Yueqing Li

A P300-Based Brain–Computer Interface: Effects of Interface Type and Screen Size

As a nonmuscular communication and control system for people with severe motor disabilities, brain–computer interface (BCI) has found several applications. Although a few empirical studies of BCI user performance do exist, little to no research has specifically evaluated the impact of contributing factors on user performance in the BCI applications. To that end, our within-subjects design compared the impact of two different types of interface (ABC interface vs. frequency-based interface) and three levels of screen size (computer monitor, global positioning system, and cell phone screen) of a P300-based BCI application, P300 Speller, on user performance (accuracy, information transfer rate, amplitude, and latency) and usage preference. Ten participants with neuromuscular disabilities such as amyotrophic lateral sclerosis and cerebral palsy and 10 nondisabled participants were asked to type six, 10-character phrases in the P300 Speller. The overall accuracy was 79.7% for the nondisabled participants and 28.7% for participants with motor disabilities. The results showed that interface type and screen size have significant effects on user performance and usage preference, with varying degree of impact to participants with and without motor disabilities. Specifically, participants typed significantly more accurately in frequency-based interface and computer monitor screen. The results of this study should provide invaluable insights to the future research of P300-based BCI applications.

An approach to increase prediction precision of GM(1,1) model based on optimization of the initial condition

We propose a novel approach to improve prediction accuracy of GM(1,1) model through optimization of the initial condition in this paper. The new initial condition is comprised of the first item and the last item of a sequence generated from applying the first-order accumulative generation operator on the sequence of raw data. Weighted coefficients of the first item and the last item in the combination as the initial condition are derived from a method of minimizing error summation of square. We can actually find that the newly modified GM(1,1) model is an extension of the original GM(1,1) model and another modified model which takes the last item in the generated sequence as the initial condition when weighted coefficients takes distinctly specific values. The new optimized initial condition can express the principle of new information priority emphasized on in grey systems theory fully. The result of a numerical example indicates that the modified GM(1,1) model presented in this paper can obtain a better prediction performance than that from the original GM(1,1) model.

Evaluation of P300-Based Brain-Computer Interface in Real-World Contexts

Despite recent advances in brain-computer interface (BCI) development, system usability still remains a large oversight. The goal of this study was to investigate the usability of a P300-based BCI system, P300 Speller, by assessing how background noise and interface color contrast affect user performance and BCI usage preference. Fifteen able-bodied participants underwent a 2 (low and high interface color contrast) × 3 (low, medium, and high background noise level) within-subjects design experiment, in which participants were asked to type six 10-character phrases in the P300 Speller paradigm. The overall accuracy in the study was 80.2%. Participants showed higher accuracy, higher information transfer rate, bigger amplitude, and smaller latency in the high interface color contrast condition than in the low contrast condition. Participants had better performance in the noisy condition than in the quiet condition, but the background noise effects were not statistically significant in the present study. These results should give some insight to the real-world applicability of the current P300 Speller as a nonmuscular communication system, especially for individuals with severe neuromuscular disabilities.

Effects of Luminosity Contrast and Stimulus Duration on User Performance and Preference in a P300-Based Brain–Computer Interface

Brain–computer interfaces (BCI) have potential to provide a new channel of communication and control for people with severe motor disabilities. Although many empirical studies exist, few have specifically evaluated the impact of contributing factors on user performance and perception in BCI applications, especially for users with motor disabilities. This article reports the effects of luminosity contrast and stimulus duration on user performance and usage preference in a P300-based BCI application, P300 Speller. Ten participants with neuromuscular disabilities (amyotrophic lateral sclerosis and cerebral palsy) and 10 able-bodied participants were asked to spell six 10-character phrases in the P300 Speller. The overall accuracy was 76.5% for the able-bodied participants and 26.8% for participants with motor disabilities. The results showed that luminosity contrast and stimulus duration have significant effects on user performance. In addition, participants preferred high luminosity contrast with middle or short stimulus duration. However, these effects on user performance and preference varied for participants with and without motor disabilities. The results also indicated that although most participants with motor disabilities can establish BCI control, BCI illiteracy does exist. These results of the study should provide insights into the future research of the BCI systems, especially the real-world applicability of the BCI applications as a nonmuscular communication and control system for people with severe motor disabilities.

Environmental Noise and P300-Based Brain-Computer Interface (BCI)

The primary purpose of this study was to systematically evaluate the overall effect of simulated environmental noise on the P300 Speller in order to obtain usability and performance data. P300 Speller is a P300-based brain-computer interface (BCI) that allows people with motor disabilities to type characters just by thinking. Two environmental noise simulations (quiet [20–40 dB], and noisy [70–120 dB]) were examined to simulate the effects of real-world noise. Results of the study indicated that although there were differences in accuracy rate and information transfer rate (ITR) between the noise and quiet conditions, the environmental noise factor was not statistically significant. On the other hand, the P300 amplitude was significantly higher in the noisy condition than in the quiet condition. Unlike the common knowledge that BCI applications are generally preferred to be performed in quiet conditions, higher noise levels seem to increase user concentration. The outcomes of this research should have a broad impact on future user interface design of BCI applications.

Haptic Science Learning System for Students with Visual Impairments: A Preliminary Study

This paper assesses the usability of developed haptic interface features to support future development of haptically enhanced science learning applications for students with visual impairments. Of the features developed and evaluated, three features are described in this study: Haptic Boundary, Menu Selection, and Object Recognition. Two focus groups participated in an interview and usability session. Results from this study give insight to the needs of the visually impaired community in regard to haptic applications.

Assessing the effectiveness of vibrotactile feedback on a 2D navigation task

The effect of vibrotactile parameters were investigated on a 2D navigation task. Participants performed a simple navigation task reproducing directional information presented by a series of vibrotactile stimuli consisting of different levels of amplitude and frequency. Task completion time and degree of annoyance were measured. The results demonstrated that both frequency and amplitude had a significant effect on the responses. In addition, interaction effects between the two parameters were found on the responses. It was concluded that user performance and comfort are significantly affected by frequency and amplitude. The results give some insight into designing navigating information presented by vibrotactile display for visually impaired people. More studies with people with visual impairment and manipulation of other vibrotactile parameters are recommended to be applicable to the potential research.

Effect of Smartphone Use on Upper Extremity and Neck

Smartphones nowadays are very popular and does most of the work from sending emails to attending meetings. However, Smartphone over-use has been studied from years now and there are many proven problems such as neck pain, back pain, headache, arm or wrist pain, psychological discomfort, etc. In this study, effect of screen sizes, task type and one/two hand on user muscle activities was investigated while users perform various tasks on Smartphone. Electromyography was used to assess muscle activities. Results showed that screen size and one/two handed use had significant main effects on users’ muscle activity. Significant interaction effect was also found. For example, significantly less muscle activities were observed in hands while texting with two hands compared to one-hand. Gaming with two hands led to higher muscle activities on large screen Smartphone than small screen. The research could help users to choose more appropriate smart phones and develop a better usage habit.

A Collaborative Brain-Computer Interface (BCI) for ALS Patients

This study evaluated a SSVEP-based collaborative brain-computer interface (BCI) for people with severe motor disabilities. With ten ALS (amyotrophic lateral sclerosis) patients and 10 age-matched able-bodied participants as control group, effects of collaboration and motor disability were investigated. Participants were requested to control a robot in a predefined path with their brain signals. Two collaboration modes were developed in the study: individual mode and simultaneous mode. Results revealed significantly better performance in simultaneous mode than individual mode, but no significant effect of motor disability. The study showed promising preliminary results for supporting collaborative work between BCI users with severe motor disabilities. It should provide great insights for future research and system development.

Neck Flexion Angle and User Experience Compared on iPhone X and Samsung S8

There have been a lot of research and explanation on Smartphone screen size and user experience of numerous Smartphones. This study considers the difference between neck flexion angle and its effects on human ergonomics while using two Smartphones with different screen sizes and display features (iPhone X and Samsung S8+). This study also collects user experience data through a questionnaire to generate the most ergonomic model among the Apple Inc.’s iPhone X and Samsung S8+. 8 participants were considered for this study. A digital goniometer was used to analyze participant’s neck flexion angle while using both the Smartphones (iPhone X and Samsung S8+). A paired t-test of means was performed. Neck flexion angle was highly flexed for the participants while using iPhone X than compared to the neck flexion angle while using Samsung S8+. Participants felt more comfortable using both Smartphones. However, ‘True-tone’ technology in iPhone X eased the stress level of eyes according to the users. This study suggests a large screen smartphone with ‘True-tone’ or similar technology, which can be an iPhone X but with a larger screen size.