Image and Speech Recognition Technology in the Development of an Elderly Care Robot: Practical Issues Review and Improvement Strategies.

As the world's population is aging and there is a shortage of sufficient caring manpower, the development of intelligent care robots is a feasible solution. At present, plenty of care robots have been developed, but humanized care robots that can suitably respond to the individual behaviors of elderly people, such as pose, expression, gaze, and speech are generally lacking. To achieve the interaction, the main objectives of this study are: (1) conducting a literature review and analyzing the status quo on the following four core tasks of image and speech recognition technology: human pose recognition, human facial expression recognition, eye gazing recognition, and Chinese speech recognition; (2) proposing improvement strategies for these tasks based on the results of the literature review.

Depth-Camera Based Energy Expenditure Estimation System for Physical Activity Using Posture Classification Algorithm.

Insufficient physical activity is common in modern society. By estimating the energy expenditure (EE) of different physical activities, people can develop suitable exercise plans to improve their lifestyle quality. However, several limitations still exist in the related works.

Development of a fingertip glove equipped with magnetic tracking sensors.

In this paper, we present the development of a data glove system based on fingertip tracking techniques. To track the fingertip position and orientation, a sensor module and two generator coils are attached on the fingertip and metacarpal of the corresponding finger. By tracking the fingertip, object manipulation tasks in a virtual environment or teleoperation system can be carried out more precisely, because fingertips are the foremost areas that reach the surface of an object in most of grasping processes.

The multisynapse neural network and its application to fuzzy clustering.

In this paper, a new neural architecture, the multisynapse neural network, is developed for constrained optimization problems, whose objective functions may include high-order, logarithmic, and sinusoidal forms, etc., unlike the traditional Hopfield networks which can only handle quadratic form optimization. Meanwhile, based on the application of this new architecture, a fuzzy bidirectional associative clustering network (FBACN), which is composed of two layers of recurrent networks, is proposed for fuzzy-partition clustering according to the objective-functional method.