The Design of an Intelligent Robotic Wheelchair Supporting People with Special Needs, Including for Their Visual System

Smart Nursing Wheelchairs: A New Trend in Assisted Care and the Future of Multifunctional Integration

As a significant technological innovation in the fields of medicine and geriatric care, smart care wheelchairs offer a novel approach to providing high-quality care services and improving the quality of care. The aim of this review article is to examine the development, applications and prospects of smart nursing wheelchairs, with particular emphasis on their assistive nursing functions, multiple-sensor fusion technology, and human-machine interaction interfaces. First, we describe the assistive functions of nursing wheelchairs, including position changing, transferring, bathing, and toileting, which significantly reduce the workload of nursing staff and improve the quality of care. Second, we summarized the existing multiple-sensor fusion technology for smart nursing wheelchairs, including LiDAR, RGB-D, ultrasonic sensors, etc. These technologies give wheelchairs autonomy and safety, better meeting patients' needs. We also discussed the human-machine interaction interfaces of intelligent care wheelchairs, such as voice recognition, touch screens, and remote controls. These interfaces allow users to operate and control the wheelchair more easily, improving usability and maneuverability. Finally, we emphasized the importance of multifunctional-integrated care wheelchairs that integrate assistive care, navigation, and human-machine interaction functions into a comprehensive care solution for users. We are looking forward to the future and assume that smart nursing wheelchairs will play an increasingly important role in medicine and geriatric care. By integrating advanced technologies such as enhanced artificial intelligence, intelligent sensors, and remote monitoring, we expect to further improve patients' quality of care and quality of life.

Enhanced Route navigation control system for turtlebot using human-assisted mobility and 3-D SLAM optimization

An autonomous, power-assisted Turtlebot is presented in this paper in order to enhance human mobility. The turtlebot moves from its initial position to its final position at a predetermined speed and acceleration. We propose an intelligent navigation system that relies solely on individual instructions. When there is no individual present, the Turtlebot remains stationary. Turtlebot utilizes a rotating Kinect sensor in order to perceive its path. Various angles were examined in order to demonstrate the effectiveness of the system in experiments conducted on a U-shaped experimental pathway. The Turtlebot was used as an experimental device during these trials. Based on the U-shaped path, deviations from different angles were measured to evaluate its performance. SLAM (Simultaneous Localization and Mapping) experiments were also explored. We divided the SLAM problem into components and implemented the Kalman filter on the experimental path to address it. The Kalman filter focused on localization and mapping challenges, utilizing mathematical processes considering both the system's knowledge and the measurement tool. This approach allowed us to achieve the most accurate system state estimation possible. The significance of this work extends beyond the immediate application, as it lays the groundwork for advancements in wheelchair navigation research by Dynamic Control. The experiments conducted on a U-shaped pathway not only validate the efficacy of our algorithm but also provide valuable insights into the intricacies of navigating in both forward and reverse directions. These insights are pivotal for refining the navigation algorithm, ultimately contributing to the development of more robust and user-friendly systems for individuals with mobility challenges. The data used for this purpose included actuator input, vehicle location, robot movement sensors, and sensor readings representing the world state. The study provides a strong foundation for future wheelchair navigation research by Dynamic Control. Consequently, we found that navigating the Turtlebot in the reverse direction resulted in a 5%-6% increase in diversion compared to forward navigation, providing valuable insight into further improvement of the navigation algorithm.

Comparative Analysis of Strabismus Measurement Using a Video Oculagraphy System and Alternate Prism Cover Test

PURPOSE

The aim of the study was to compare distance vision measurements obtained with video oculography (VOG) and an alternate prism cover test (APCT).

DESIGN

Single-center, retrospective, and cross-sectional.

METHODS

Eighty-seven subjects with strabismus were included. All patients underwent an optometric examination. The measurement of strabismus in distance vision was performed with the best optical correction using the APCT and the VOG GazeLab. Subjects were divided according to the type of strabismus; 41 were esotropic and 46 were exotropic.

RESULTS

The general comparison of APCT and VOG showed a mean difference of 0.60±2.74 prism diopters (Δ), not observing statistical differences between both methods ( P =0.059) and presenting a correlation of 0.976 ( P <0.001). Using APCT, the mean amount of esotropia for the group was 18.31±11.64 Δ and that of exotropia was 19.62±8.80 Δ. Compared with the VOG, the mean value of esotropia for the group was 18.65±11.65 Δ and that of exotropia was 19.48±8.62 Δ. The means are statistically different for the esotropia group ( P =0.005) but not for the exotropia group ( P =0.318). There was a high direct correlation between the methods of measurement for both the esotropic ( R =0.980; P <0.001) and exotropic patients ( R =0.975; P <0.001). Bland-Altman analysis shows a mean difference of 1.37±2.76 Δ for the esotropia patients and 0.31±2.66 Δ for the exotropic patients, respectively.

CONCLUSIONS

This study demonstrated comparable results in measuring strabismus between VOG and APTC for esotropia and exotropia, with an excellent correlation between both methods and good agreement, especially in subjects with exotropia.

Promoting active aging through assistive product design innovation: a preference-based integrated design framework

Background

With the accelerating trend of global aging, over one billion people need to use one or more types of assistive products. However, the high abandonment rate of current assistive products is affecting the quality of life of the older adults, posing challenges to public health. Accurately capturing the preference factors of the older adults in the design process is an important way to improve the acceptance of assistive products. In addition, a systematic approach is needed to translate these preference factors into innovative product solutions. These two issues are less addressed in existing research.

Methods

First, the evaluation grid method was used to conduct in-depth interviews with users and extract the structure of preference factors for assistive products. Quantification theory type I was used to calculate the weight of each factor. Secondly, universal design principles, TRIZ theory's contradiction analysis techniques, and invention principles were used to translate the preference factors into design guidelines. Then, finite structure method (FSM), morphological chart, and CAD techniques were used to visualize the design guidelines as alternatives. Finally, Analytic Hierarchy Process (AHP) was used to evaluate and rank the alternatives.

Results

A Preference-based Assistive Product Design Model (PAPDM) was proposed. The model includes three stages: definition, ideation, and evaluation. A case study on walking aid demonstrated the execution of PAPDM. The results show that 28 preference factors influence the four psychological needs of the older adults: sense of security, sense of independence, self-esteem, and sense of participation. These psychological needs were reflected in the shape, color, material, universality, user-friendly, reliability, and smart functions of assistive products. The preference factors were transformed into five design guidelines, and three alternatives were generated. Finally, the evaluation concludes that solution C was the optimal solution.

Conclusion

The PAPDM framework provides designers with a transparent, progressive approach to designing assistive products that meet unique needs and preferences of older adults. This enhances objectivity and scientific rigor in assistive product development, avoiding blind design and production. By considering the perspective of older adults from the outset, we can avoid high abandonment rates of assistive products and contribute to promoting active aging.

A human-in-the-loop approach for enhancing mobile robot navigation in presence of obstacles not detected by the sensory set

Human-in-the-loop approaches can greatly enhance the human-robot interaction by making the user an active part of the control loop, who can provide a feedback to the robot in order to augment its capabilities. Such feedback becomes even more important in all those situations where safety is of utmost concern, such as in assistive robotics. This study aims to realize a human-in-the-loop approach, where the human can provide a feedback to a specific robot, namely, a smart wheelchair, to augment its artificial sensory set, extending and improving its capabilities to detect and avoid obstacles. The feedback is provided by both a keyboard and a brain-computer interface: with this scope, the work has also included a protocol design phase to elicit and evoke human brain event-related potentials. The whole architecture has been validated within a simulated robotic environment, with electroencephalography signals acquired from different test subjects.