They See Me Rollin’, They Hatin’

Aubrey Graham, more commonly known as hip-hop performer Drake, presents himself as a man of contradiction—a lover and a fighter, sensitive but hard, successful but humble. Despite this subjective work, designed to present a complex embodiment of an artistic and financial success, the discourse of Graham online is often underpinned by suspicion and derision that seeks to redefine him as a pretender who is unworthy of the status he claims. Nowhere is this more evident than in the “Wheelchair Drake” memetic cluster, which uses an old Degrassi: The Next Generation promotional image of Graham sitting on a wheelchair, combined with humorous juxtaposition of rap lyrics, to critique Graham’s status as both a performer and a Black man. In various Wheelchair Drake memes, physical impairment becomes a living metaphor for a spoiled identity; the memes argue that, just like ableist imaginations of physically disabled people, Graham is doomed to a life of impotence and dependency. Built upon a sample of 583 user-generated images, coded into 9 thematic groups, this article excavates the latticed discourses of masculinity, disability and race that animate the Wheelchair Drake meme and consider the ways that this memetic cluster subjects Aubrey Graham to the strictures of ableist hegemonic masculinity.

A GSM Based Assistive Device for Blind, Deaf and Dumb

This paper tries to overcome the shortcomings of the recent technology that fails to enhance the communication between physically disabled people by designing an assistive device. This device uses a GSM modem with a SIM card and no smartphones are needed which makes the device affordable. Here, the sender sends the message to the phone number of the disabled person and he/she receives the SMS that gets converted to text and voice message and vibrations to Braille pad using a microcontroller which is easily readable by the disabled person.

Developments of Adapted Clothing for Physically Disabled People with Scoliosis Using 3D Geometrical Model

Scoliosis is a deformity of the spine that causes disorders of the rib cage. This makes it difficult to design clothes for affected people without following the shape of the rib cage. This paper presents a new 3D clothing design method based on virtual reality for women with physical disabilities such as scoliosis. The current design method is a variation of the draping techniques commonly used by fashion designers to design clothes on a mannequin or human body. However, the current design process highly considers the skeleton and body scan of the person. The skeleton is used to detect the anthropometric points of the patient, while the body scan allows us to detect the morphological contours at the onset of scoliosis. Thus, both allow us to accurately track the patient’s morphology and atypical shape. The position of the morphological contours is indicated by reference marks that are closely associated with the skeleton. This helps to automatically adapt the garment to the evolution of the patient’s pathology over time. The process of creating the 3D garment was processed based on the 3D model of the thorax, which helps to easily determine the anthropometric points and the morphological curves. Using this data, the geometrical model of the garment could be created with 3D ease allowances. The 2D block pattern was then obtained by flattening the 3D patterns using flattening methods. Finally, various tests were performed considering the evolution of pathology to predict the future garment. These tests validate our geometrical model of the garment with 3D ease allowances by comparing the results with previous work.

Reinforcement Learning-Based Assistive Framework for Disabled Persons

Robot programming by demonstration (PbD) enables human users to teach the robot and increases its capabilities by interactive teaching without having to manually program the robot. PbD combined with intelligent machine learning algothrims can help us to develop autonomous robots for various industrial and domestic tasks. One such task is the pouring of liquids from bottle into the cup/glass. In this paper the first step is to teach the robot liquid pouring task by the human user in order to facilitate physically disabled people in making various types of drinks and then dataset is created from the user taken demonstrations. In training stage the dataset obtained is feed to the decision-making algorithm based on reinforcement learning. The algorithm enables the robot to learn to pour different liquids under different pouring conditions with the help of minimum number of human user demonstrations needed for the learning of task. The acquired results show that the robot can learn to pour different liquids and is able to accurately adapt to different pouring conditions by using reward-based system and online feedback. Furthermore the results show that the proposed framework can work with different types of liquid and container sizes without any further need for reprogramming or demonstrations.

Virtual Interface with Kinect 3D Sensor for Interaction with Bedridden People

The human-machine interaction has evolved significantly in the last years, allowing a new range of opportunities for developing solutions for people with physical limitations. Natural user interfaces (NUI) allow bedridden and/or physically disabled people to perform a set of actions trough gestures thus increasing their quality of life and autonomy. This paper presents a solution based on image processing and computer vision using the Kinect 3D sensor for development of applications that recognize gestures made by the human hand. The gestures are then identified by a software application that triggers a set of actions of upmost importance for the bedridden person, for example, trigger the emergency, switch on/off the TV or control the bed slope. It was used a shape matching technique for six gestures recognition, being the final actions activated by the Arduino platform. The results show a success rate of 96%. This system can improve the quality of life and autonomy of bedridden people, being able to be adapted for the specific necessities of an individual subject.

The Association Between Falls and Physical and Psychological Conditions in Physically Disabled Elderly People: A Retrospective Cohort Study

Background Falling in physically disabled people is a worldwide social issue and associated with declined physical and psychological health. This study aimed to clarify the physical and psychological conditions in physically disabled people and to explore whether those conditions are the risk factors of falls. Methods One hundred and forty-six physically disabled people were recruited (age 64.2 ± 5.7, ranging from 43 to 77). Their demographic information, psychological status, musculoskeletal conditions, and history of falls in the past year were collected, and mobility was evaluated. A logistic regression analysis was used to clarify the risk factors of falls with the receiver operating characteristic (ROC) curve exploring the effectiveness of the regression model on fall diagnosis via area under the curve (AUC). A subgroup analysis was done between the disabled participants with and without poliomyelitis (polio). Results The cause of disability (polio or no-polio), gender, disability grade, and functional gait assessment were significantly associated with falls (all p < 0.05, Nagelkerke R2 = 0.320), and ROC curve indicated that AUC of this model was 0.805 (p < 0.001, 95% CI 0.735–0.876, Youden Index = 0.502). The subgroup analysis showed that the polio group (75 of the 146 participants) had a longer history of disability (t = 12.360, p < 0.001) than the no-polio disabled group while there were no significant differences in the other demographic information (all p > 0.05). The proportion of moderate anxiety in the no-polio participants was significantly higher than that in the polio group (p < 0.001) but the polio group had more musculoskeletal conditions. In the mobility test, the polio participants walked slower in the timed-up-and-go test (t = 2.050, p = 0.042) and had a higher rate of recurrent falls (χ2 = 14.916, p < 0.001) than the no-polio disabled group. Conclusions The disabled people with a high risk of falling can be identified through a 10-minute screening (cause of disability, gender, disability grade, and gait stability testing). The physical conditions of the polio disabled people were relatively more affected.

A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

Relationship between Sleep Duration Trajectories and Self-Rated Depressive Symptoms in South Koreans with Physical Disabilities

Physically disabled persons can have sleep problems, which affects their mental health more than those in non-disabled people. However, there are few studies on the relationship between sleep duration and mental health targeting physically disabled people in South Korea, and existing studies on the disabled have mostly used data collected from convenience rather than nationally representative samples, limiting the generalization of the results. This study used data from the second wave of the Panel Survey of Employment for the Disabled (PSED, 2016–2018, 1st–3rd year). Participants included 1851 physically disabled individuals. The Chi-square test and generalized estimating equation (GEE) were used and the Akaike information criterion (AIC) value and the AIC log Bayes factor approximation were used to select sleep trajectories. This is the first study to elucidate multiple sleep trajectories in physically disabled people in Korea, and the relationship between sleep duration trajectories and self-rated depressive symptoms. People with physical disabilities who sleep more than 9 h have the highest risk of depression and need more intensive management as a priority intervention.

Assessing Stability of Crutch Users by Non-Contact Methods

Enhancing gait stability in people who use crutches is paramount for their health. With the significant difference in gait compared to users who do not require an assistive device, the use of standard gait analysis tools to measure movement for temporary crush users and physically disabled people proves to be more challenging. In this paper, a novel approach based on video analysis is proposed as non-contact low-cost solution to the more expensive alternative with the data collected from processed videos, two values are calculated: the Signal to Noise Ratio (SNR) of acceleration, and the Signal to Noise Ratio of the jerk (time derivative of acceleration), to assess the user’s stability while they walk with crutches. The adopted methodology has been tested on a total of 10 participants. Five are temporary users of assistive devices with one being a long-term user and the other four novice users, and five are disabled participants who use those assistive devices permanently. Preliminary results show differences between novice users, long-term users, and physically disabled users. The approach is promising and could improve the assessment of crutch user stability, allowing for the correction of gait for individuals while using an inexpensive non-contact setup and preventing unnecessary falls.