Researchers have given attention to lower limb exoskeletons in recent years. Lower limb exoskeletons have been designed, prototype tested through experiments, and even produced. In general, lower limb exoskeletons have two different objectives: (1) rehabilitation and (2) assisting human work activities. Referring to these objectives, researchers have iteratively improved lower limb exoskeleton designs, especially in the location of actuators. Some of these devices use actuators, particularly on hips, ankles or knees of the users. Additionally, other devices employ a combination of actuators on multiple joints. In order to provide information about which actuator location is more suitable; a review study on the design of actuator locations is presented in this paper. The location of actuators is an important factor because it is related to the analysis of the design and the control system. This factor affects the entire lower limb exoskeleton’s performance and functionality. In addition, the disadvantages of several types of lower limb exoskeletons in terms of actuator locations and the challenges of the lower limb exoskeleton in the future are also presented in this paper.

Teleoperation can allow an operator to control a robot remotely in inaccessible and hostile places. To achieve more dexterous control of a tele-operated robot some researchers are developing user interfaces equipped with vision and tactile feedback. 3D visual perception and tactile feedback can also assist the operator to feel immersed in the robot's environment and embodied within the robot to some extent. Most existing tactile feedback systems use electro-mechanical actuators and linkages. However, these systems are complex, cumbersome and consequently make it difficult for the operator feel embodied within the robot. To improve on these drawbacks, this paper introduces an immersive teleoperation system comprised of a 3D stereo vision head set combined with an electro-tactile feedback system. Our electro-tactile feedback system is compact, nonmechanical and versatile. Experimental results are provided which show how this form of immersive 3D perception and tactile feedback system can enable the user to achieve more dexterous control of a robot arm by enabling the operator to effectively see what robot sees and experience what the robot feels while performing work with the robot.

Tactile feedback from a remotely controlled robotic arm can facilitate certain tasks by enabling the user to experience tactile or force sensations from the robot's interaction with the environment. However, equipping both the robot and the user with tactile sensing and feedback systems can be complex, expensive, restrictive and application specific. This paper introduces a new tele-operation haptic feedback method involving electro-tactile feedback. This feedback system is inexpensive, easy to setup and versatile in that it can provide the user with a diverse range of tactile sensations and is suitable for a variety of tasks. We demonstrate the potential of our electro-tactile feedback system by providing experimental results showing how electro-tactile feedback from a tele-operated robotic arm equipped with range sensors can help with avoiding obstacles in cluttered workspace. We also show how interactive tasks, like placing a peg in a hole, can be facilitated with electro-tactile feedback from force sensors.

To achieve effective interaction between a human and a computing device or machine, adequate feedback from the computing device or machine is required. Recently, haptic feedback is increasingly being utilised to improve the interactivity of the Human Computer Interface (HCI). Most existing haptic feedback enhancements aim at producing forces or vibrations to enrich the user's interactive experience. However, these force and/or vibration actuated haptic feedback systems can be bulky and uncomfortable to wear and only capable of delivering a limited amount of information to the user which can limit both their effectiveness and the applications they can be applied to. To address this deficiency, electrotactile feedback is used. This involves delivering haptic sensations to the user by electrically stimulating nerves in the skin via electrodes placed on the surface of the skin. This paper presents a review and explores the capability of electrotactile feedback for HCI applications. In addition, a description of the sensory receptors within the skin for sensing tactile stimulus and electric currents alsoseveral factors which influenced electric signal to transmit to the brain via human skinare explained.

This paper presents a comparison study between support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) classification for electromyography (EMG) signals. The EMG signals were acquired from seven hand common gestures. Sixteen features were extracted and were reduced into three new features set using principal component analysis (PCA). The new features set were divided into two for training and testing. The result of ANFIS classification is 91.43% which is higher than SVM classification that has been conducted in previous study.

Potential land drought mapping on Batam is needed to determine the distribution of areas that are very potential to the physical drought of the land. It is because the drought is always threatening on the long dry season. This research integrates remote sensing science with Geographic Information System (GIS). This research aims to map the distribution of land drought potential in Batam Island. The parameters used in this research are land use, Land Surface Temperature (LST), Potential dryness of land on the Batam island. The resulting map indicates the existence of five potential drought classes on the island of Batam. The area of very low drought potential is 2629.45 ha, mostly located in the Sungai Beduk sub-district. High drought potential with an area of 7081.39 ha is located in Sekupang sub-district. The distribution of very high land drought potential is in Batam city and Nongsa sub-district with area of 15600.12 ha. The coefficient of determination (R ²) is 0.6279. This indicates a strong positive relationship between field LST and modelled LST.