Tremor is the most common of all involuntary movement. A lot of tremor patients in upper limb have serious difficulties performing daily living activities. We have developed the exoskeleton robot for tremor patient. In this paper, we focused on to develop a signal processing method to extract the voluntary movement from the electromyogram (EMG) signal in which the voluntary movement and tremor were mixed. We have researched about following two methods to recognize the voluntary movement: one is low pass filter and neural network (NN), the other is short time Fourier transform and NN. The low pass filter and neural network (NN) were effective for recognition of healthy subject’s movement. However, these methods were not applied to the tremor patient’s movement due to the characteristic oscillation of the EMG signal in the tremor patient. The proposed algorithm, which was composed of the short time Fourier transform and NN, dramatically improved the recognition rate of tremor patient’s movement. It was confirmed that the signal processing using STFT and NN is suitable for the recognition of the tremor patients. In future, we will develop more accurate algorithm based on this study, and finally conduct the clinical test to show effectiveness of our system.

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This paper is concerned with a control method of an exoskeletal ankle based on surface electromyographic (sEMG) signals. The sEMG signals of human ankle are introduced first. The muscles which are medial gastrocnemius(MG) and tibialis anterior(TA) are selected by experiments. Then a threshold method of controlling the exoskeletal ankle using sEMG signals is designed. A control system is realized. The sEMG signals are acquired, and sent to the computer. The computer deals with the sEMG signals and generates the control orders. The control orders are passed to the motor controller and drive the exoskeleton to move. At last, through experiment, the control method is verified and the effectiveness of the control system is proved.

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Chitin, extracted primarily from exoskeleton shellfish, is one of the most abundant biopolymer in the world. It is estimated to be produced annually almost as much as cellulose. The development of fishing activities in Morocco (coastline of 3500 km on both the Atlantic and the Mediterranean) induced an important fish industry waste. The aim of this work is to recover chitin, extracted from shellfish waste, and chitosan, produced by deacetylation of chitin, in the adsorption of organic pesticide 2,4-dichlorophenoxyacetate (2,4-D). The chitosan samples were prepared from α-chitin from crustacean shells and β-chitin from squid pens. The chitin deacetylation was carried out according to two methods using, respectively, as alkaline agent, the aqueous sodium hydroxide solution and anhydrous potassium hydroxide. The role of the source and of the process on the N-deacetylation reactions is confirmed. Characterization of chitin and chitosan was performed by infrared spectroscopy and nuclear magnetic resonance. The adsorption of 2,4-D by chitin and chitosan was performed at different pH values, the pesticide-adsorbent contact time and initial pesticide concentration. The adsorption is described by Langmuir-type isotherm and Freundlich-type isotherm. Recovery tests of 2,4-D confirm the initial interest in using chitin and chitosan as a depolluting agent.

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One of the principal guidelines in the design of haptic devices is to provide a suitable mechanical design that can improve control performance and the force-feedback fidelity. Unfortunately these guidelines may conflict with other design objectives (reflected mass, balancing, dexterity) as well as with specifications given by users and applications. For haptic interfaces based on tendon driven actuation it is highly important to achieve an accurate model of friction losses in the transmission system, in order to be able to compensate for them through an active control. In this paper it is reported a method for modeling and control complex tendon transmissions used for driving haptic devices and robots. The presented approach can operate in realtime with very low complexity; it is applicable to all kinds of serial manipulators and provides enough flexibility to allow identification of parameters and modeling of distributed friction phenomena all along the transmission. The approach has been implemented and tested on a 4 DOF exoskeleton system, the PERCRO L-EXOS.

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Background: Robotic devices are expected to be widely used in various applications including support for the independent mobility of the elderly with muscle weakness and people with impaired motor function as well as support for nursing care that involves heavy laborious work. We evaluated the effects of a hybrid assistive limb robot suit on the gait of stroke patients undergoing rehabilitation.
Methods: The study group comprised 16 stroke patients with severe hemiplegia. All patients underwent gait training. Four patients required assistance, and 12 needed supervision while walking. The stride length, walking speed and physiological cost index on wearing the hybrid assistive limb suit and a knee–ankle–foot orthosis were compared.
Results: The hybrid assistive limb suit increased the stride length and walking speed in 4 of 16 patients. The patients whose wal-king speed decreased on wearing the hybrid assistive limb suit either had not received sufficient gait training or had an estab-lished gait pattern with a knee–ankle–foot orthosis using a quad cane. The physiological cost index increased after wearing the hybrid assistive limb suit in 12 patients, but removal of the suit led to a decrease in the physiological cost index values to equivalent levels prior to the use of the suit.
Conclusions: Although the hybrid assistive limb suit is not useful for all hemiplegic patients, it may increase the walking speed and affect the walking ability. Further investigation would clarify its indication for the possibility of gait training.

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