ABSTRACT
Despite advancements in creating barrier-free environments, many buildings still have stairs, making accessibility a significant concern for wheelchair users, the majority of whom check for accessibility information before venturing out. This paper focuses on developing a transformable quadruped wheelchair to address the mobility challenges posed by stairs and steps for wheelchair users. The wheelchair, inspired by the Unitree B2 quadruped robot, combines wheels for flat surfaces and robotic legs for navigating stairs and is equipped with advanced sensors and force detectors to interact with its surroundings effectively. This research utilized reinforcement learning, specifically curriculum learning, to teach the wheelchair stair-climbing skills, with progressively increasing complexity in a simulated environment crafted in the Unity game engine. The experiments demonstrated high success rates in both stair ascent and descent, showcasing the wheelchair's potential in overcoming mobility barriers. However, the current model faces limitations in tackling various stair types, like spiral staircases, and requires further enhancements in safety and stability, particularly in the descending phase. The project illustrates a significant step towards enhancing mobility for wheelchair users, aiming to broaden their access to diverse environments. Continued improvements and testing are essential to ensure the wheelchair's adaptability and safety across different terrains and situations, underlining the ongoing commitment to technological innovation in aiding individuals with mobility impairments.
Subject(s)
Equipment Design , Robotics , Wheelchairs , Humans , Stair Climbing/physiologyABSTRACT
Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app.
