The relationship of subepidermal moisture and early stage pressure injury by visual skin assessment.

AIM: The purpose of this study was to examine the relationship of subepidermal moisture and early stage pressure injury by visual skin assessment in elderly Korean. METHODS: Twenty-nine elderly participated at a particular nursing home. Data were collected for 12 weeks by one wound care nurse. Visual skin assessment and subepidermal moisture value were measured at both buttocks, both ischia, both trochanters, sacrum, and coccyx of each subject once a week. RESULTS: Subepidermal moisture value of stage 1 pressure injury was significantly higher than that of no injury and blanching erythema. After adjustment with covariates, odds ratios of blanching erythema to normal skin and stage 1 pressure injury to blanching erythema/normal skin were statistically significant (p < 0.05). Odds ratio of blanching erythema to normal skin was 1.003 (p = .047) by 1-week prior subepidermal moisture value, and that of concurrent subepidermal moisture value was 1.004 (p = .011). Odds ratio of stage 1 pressure injury to normal skin/blanching erythema was 1.003 (p = .005) by 1-week prior subepidermal moisture value, and that for concurrent subepidermal moisture value was 1.007 (p = .030). Subepidermal moisture was associated with concurrent and future (1 week later) skin damage at both trochanters. CONCLUSION: Subepidermal moisture would be used to predict early skin damage in clinical nursing field for the effective pressure injury prevention.

Quantitative evaluation of a low-cost noninvasive hybrid interface based on EEG and eye movement.

This paper describes a low-cost noninvasive brain-computer interface (BCI) hybridized with eye tracking. It also discusses its feasibility through a Fitts' law-based quantitative evaluation method. Noninvasive BCI has recently received a lot of attention. To bring the BCI applications into real life, user-friendly and easily portable devices need to be provided. In this work, as an approach to realize a real-world BCI, electroencephalograph (EEG)-based BCI combined with eye tracking is investigated. The two interfaces can be complementary to attain improved performance. Especially to consider public availability, a low-cost interface device is intentionally used for test. A low-cost commercial EEG recording device is integrated with an inexpensive custom-built eye tracker. The developed hybrid interface is evaluated through target pointing and selection experiments. Eye movement is interpreted as cursor movement and noninvasive BCI selects a cursor point with two selection confirmation schemes. Using Fitts' law, the proposed interface scheme is compared with other interface schemes such as mouse, eye tracking with dwell time, and eye tracking with keyboard. In addition, the proposed hybrid BCI system is discussed with respect to a practical interface scheme. Although further advancement is required, the proposed hybrid BCI system has the potential to be practically useful in a natural and intuitive manner.

Quadcopter flight control using a low-cost hybrid interface with EEG-based classification and eye tracking.

We propose a wearable hybrid interface where eye movements and mental concentration directly influence the control of a quadcopter in three-dimensional space. This noninvasive and low-cost interface addresses limitations of previous work by supporting users to complete their complicated tasks in a constrained environment in which only visual feedback is provided. The combination of the two inputs augments the number of control commands to enable the flying robot to travel in eight different directions within the physical environment. Five human subjects participated in the experiments to test the feasibility of the hybrid interface. A front view camera on the hull of the quadcopter provided the only visual feedback to each remote subject on a laptop display. Based on the visual feedback, the subjects used the interface to navigate along pre-set target locations in the air. The flight performance was evaluated by comparing with a keyboard-based interface. We demonstrate the applicability of the hybrid interface to explore and interact with a three-dimensional physical space through a flying robot.

A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in which a subject remotely controls a humanoid robot in a properly sized maze. The subject sees what the surrogate robot sees through visual feedback and can navigate the surrogate robot. While navigating, the robot encounters objects located in the maze. It then recognizes if the encountered object is of interest to the subject. The subject communicates with the robot through SSVEP and ERD-based BCIs to navigate and explore with the robot, and P300-based BCI to allow the surrogate robot recognize their favorites. Using several evaluation metrics, the performances of five subjects navigating the robot were quite comparable to manual keyboard control. During object recognition mode, favorite objects were successfully selected from two to four choices. Subjects conducted humanoid navigation and recognition tasks as if they embodied the robot. Analysis of the data supports the potential usefulness of the proposed hybrid BCI system for extended applications. This work presents an important implication for the future work that a hybridization of simple BCI protocols provide extended controllability to carry out complicated tasks even with a low-cost system.