Lifting patients is a demanding task for care providers. In addition, the number of patients is rising and the number of people with obesity is expanding. Current lifting aids are single purpose and time consuming to use. Exoskeletons can fulfill the demand for a versatile and easy to use lifting aid. A drawback of a typical exoskeleton is that in order to function correctly the axes need to be aligned to the human joints, which is time consuming. Furthermore, an exoskeleton for healthcare must reduce the reaction forces in the user while lifting. It is chosen to design an exoskeleton, which requires no adjustment and can cope with power enhancement. The goal of this paper is to design an exoske-leton that is fast, easy to use and reduces the reaction forces in the user. A design is proposed which easily fits different sized users. In addition the reaction forces in the human skeleton are eliminated. The model is tested by means of a demonstrator. Elastic tension elements are used as a gravity compensator. By reducing the potential energy fluctuation the required external input is reduced. Optimizing a number of design parameters leads to a calculated moment reduction of 98.8% and moment fluctuation reduction of 96.8%. This is the first exoskeleton to combine fast to use design with high-energy efficiency gravity compensation.

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An exoskeleton is a mechatronic system which has the goal of to ensure an extra strength when muscles of humans are affected and don’t achieve the driving force necessary. As structural exoskeleton are used orthotics and the prostheses. The orthosis is a medical device which is applied at the level of a body segment in the goal of prevention or correction the gap that segment. The prosthesis is a medical device which makes part of the biomechatronics field and which deals with the substitution a segment of the human body. In this paper it illustrate how to design a structural exoskeleton.

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Powered robotic exoskeletons used to assist in human locomotion require a lot of energy. The Walking Assist Machine Using Crutches (WAMC) is such an exoskeleton used to assist paraplegic people in walking. It uses telescopic links driven by linear actuators with electro motors and people wearing the device move crutches themselves. An evaluation was done to see if the implementation of springs could lead to a reduction in required motor energy. A computer simulation calculating the movement of such a configuration with springs indeed showed a reduction in required motor energy and also effected in a higher walking speed. The user had to spend more effort to swing the crutches.

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The purpose of this study is to develop a pneumatic artificial muscle with a high contractile rate to realize a required performance in a power assist device. The developed muscle is constructed with two nylon bands and an expansion unit. The generated force from the expansion unit is converted to a contraction force by the nylon band. This artificial muscle can be realized the high contrac-tile rate. In this paper, the structure and the characteristics of the developed muscle are described, and then the application of this artificial muscle is discussed.

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Moving a brain–computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI are demonstrated through the realization and testing of a steady-state visual evoked potential (SSVEP)-based BCI. This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs. The results of this study showed that the performance of the proposed cell-phone-based platform was comparable, in terms of the information transfer rate, with other BCI systems using bulky commercial EEG systems and personal computers. To the best of our knowledge, this study is the first to demonstrate a truly portable, cost-effective and miniature cell-phone-based platform for online BCIs.

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