ZnO and Aluminum doped ZnO nanoparticles (Al/ZnO NPs) were successfully synthesized by the sol-gel method. Together with the effect of calcination temperatures (200, 300 and 400 °C) and Al dosage (1%, 3%, 5% and 10%) on structural, morphological and optical properties of Al/ZnO NPs, their photocatalytic degradation of methyl orange (MO) dye was investigated. The calcination temperatures at 200, 300 and 400 °C in forming structure of ZnO NPs led to spherical nanoparticle, nanorod and nanoflake structures with a well-crystalline hexagonal wurtzite, respectively. The ZnO NPs calcined at 200 °C exhibited the highest specific surface area and light absorption property, leading to the MO removal efficiency of 80% after 4 h under the Ultraviolet (UV) light irradiation. The MO removal efficiency was approximately two times higher than the nanoparticles calcined at 400 °C. Furthermore, the 5% Al/ZnO NPs exhibited superior MO removal efficiency of 99% in only 40 min which was approximately 20 times enhancement in photocatalytic activity compared to pristine ZnO under the visible light irradiation. This high degradation performance was attributed to the extended light absorption, narrowed band gap and effective suppression of electron–hole recombination through an addition of Al metal.

Recent advancements in exoskeleton technology, both passive and active, are driven by the need to enhance human capabilities across various industries as well as the need to provide increased safety for the human worker. This review paper examines the sensors, actuators, mechanisms, design, and applications of passive and active exoskeletons, providing an in-depth analysis of various exoskeleton technologies. The main scope of this paper is to examine the recent developments in the exoskeleton developments and their applications in different fields and identify research opportunities in this field. The paper examines the exoskeletons used in various industries as well as research-level prototypes of both active and passive types. Further, it examines the commonly used sensors and actuators with their advantages and disadvantages applicable to different types of exoskeletons. Communication protocols used in different exoskeletons are also discussed with the challenges faced.

Electromyography (EMG) has emerged as a vital tool in the development of wearable robotic exoskeletons, enabling intuitive and responsive control by capturing neuromuscular signals. This review presents a comprehensive analysis of the EMG signal processing pipeline tailored to exoskeleton applications, spanning signal acquisition, noise mitigation, data preprocessing, feature extraction, and control strategies. Various EMG acquisition methods, including surface, intramuscular, and high-density surface EMG, are evaluated for their applicability in real-time control. The review addresses prevalent signal quality challenges, such as motion artifacts, power-line interference, and crosstalk. It also highlights both traditional filtering techniques and advanced methods, such as wavelet transforms, empirical mode decomposition, and adaptive filtering. Feature extraction techniques are explored to support pattern recognition and motion classification. Machine learning approaches are examined for their roles in pattern recognition-based and hybrid control architectures. This article emphasizes muscle synergy analysis and adaptive control algorithms to enhance personalization and fatigue compensation, followed by the benefits of multimodal sensing and edge computing in addressing the limitations of EMG-only systems. By focusing on EMG-driven strategies through signal processing, machine learning, and sensor fusion innovations, this review bridges gaps in human–machine interaction, offering insights into improving the precision, adaptability, and robustness of next generation exoskeletons.

Exoskeletons possess a high potential for assisting the human workforce while eliminating or reducing the risk of Work-Related Musculoskeletal Disorders (WMSDs). However, their usage in agricultural work, where there is a plethora of reported WMSD cases, seems limited. Since agricultural tasks are complex and performed in harsh environments, developing novel exoskeleton-based solutions could be challenging. However, commercial exoskeletons are already being used in various other industries, such as logistics, military, medicine, and manufacturing. Thus, it is expected that those existing exoskeleton solutions could be applied to agricultural tasks. Nevertheless, prior to implementation, assessing the feasibility, efficacy, and necessary modifications for these exoskeletons is imperative to supporting agricultural activities prone to WMSDs. In this review, prevalent exoskeletons documented in scientific literature are identified, and their potential relevance to agricultural tasks with elevated WMSD risks is evaluated. The review further highlights and deliberates on exoskeletons that could be applicable in an agricultural context. This comprehensive examination serves as a foundational step towards the conceptualization and development of exoskeleton-based approaches tailored explicitly for agricultural tasks.