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This paper deals with the optimal design and control of an exoskeleton robot. First, the motion data from the thumb of a normal subject was captured by a vision system. As the human finger joints cannot be modeled by single revolute joints due to changing instantaneous centre of rotation, we have used 4-bar mechanisms to model each joint. Optimal 4-bars have been designed using genetic algorithms, by minimizing the error between a coupler point and points traced by the finger links. It is shown that the designed 4-bars can accurately track the motion of the human fingers. The exoskeleton is controlled by using the EMG signals obtained from the subject's muscles. The relation between the EMG and finger motion is first learned, using a neural net. Based on the learned parameters, the subjects EMG signal is used to control a simulation of the exoskeleton joint motion.

This paper deals with the optimal design and control of an exoskeletal robot. First, the motion data from the fingers of a normal subject was captured by a vision system. As the human finger joints cannot be modeled by single revolute joints due to changing instantaneous centre of rotation, we have used 4-bar mechanisms to model each joint. Optimal 4-bars have been designed using genetic algorithms, by minimizing the error between a coupler point and points traced by the finger links. It is shown that the designed 4-bars can accurately track the motion of the human fingers. The exoskeleton is controlled by using the EMG signals obtained from the subject's muscles. The relation between the EMG and finger motion is first learned, using a neural net. Based on the learned parameters, the subjects EMG signal is used to control a simulation of the exoskeleton joint motion. A comparison between Recurrent Neural Network and Multi Layer Perceptron for classifying and mapping the EMG to finger position was also carried out.

We compared the Oxoid Signal bottle (Oxoid, U.S.A.) with supplemented peptone broth (SPB) tubes (B-D Vacutainer; Becton Dickinson Vacutainer Systems) for performing blood cultures in a pediatric hospital. Blood from 3,066 samples was divided equally between the two systems. Of 131 probable pathogens isolated, 121 were detected in the Signal bottle and 111 were detected in the SPB tubes (P greater than 0.05). Of 167 probable contaminants, 122 grew in the Signal bottle and 109 grew in the SPB tubes (P greater than 0.05). The recovery of staphylococci, both probable pathogens and probable contaminants, was increased in the Signal bottle. The recoveries of other organisms, including streptococci, members of the family Enterobacteriaceae, and yeasts, were similar in the two systems. However, the Signal bottle failed to detect three isolates of Haemophilus influenzae, and the time to availability of isolated colonies of other isolates of H. influenzae was delayed. Overall, the Signal bottle was easy and convenient to use, and its innovative detection system should facilitate the early recognition of positive cultures. If its ability to recover H. influenzae can be improved, the Signal bottle could be a useful alternative to existing systems for use in a pediatric setting.