG Sensor System.

Hand function rehabilitation training typically requires monitoring the activation status of muscles directly related to hand function. However, due to factors such as the small surface area for hand-back electrode placement and significant skin deformation, the continuous real-time monitoring of high-quality surface electromyographic (sEMG) signals on the hand-back skin still poses significant challenges. We report a stretchable, flexible, breathable, and self-adhesive epidermal sEMG sensor system. The optimized serpentine structure exhibits a sufficient stretchability and filling ratio, enabling the high-quality monitoring of signals. The carving design minimizes the distribution of connecting wires, providing more space for electrode reservation. The low-cost fabrication design, combined with the cauterization design, facilitates large-scale production. Integrated with customized wireless data acquisition hardware, it demonstrates the real-time multi-channel sEMG monitoring capability for muscle activation during hand function rehabilitation actions. The sensor provides a new tool for monitoring hand function rehabilitation treatments, assessing rehabilitation outcomes, and researching areas such as prosthetic control.

Soft pneumatic muscles for post-stroke lower limb ankle rehabilitation: leveraging the potential of soft robotics to optimize functional outcomes.

Introduction: A soft pneumatic muscle was developed to replicate intricate ankle motions essential for rehabilitation, with a specific focus on rotational movement along the x-axis, crucial for walking. The design incorporated precise geometrical parameters and air pressure regulation to enable controlled expansion and motion. Methods: The muscle's response was evaluated under pressure conditions ranging from 100-145 kPa. To optimize the muscle design, finite element simulation was employed to analyze its performance in terms of motion range, force generation, and energy efficiency. An experimental platform was created to assess the muscle's deformation, utilizing advanced techniques such as high-resolution imaging and deep-learning position estimation models for accurate measurements. The fabrication process involved silicone-based materials and 3D-printed molds, enabling precise control and customization of muscle expansion and contraction. Results: The experimental results demonstrated that, under a pressure of 145 kPa, the y-axis deformation (y-def) reached 165 mm, while the x-axis and z-axis deformations were significantly smaller at 0.056 mm and 0.0376 mm, respectively, highlighting the predominant elongation in the y-axis resulting from pressure actuation. The soft muscle model featured a single chamber constructed from silicone rubber, and the visually illustrated and detailed geometrical parameters played a critical role in its functionality, allowing systematic manipulation to meet specific application requirements. Discussion: The simulation and experimental results provided compelling evidence of the soft muscle design's adaptability, controllability, and effectiveness, thus establishing a solid foundation for further advancements in ankle rehabilitation and soft robotics. Incorporating this soft muscle into rehabilitation protocols holds significant promise for enhancing ankle mobility and overall ambulatory function, offering new opportunities to tailor rehabilitation interventions and improve motor function restoration.

Multifunctional Biosensing Platform Based on Nickel-Modified Laser-Induced Graphene.

Nickel plating electrolytes prepared by using a simple salt solution can achieve nickel plating on laser-induced graphene (LIG) electrodes, which greatly enhances the electrical conductivity, electrochemical properties, wear resistance, and corrosion resistance of LIG. This makes the LIG-Ni electrodes well suited for electrophysiological, strain, and electrochemical sensing applications. The investigation of the mechanical properties of the LIG-Ni sensor and the monitoring of pulse, respiration, and swallowing confirmed that the sensor can sense insignificant deformations to relatively large conformal strains of skin. Modulation of the nickel-plating process of LIG-Ni, followed by chemical modification, may allow for the introduction of glucose redox catalyst Ni2Fe(CN)6 with interestingly strong catalytic effects, which gives LIG-Ni impressive glucose-sensing properties. Additionally, the chemical modification of LIG-Ni for pH and Na+ monitoring also confirmed its strong electrochemical monitoring potential, which demonstrates application prospects in the development of multiple electrochemical sensors for sweat parameters. A more uniform LIG-Ni multi-physiological sensor preparation process provides a prerequisite for the construction of an integrated multi-physiological sensor system. The sensor was validated to have continuous monitoring performance, and its preparation process is expected to form a system for non-invasive physiological parameter signal monitoring, thus contributing to motion monitoring, disease prevention, and disease diagnosis.

Growth of carbon nanotubes over carbon nanofibers catalyzed by bimetallic alloy nanoparticles as a bifunctional electrode for Zn-air batteries.

Design of economical, large-scale, stable, and highly active bifunctional electrocatalysts for Zn-air batteries with enhanced oxygen reduction and oxygen evolution performance is needed. Herein, a series of electrocatalysts were facilely fabricated where in situ formed bimetallic nanoparticles aided in the growth of carbon nanotubes over carbon nanofibers (MM'-CNT@CNF) during thermal treatment. Different combinations of Fe, Ni, Co and Mn metals and melamine as precursor for CNT growth were investigated. The synergistic interaction between bimetallic nanoparticles and N-doped carbon results in greatly improved bifunctional catalytic activity for both oxygen reduction and evolution reactions (ORR, OER) using FeNi-CNT@CNF as catalyst. The half-wave potential (0.80 V vs. RHE) for FeNi-CNT@CNF for ORR was close to that of Pt/C (0.79 V vs. RHE), meanwhile its stability was superior to Pt/C. Likewise, during OER, the FeNi-CNT@CNF reached a current density of 10 mA cm-2 at a rather low overpotential of 310 mV vs. RHE compared to benchmark RuO2 (410 mV). The rechargeable Zn-air prototype battery using FeNi-CNT@CNF as an air electrode outperformed the mixture of Pt/C and RuO2 with discharge/charge overpotential of 0.61 V, power density of 118 mW cm-2 at 10 mA cm-2 and an improved cycling stability over 108 hours.

Extended Control with Hybrid Gaze-BCI for Multi-Robot System under Hands-occupied Dual-tasking.

Currently there still remains a critical need of human involvements for multi-robot system (MRS) to successfully perform their missions in real-world applications, and the hand-controller has been commonly used for the operator to input MRS control commands. However, in more challenging scenarios involving concurrent MRS control and system monitoring tasks, where the operator's both hands are busy, the hand-controller alone is inadequate for effective human-MRS interaction. To this end, our study takes a first step toward a multimodal interface by extending the hand-controller with a hands-free input based on gaze and brain-computer interface (BCI), i.e., a hybrid gaze-BCI. Specifically, the velocity control function is still designated to the hand-controller that excels at inputting continuous velocity commands for MRS, while the formation control function is realized with a more intuitive hybrid gaze-BCI, rather than with the hand-controller via a less natural mapping. In a dual-task experimental paradigm that simulated the hands-occupied manipulation condition in real-world applications, operators achieved improved performance for controlling simulated MRS (average formation inputting accuracy increases 3%, average finishing time decreases 5 s), reduced cognitive load (average reaction time for secondary task decreases 0.32 s) and perceived workload (average rating score decreases 15.84) with the hand-controller extended by the hybrid gaze-BCI, over those with the hand-controller alone. These findings reveal the potential of the hands-free hybrid gaze-BCI to extend the traditional manual MRS input devices for creating a more operator-friendly interface, in challenging hands-occupied dual-tasking scenarios.

Experimental Research on Seismic Behavior of Seismic-Damaged Double-Deck Viaduct Frame Pier Strengthened with CFRP and Enveloped Steel.

This paper investigates the seismic behavior of a seismic-damaged double-deck viaduct frame pier (DVFP) strengthened with CFRP and enveloped steel, four strengthened DVFP specimens with different degrees of initial damage were tested under quasi-static cyclic loading. Based on the test results, the hysteretic behavior, the stiffness and strength degradation, crack propagation, and failure mechanism were firstly analyzed. Then, the damage indexes of the tested specimens were calculated with different models to evaluate the seismic strengthening performance. Results of this study show that CFRP and enveloped steel strengthening could effectively improve the strength and ductility of pre-damaged DVFPs. The ultimate load, the failure displacement and the displacement ductility of the moderately damaged specimen after being strengthened were found to increase by 120.74%, 35% and 32.33%, respectively. For the severely damaged specimens with CFRP and enveloped steel strengthening, the figures were 105.36%, 25.98% and 31.41%, respectively. The research results can provide reference for the hybrid strengthening application of seismic-damaged DVFP.

Object Localization Assistive System Based on CV and Vibrotactile Encoding.

Intelligent assistive systems can navigate blind people, but most of them could only give non-intuitive cues or inefficient guidance. Based on computer vision and vibrotactile encoding, this paper presents an interactive system that provides blind people with intuitive spatial cognition. Different from the traditional auditory feedback strategy based on speech cues, this paper firstly introduces a vibration-encoded feedback method that leverages the haptic neural pathway and enables the users to interact with objects other than manipulating an assistance device. Based on this strategy, a wearable visual module based on an RGB-D camera is adopted for 3D spatial object localization, which contributes to accurate perception and quick object localization in the real environment. The experimental results on target blind individuals indicate that vibrotactile feedback reduces the task completion time by over 25% compared with the mainstream voice prompt feedback scheme. The proposed object localization system provides a more intuitive spatial navigation and comfortable wearability for blindness assistance.

Comparative Experimental Research on Haptic Display Methods of Virtual Surface Shape Based on Touch Screen.

With the wide application of touch screen technology in daily life, more and more studies have tried to use touch screen as a carrier to convey the surface shape features of virtual objects to people. Current studies have proposed methods such as direct height mapping and haptic illusion based on lateral force to display the geometric shape of virtual surfaces on the touch screen. However, whether there are differences in the performance of these methods in displaying the shape features, and whether the lateral force-based haptic illusion can be used to display the shape features of complex surfaces, has not been fully explored. Aiming at this situation, in this article, we carry out user experiments on two regular shapes and eight natural images under displacement field and two types of lateral force fields with the help of three haptic devices previously designed. We also evaluate the effect of image smoothing on users' perception of natural image shape features. Experimental results show that the current shape display devices and methods that can simulate the lateral force field proposed by (Minsky et al., 1990) cannot achieve the display effect of the displacement field on complex shapes, and the shape display effect is the worst when only resistive lateral force feedback is employed. Nevertheless, since methods based on lateral force field, such as electrovibration, allow people to directly perceive the shape features of the virtual surface on the touch screen with their bare fingers, continuous research on this shape expression method still has a very attractive prospect.

Nano-Film-Forming Plugging Drilling Fluid and Bridging Cross-Linking Plugging Agent Are Used to Strengthen Wellbores in Complex Formations.

Lost circulation is one of the great challenges during the drilling process as it can not only increase the risk of drilling operations but also cause an increase in drilling costs, thus greatly affecting the drilling efficiency. Wellbore strengthening has been widely used to prevent lost circulation, which ultimately expands the mud density window by increasing the formation fracture pressure. This paper proposes a combination of "preventive" wellbore strengthening and "remedial" wellbore strengthening to prevent leakage and plug and stabilize wellbores by means of summarizing the characteristics of lost circulation and wellbore instability in the Hasan area. The formula of the bridging cross-linking plugging agent is determined by experiments as well slurry + 8-10% granular material + 3-5% fiber material + 2-4% elastic material + 0.5-1% cementing material. The formula of the nano-film-forming plugging drilling fluid is determined to be 3% bentonite + 0.2NaOH + 0.2% KPAM + 3% SMP + 1% PB-1 + 2% SMNA-1 + 2% lubricant SMLUB-1 + 1% modified nano-SiO2 particles. Then, the performance evaluation of the composite system is carried out by the high-temperature and high-pressure plugging simulation evaluation device. The results show that the bridging and cross-linking plugging agent can effectively block the 1-3 mm crack, the pressure-bearing capacity is greater than 10 MPa, and the anti-liquid return capacity is greater than 4 MPa. The nano-film-forming plugging drilling fluid has lower fluid loss and better rheological properties.

Exploring Biomimetic Stiffness Modulation and Wearable Finger Haptics for Improving Myoelectric Control of Virtual Hand.

The embodiment of virtual hand (VH) by the user is generally deemed to be important for virtual reality (VR) based hand rehabilitation applications, which may help to engage the user and promote motor skill relearning. In particular, it requires that the VH should produce task-dependent interaction behaviors from rigid to soft. While such a capability is inherent to humans via hand stiffness regulation and haptic interactions, yet it have not been successfully imitated by VH in existing studies. In this paper, we present a work which integrates biomimetic stiffness regulation and wearable finger force feedback in VR scenarios involving myoelectric control of VH. On one hand, the biomimetic stiffness modulation intuitively enables VH to imitate the stiffness profile of the user's hand in real time. On the other hand, the wearable finger force-feedback device elicits a natural and realistic sensation of external force on the fingertip, which provides the user a proper understanding of the environment for enhancing his/her stiffness regulation. The benefits of the proposed integrated system were evaluated with eight healthy subjects that performed two tasks with opposite stiffness requirements. The achieved performance is compared with reduced versions of the integrated system, where either biomimetic impedance control or wearable force feedback is excluded. The results suggest that the proposed integrated system enables the stiffness of VH to be adaptively regulated by the user through the perception of interaction torques and vision, resulting in task-dependent behaviors from rigid to soft for VH.

StereoPilot: A Wearable Target Location System for Blind and Visually Impaired Using Spatial Audio Rendering.

Vision loss severely impacts object recognition and spatial cognition for limited vision individuals. It is a challenge to compensate for this using other sensory modalities, such as touch or hearing. This paper introduces StereoPilot, a wearable target location system to facilitate the spatial cognition of BVI. Through wearing a head-mounted RGB-D camera, the 3D spatial information of the environment is measured and processed into navigation cues. Leveraging spatial audio rendering (SAR) technology, it allows the navigation cues to be transmitted in a type of 3D sound from which the sound orientation can be distinguished by the sound localization instincts in humans. Three haptic and auditory display strategies were compared with SAR through experiments with three BVI and four sighted subjects. Compared with mainstream speech instructional feedback, the experimental results of the Fitts' law test showed that SAR increases the information transfer rate (ITR) by a factor of three for spatial navigation, while the positioning error is reduced by 40%. Furthermore, SAR has a lower learning effect than other sonification approaches such as vOICe. In desktop manipulation experiments, StereoPilot was able to obtain precise localization of desktop objects while reducing the completion time of target grasping tasks in half as compared to the voice instruction method. In summary, StereoPilot provides an innovative wearable target location solution that swiftly and intuitively transmits environmental information to BVI individuals in the real world.

Finger Movement Recognition via High-Density Electromyography of Intrinsic and Extrinsic Hand Muscles.

Surface electromyography (sEMG) is commonly used to observe the motor neuronal activity within muscle fibers. However, decoding dexterous body movements from sEMG signals is still quite challenging. In this paper, we present a high-density sEMG (HD-sEMG) signal database that comprises simultaneously recorded sEMG signals of intrinsic and extrinsic hand muscles. Specifically, twenty able-bodied participants performed 12 finger movements under two paces and three arm postures. HD-sEMG signals were recorded with a 64-channel high-density grid placed on the back of hand and an 8-channel armband around the forearm. Also, a data-glove was used to record the finger joint angles. Synchronisation and reproducibility of the data collection from the HD-sEMG and glove sensors were ensured. The collected data samples were further employed for automated recognition of dexterous finger movements. The introduced dataset offers a new perspective to study the synergy between the intrinsic and extrinsic hand muscles during dynamic finger movements. As this dataset was collected from multiple participants, it also provides a resource for exploring generalized models for finger movement decoding.

Janus Hollow Nanofiber with Bifunctional Oxygen Electrocatalyst for Rechargeable Zn-Air Battery.

Zn-air battery technologies have received increasing attention, while the application is hindered by the sluggish kinetics of the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). In order to explore an efficient method to fabricate a high-performance electrocatalyst via modification of advanced nanostructure, a coaxial electrospinning method with in-situ synthesis and subsequent carbonization to construct 3D flexible Janus-like electrocatalysts is developed. The resulting Janus nanofibers have a unique core-shell hollow fiber structure, where NiFe alloy electrocatalysts supported by N-doped carbon nanobelt are located on the inner wall of the carbon layer, and leaf-like Co-N nanosheets are anchored on the outer wall of the carbon layer. As a result, the electrocatalyst exhibits excellent bifunctional catalytic performance for ORR and OER, demonstrating the small potential gap value of 0.73 V between the ORR half-wave potential and the OER potential at 10 mA cm-2 , which is even comparable to the mixed commercial noble catalyst with 20% Pt/C and RuO2 . The rechargeable Zn-air battery is constructed and displays a large open-circuit voltage of 1.44 V, high power density (130 mW cm-2 ) and energy density (874 Wh kg-1 ). This study provides a concept to synthesize and construct high performance bifunctional electrocatalysts.

New insight into degradation of chloramphenicol using a nanoporous Pd/Co3O4cathode: characterization and pathways analysis.

The growing chloramphenicol (CAP) in wastewater brought a serious threat to the activity of activated sludge and the spread of antibiotics resistance bacteria. In this study, a highly ordered nanoporous Co3O4layer on Co foil through anodization was prepared as cathode for nitro-group reduction and electrodeposited with Pd particles for dechlorination to reduce CAP completely. After 3 h treatment, almost 100% of CAP was reduced. Co2+ions in Co3O4served as catalytic sites for electrons transfer to CAP through a redox circle Co2+-Co3+-Co2+, which triggered nitro-group reduction at first. With the presence of Pd particles, more atomic H* were generated for dechlorination, which increased 22% of reduction efficiency after 3 h treatment. Therefore, a better capacity was achieved by Pd/Co3O4cathode (K = 0.0245 min-1,Kis reaction constant) than by other cathodes such as Fe/Co3O4(K = 0.0182 min-1), Cu/Co3O4(K = 0.0164 min-1), and pure Co3O4(K = 0.0106 min-1). From the proposed reaction pathway, the ultimate product was carbonyl-reduced AM (dechlorinated aromatic amine product of CAP) without antibacterial activity, which demonstrated this cathodic technology was a feasible way for wastewater pre-treatment.

Research on the Method of Displaying the Contour Features of Image to the Visually Impaired on the Touch Screen.

Conveying image information to the blind or visually impaired (BVI) is an important means to improve their quality of life. The touch screen devices used daily are the potential carriers for BVI to perceive image information through touch. However, touch screen devices also have the disadvantages of limited computing power and lack of rich tactile experience. In order to help BVI to access images conveniently through the touch screen, we built an image contour display system based on vibrotactile feedback. In this paper, an image smoothing algorithm based on convolutional neural network that can run quickly on the touch screen device is first used to preprocess the image to improve the effect of contour extraction. Then, based on the haptic physiological characteristics of human beings, this paper proposes a method of using the improved MH-Pen to guide the BVI to perceive image contour on the touch screen. This paper introduces the extraction and expression methods of image contours in detail, and compares and analyzes the effects of the subjects' perception of image contours in two haptic display modes through two types of user experiments. The experimental results show that the image smoothing algorithm is useful and necessary to help obtain the main contour of the image and to ensure the real-time display of the contour, and the contour expression method based on the motion direction guidance helps the subjects recognize the contour of the image more effectively.

Towards Integration of Domain Knowledge-Guided Feature Engineering and Deep Feature Learning in Surface Electromyography-Based Hand Movement Recognition.

As a machine-learning-driven decision-making problem, the surface electromyography (sEMG)-based hand movement recognition is one of the key issues in robust control of noninvasive neural interfaces such as myoelectric prosthesis and rehabilitation robot. Despite the recent success in sEMG-based hand movement recognition using end-to-end deep feature learning technologies based on deep learning models, the performance of today's sEMG-based hand movement recognition system is still limited by the noisy, random, and nonstationary nature of sEMG signals and researchers have come up with a number of methods that improve sEMG-based hand movement via feature engineering. Aiming at achieving higher sEMG-based hand movement recognition accuracies while enabling a trade-off between performance and computational complexity, this study proposed a progressive fusion network (PFNet) framework, which improves sEMG-based hand movement recognition via integration of domain knowledge-guided feature engineering and deep feature learning. In particular, it learns high-level feature representations from raw sEMG signals and engineered time-frequency domain features via a feature learning network and a domain knowledge network, respectively, and then employs a 3-stage progressive fusion strategy to progressively fuse the two networks together and obtain the final decisions. Extensive experiments were conducted on five sEMG datasets to evaluate our proposed PFNet, and the experimental results showed that the proposed PFNet could achieve the average hand movement recognition accuracies of 87.8%, 85.4%, 68.3%, 71.7%, and 90.3% on the five datasets, respectively, which outperformed those achieved by the state of the arts.

Semi-Autonomous Robotic Arm Reaching With Hybrid Gaze-Brain Machine Interface.

Recent developments in the non-muscular human-robot interface (HRI) and shared control strategies have shown potential for controlling the assistive robotic arm by people with no residual movement or muscular activity in upper limbs. However, most non-muscular HRIs only produce discrete-valued commands, resulting in non-intuitive and less effective control of the dexterous assistive robotic arm. Furthermore, the user commands and the robot autonomy commands usually switch in the shared control strategies of such applications. This characteristic has been found to yield a reduced sense of agency as well as frustration for the user according to previous user studies. In this study, we firstly propose an intuitive and easy-to-learn-and-use hybrid HRI by combing the Brain-machine interface (BMI) and the gaze-tracking interface. For the proposed hybrid gaze-BMI, the continuous modulation of the movement speed via the motor intention occurs seamlessly and simultaneously to the unconstrained movement direction control with the gaze signals. We then propose a shared control paradigm that always combines user input and the autonomy with the dynamic combination regulation. The proposed hybrid gaze-BMI and shared control paradigm were validated for a robotic arm reaching task performed with healthy subjects. All the users were able to employ the hybrid gaze-BMI for moving the end-effector sequentially to reach the target across the horizontal plane while also avoiding collisions with obstacles. The shared control paradigm maintained as much volitional control as possible, while providing the assistance for the most difficult parts of the task. The presented semi-autonomous robotic system yielded continuous, smooth, and collision-free motion trajectories for the end effector approaching the target. Compared to a system without assistances from robot autonomy, it significantly reduces the rate of failure as well as the time and effort spent by the user to complete the tasks.

Systematic review of resecting primary tumor in MNETs patients with unresectable liver metastases.

BACKGROUND: Treatment for midgut neuroendocrine tumor patients with unresectable liver metastasis has long been a controversial issue. This system review aims to summarize existing evidence concerning the value of primary tumor resection in this group of patients. RESULTS: 8 cohort studies were identified for qualitative analysis. None of them strictly met with the inclusion criteria and meta-analysis was impossible. There was a tendency towards better overall survival for the primary tumor resected group in all 8 studies, in which 6 demonstrated significant difference. Progression free survival to liver disease was prolonged and less patients died of liver failure in the resected group. METHODS: MEDLINE, EMBASE and CENTRAL were searched until 2016/7/4 for relevant studies, with primary outcome being overall survival, and secondary outcome being progression free survival, cause of death and symptom relief. CONCLUSIONS: Current evidence supports resection of primary tumor for midgut neuroendocrine tumor patients with liver metastases, but randomized controlled trials are required to reach a final conclusion.

CEA Level, Radical Surgery, CD56 and CgA Expression Are Prognostic Factors for Patients With Locoregional Gastrin-Independent GNET.

Gastrin-independent gastric neuroendocrine tumors (GNETs) are highly malignant. Radical resections and lymphadenectomy are considered to be the only possible curative treatment for these tumors. However, the prognosis of gastrin-independent GNETs is not well defined. In this study, we identified prognostic factors of locoregional gastrin-independent GNETs.All patients diagnosed with locoregional gastrin-independent GNETs between 2000 and 2014 were included in this retrospective study. Clinical characteristics, blood tests, pathological characteristics, treatments, and follow-up data of the patients were collected and analyzed.Of the 66 patients diagnosed with locoregional gastrin-independent GNETs, 57 (86.4%) received radical resections, 7 (10.6%) with palliative resection, 1 (1.5%) with gastrojejunostomy, and 1 (1.5%) with exploration surgeries. The median survival time for these patients was 19.0 months (interquartile range, 11.0-38.0). The 1-, 3-, and 5-year survival rates were 72%, 34%, and 28%, respectively. Multivariate analysis indicated that carcinoembryonic antigen (CEA) level (P = 0.04), radical resection (P = 0.04), and positive Cluster of Differentiation 56 (CD56) expression (P = 0.016) were significant prognostic factors on overall survival rate. Further univariate and multivariate analysis of 57 patients who received radical resections found that CgA expression (P = 0.35) and CEA level (P = 0.33) are independent prognostic factors.Gastrin-independent GNETs had poor prognosis. Serum CEA level, radical surgery, CD56 and CgA expression are markers to evaluate the survival of patients with locoregional gastrin-independent GNETs.