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Many individuals who are in need of mobility assistance do not have access to the proper wheelchair for their type of mobility disability. There is growing research towards creating smart wheelchairs using a variety of methods, such as biopotential signals or eye tracking for input and LiDAR, ultrasonic sensors, or using a camera to create a map or track position. There have been other methods, such as voice control, sip and puff, and hand gestures, but there are disadvantages of these that can limit their usefulness. Smart wheelchairs should account for collisions, but also emphasize the safety and comfort of the user. In this paper, we review and classify state-of-the-art research in smart wheelchairs. Many machine learning models are used for various parts of wheelchairs, from mapping and signal processing to input classification. Smart wheelchairs rely on various hardware devices, such as eye trackers, electrode caps, EMG armbands, RPLidar, RGB-cameras, and ultrasonic sensors. Some hybrid models use a combination of methods to account for some of their limitations. Some research has leaned towards training games to help teach users. Future work should include improvement of classification methods for various input signals and improvement on the accessibility of the technology. 

This survey paper aims to provide an overview of the current state of EEG (Electroencephalography) signal technology as it relates to people with disabilities. It will highlight the various methods and techniques employed, discussing their advantages and disadvantages. The paper will also examine the applications of EEG technology in assisting individuals with disabilities, specifically focusing on Brain-Computer Interfaces (BCIs) and assistive device control. By understanding the current state of EEG signal technology, we can identify the opportunities and challenges involved in utilizing this technology to improve the lives of people with disabilities 

Millions of people with hearing disabilities use sign language for communication, creating a communication gap with those who are not fluent in ASL (American Sign Language). This paper aims to introduce an ASL interpreter system using a smart-glasses-based augmented reality system. We begin by introducing and comparing two models that translate spoken language into ASL poses. The first system translates spoken text to ASL Gloss, an intermediate representation, before generating ASL poses. The second system directly translates the text to ASL poses. Our analysis shows that using ASL Gloss as an intermediate step significantly improves the translation speed. We then explore a system of encoding ASL pose videos for display on smart glasses. The chosen translation method has a BLEU score of 66.5801 and a rate of 1.825 milliseconds per gloss translation. Our algorithm for mapping gloss text to ASL videos obtained a mean squared error of 0.05, indicating that our system has good translational accuracy and a low mapping error. 

Primate models are important for understanding human conditions, especially in studies of ageing, pathology, adaptation, and evolution. However, how to integrate data from multiple disciplines and render them compatible with each other for datamining and in-depth study is always challenging. In a long-term project, we have started a collaborative research endeavor to examine the health history of a free-ranging rhesus macaque colony at Cayo Santiago, and build a knowledge model for anthropological and biomedical/translational studies of the effects of environment and genetics on bone development, aging, and pathologies. This paper discusses the conceptual design as well as the prototyping of this model and related graphical user interfaces, and how these will help future scientific queries and studies. 

Primate models are important for understanding human conditions, especially in studies of ageing, pathology, adaptation, and evolution. However, how to integrate data from multiple disciplines and render them compatible with each other for datamining and in-depth study is always challenging. In a long-term project, we have started a collaborative research endeavor to examine the health history of a free-ranging rhesus macaque colony at Cayo Santiago, and build a knowledge model for anthropological and biomedical/translational studies of the effects of environment and genetics on bone development, aging, and pathologies. This paper discusses the conceptual design as well as the prototyping of this model and related graphical user interfaces, and how these will help future scientific queries and studies.