Design of Dynamic Vibrotactile Textures.

This paper describes a method for creating virtual textures without force feedback by using a simple motion sensor and a single vibrotactile actuator. It is based on wavetable synthesis driven by the user's hand movements. The output of the synthesis is rendered with the tactile actuator attached in a hand-held box together with the motion sensor. The method provides a solution for creating tangible properties for virtual objects which can be explored by pointing at them with the sensor-actuator device. The study introduces 12 virtual textures which were based on three different envelope ridge lengths, two spatial densities, and were either regularly or irregularly organized. To evaluate the role of each design parameter in the perception of the texture, a series of experiments was conducted. The perceived similarity was assessed in a pairwise comparison test and the outcome was analyzed by using multidimensional scaling. The analysis revealed that envelope ridge length and spatial density were distinguishable design parameters while regularity was not. The textures were also rated according to five attribute scales previously determined in the pilot experiment. The results show that ridge length and spatial density influence perceived roughness and flatness similarly as with real textures.

Feasibility of building robust surface electromyography-based hand gesture interfaces.

This study explored the feasibility of building robust surface electromyography (EMG)-based gesture interfaces starting from the definition of input command gestures. As a first step, an offline experimental scheme was carried out for extracting user-independent input command sets with high class separability, reliability and low individual variations from 23 classes of hand gestures. Then three types (same-user, multi-user and cross-user test) of online experiments were conducted to demonstrate the feasibility of building robust surface EMG-based interfaces with the hand gesture sets recommended by the offline experiments. The research results reported in this paper are useful for the development and popularization of surface EMG-based gesture interaction technology.

Exploration on the feasibility of building muscle-computer interfaces using neck and shoulder motions.

This paper investigates the feasibility of building muscle-computer interfaces starting from surface Electromyography (SEMG) -based neck and shoulder motion recognition. In order to reach the research goal, a real-time SEMG sensing, processing and classification system was developed firstly. Then two types of SEMG recognition experiments, namely user-specific and user-independent classification, were designed and conducted on seven kinds of neck and shoulder motions to explore the feasibility of using these motions as input commands of muscle-computer interfaces. In all 9 subjects took part in these experiments, 97.8% and 84.6% overall average recognition accuracies were obtained in user-specific and user-independent experiments respectively. The experimental results demonstrate that it is possible to build muscle-computer interfaces with neck and shoulder motions. In addition, the results of cross-time experiments designed to explore the relationship between training and accuracy in user-specific recognition indicate that users can interact accurately with computers using the defined motions only after four times training in different days.