Search results

The purpose of this paper is to develop a novel wearable rehabilitation robotic hand driven by Pneumatic Muscle‐Torsion Spring (PM‐TS) for finger therapy. PM has complex nonlinear dynamics, which makes PM modelling difficult. To realize high‐accurate tracking for the robotic hand, an Echo State Network (ESN)‐based PID adaptive controller is proposed, even though the plant model is unknown.

To drive a single joint of rehabilitation robotic hand, the paper proposes a new PM‐TS actuator comprising a Pneumatic Muscle (PM) and a Torsion Spring (TS). Based on the novel actuator, a wearable robotic hand is designed. By employing the model‐free approximation capability of ESN, the RLSESN based PID adaptive controller is presented for improving the trajectory tracking performance of the rehabilitation robotic hand. An ESN together with Recursive Least Square (RLS) is called a RLSESN, where the ESN output weight matrix is updated by the online RLS learning algorithm.

Practical experiments demonstrate the validity of the PM‐TS actuator and indicate that the performance of the RLSESN based PID adaptive controller is better than that of the conventional PID controller. In addition, they also verify the effectiveness of the proposed rehabilitation robotic hand.

A new PM‐TS actuator configuration that uses a PM and a torsion spring for bi‐directional movement of joint is presented. By utilizing the new PM‐TS actuator, a novel wearable rehabilitation robotic hand for finger therapy is designed. Based on the unknown plant model, the RLSESN_PID controller is proposed to attain satisfactory performance.

Due to consumption changes in the post-pandemic era, the production safety of agricultural products is affecting global consumers. This paper constructs an evaluation index of the agricultural Internet of things (IOT) traceability system and evaluates it using the dynamic hesitant-fuzzy linguistic term sets (HFLTS)-based DEMATEL method to improve agricultural supply-chain links and improve production quality.

The agricultural IOT traceability index system is constructed using the literature and expert interviews; it comprises 6 first-level indices and 20 second-level indices. The agricultural IOT traceability system is evaluated using the dynamic HFLTS-DEMATEL method.

Producers' awareness of agricultural-production safety (A11) has the most significant impact on production and processing links, while warehouse location and storage capacity (A31) have the largest impact on the circulation link. Inspection authenticity and transparency and quarantine information (A41) have the largest impact on the detection-consumption link. The extent to which the traceability-platform construction is complete (A62) has the largest impact on technical support.

The present paper may be limited to the era of post-pandemic, and it is hard to consider all the indices. Further research can broaden the research context and establish a more comprehensive index system.

The index system constructed in this study will surely help relevant regulatory authorities in China to promote the construction of agricultural IOT traceability system and establish a unified standard, so as to provide a basis for future developers to enter the field. Accordingly, it also can help every subject to identify the key indices of each process in the agricultural-product supply chain and guide relevant departments to conduct targeted information tracking and management. The consumers could also understand the standards of traceable agricultural products and effectively protect their own rights and interests.

The existing literature does not provide an objective, unified standard for measuring a decentralized traceability system or identifying key processes. This study therefore proposes a new evaluation index system and uses a dynamic evaluation method to determine the importance of key indices. This study identifies the most important indices in each process, making it possible to discover, improve, and enhance the quality of agricultural products at a practical level.

This paper aims at assessing the impact of institutional and cultural distances and trade barriers on ASEAN's trade efficiency using a panel data set of 65 countries for the period 2006–2017.

First, the authors applied an improved version of the stochastic frontier model to estimate the trade efficiency scores. After that, we used the system generalized method of moment (GMM) estimator to investigate the impacts of institutional and cultural distances on ASEAN's trade efficiency.

The results show that the trade efficiency of ASEAN countries with the rest of the world (ROW) is moderate, ranging from 0.561 to 0.612, but shows a downward trend. This result indicates that considerable trade potential exists between ASEAN countries and ROW. Institutional and cultural distances, as well as the trade barriers, negatively affect ASEAN's trade efficiency. Efforts to reduce differences in institutions and cultures and to promote trade liberalization are vital remedies for ASEAN countries to turn potentials into actual trade performance.

This study contributes to the existing literature in three different ways. First, this is the first study on the impact of the differences between internal and external characteristics on trade efficiency, specifically, the impact of institutional and cultural distances on ASEAN's trade efficiency. Second, to obtain accurate efficiency scores, the authors use an improved version of the stochastic frontier model proposed by Karakaplan (2018), which can control the problem of endogeneity. Third, in quantifying the determinants of trade efficiency, the authors apply a system GMM estimator, which allows us to overcome the problems of endogeneity, measurement errors, and omitted variables.

The purpose of this paper is to review the challenges present in the development of hand exoskeletons powered by pneumatic artificial muscles. This paper also presents the development of a novel strain sensor and its application in a five‐fingered hand exoskeleton.

The issues of current hand exoskeletons powered by pneumatic artificial muscles are examined by studying the artificial muscles and the human hand anatomy. Traditional sensors are no longer suitable for applications in hand exoskeletons. A novel strain sensor was developed by depositing a conducting polymer called polypyrrole onto a natural rubber substrate through vapor phase polymerization and is used in the authors' five‐fingered hand exoskeleton.

The error of measurements from the polypyrrole strain sensor in controlling the actuation of pneumatic artificial muscles is within 1.5 mm. The small physical size and weight of the novel polypyrrole strain sensor also helped to keep the exoskeleton's profile (less than 20 mm) and total weight low (<1 kg).

The novel strain sensor allows the realization of hand exoskeletons that are lightweight, portable and low profile. This improves the comfort and practicality of hand exoskeletons to allow their usage outside the research environment.