Abstract: Hand exoskeletons have been developed in order to assist daily activities for disabled and elder people. A figure exoskeleton was developed using ionic polymer metal composite (IPMC) actuators, and the performance of it was evaluated in this study. In order to study dynamic performance of a finger dummy performing pinching motion, force generating characteristics of an IPMC actuator and pinching motion of a thumb and index finger dummy actuated by IMPC actuators were analyzed. The blocking force of 1.54 N was achieved under 4 V of DC. A thumb and index finger dummy, which has one degree of freedom at the proximal joint of each figure, was manufactured by a three dimensional rapid prototyping. Each figure was actuated by an IPMC actuator, and the maximum fingertip force was 1.18 N. Pinching motion of a dummy was analyzed by two video cameras in vertical top and horizontal left end view planes. A figure dummy powered by IPMC actuators could perform flexion and extension motion of an index figure and a thumb.
Abstract: Children with hemiplgic cerebral palsy often walk
with diminished reciprocal arm swing so the purpose of this study
was to describe kinematic characteristics in children with hemiplegic
cerebral palsy (CP) during the gait suphases, and find if there is a
correlation between upper(shoulder and elbow) and lower(hip, knee,
and ankle) limb joints either in involved or uninvolved.48 children
with hemiplegic cerebral palsy (18boys, 30girls) with an average age
of (5.1±0.87) years were selected randomly to evaluate joint angles
during gait by 3D motion analysis system with 6 pro reflex cameras
in a sagittal plane for both sides of the body. The results showed
increased shoulder and elbow flexion, increased hip angular
displacement, decreased knee and ankle arcs during gait cycle, also
there is correlation between shoulder and elbow to hip, knee, and
ankle joints during various subphases of gait.
Abstract: This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.