Smart Assistive Device Research Articles

Toward a better understanding of barriers to wayfinding technology use for people with disabilities

ABSTRACT Wayfinding is the process of navigating from one’s present location to their desired location. While wayfinding technologies are increasingly used by people with disabilities, there is little understanding of the barriers specific to wayfinding technology. The objective of this study was to understand the wayfinding technology barriers experienced by Canadians with disabilities. A total of 213 participants with varying disabilities (i.e. mobility, visual, hearing, memory and learning disabilities) completed a survey of open-ended questions about their personal experiences with different types of technologies. Technologies were categorized into public (i.e. digital and tactile interfaces) and personalized (i.e. mobile/website applications, wearable devices, smart assistive devices), and qualitative content analysis was used. Main themes were identified and either common across both groups (i.e. compatibility, demands on personal resources, information provision, interactability) or specific to one technology type (i.e. stigma, specific to personalized technology). Detailed subthemes provided greater specificity on the types of barriers encountered. For example, infection risk was noted as a barrier to public technology and high costs was a barrier for personalized technology. Results support the inclusion of wayfinding technology within accessibility standards and provide insights to clinicians on how to best support people with disabilities and their use of technology.

The highs and lows of lifting loads: SPM analysis of multi-segmental spine angles in healthy adults during manual handling with increased load

Introduction: Manual handling personnel and those performing manual handling tasks in non-traditional manual handling industries continue to suffer debilitating and costly workplace injuries. Smart assistive devices are one solution to reducing musculoskeletal back injuries. Devices that provide targeted assistance need to be able to predict when and where to provide augmentation via predictive algorithms trained on functional datasets. The aim of this study was to describe how an increase in load impacts spine kinematics during a ground-to-platform manual handling task. Methods: Twenty-nine participants performed ground-to-platform lifts for six standardised loading conditions (50%, 60%, 70%, 80%, 90%, and 100% of maximum lift capacity). Six thoracic and lumbar spine segments were measured using inertial measurement units that were processed using an attitude-heading-reference filter and normalised to the duration of the lift. The lift was divided into four phases weight-acceptance, standing, lift-to-height and place-on-platform. Statistical significance of sagittal angles from the six spine segments were identified through statistical parametric mapping one-way analysis of variance with repeated measures and post hoc paired t-tests.Results: Two regions of interest were identified during a period of peak flexion and a period of peak extension. There was a significant increase in spine range of motion and peak extension angle for all spine segments when the load conditions were increased (p < 0.001). There was a decrease in spine angles (more flexion) during the weight acceptance to standing phase at the upper thoracic to upper lumbar spine segments for some condition comparisons. A significant increase in spine angles (more extension) during the place-on-platform phase was seen in all spine segments when comparing heavy loads (>80% maximum lift capacity, inclusive) to light loads (<80% maximum lift capacity) (p < 0.001).Discussion: The 50%–70% maximum lift capacity conditions being significantly different from heavier load conditions is representative that the kinematics of a lift do change consistently when a participant’s load is increased. The understanding of how changes in loading are reflected in spine angles could inform the design of targeted assistance devices that can predict where and when in a task assistance may be needed, possibly reducing instances of back injuries in manual handling personnel.

AI-Enabled Smart Glasses for People with Severe Vision Impairments

Over the last decade, there has been significant research on how smart assistive devices with artificial intelligence (AI) built into them can assist people with severe vision impairments to comprehend their surroundings. These devices come in various forms such as smartphone applications, smart-glasses, and smart canes. Smart glasses have gained popularity lately due to recent technological advancements, as well as their natural position in front of the user's eyes. However, there has been limited research to understand how people with severe vision impairments would prefer to interact with them. The objective of this project is to investigate the use of AI-enabled smart-glasses to aid individuals with severe vision impairments. The research aims to comprehend the differences between the types of research conducted by researchers and the needs and desires of the community. The study will utilise a Design Thinking approach and involve vision-impaired users throughout the project by utilising co-design methods. The research will involve the development of smart-glass application prototypes through iterative case studies with individuals who are blind, have low-vision, and have cerebral vision impairment (CVI). The goal is to understand the users' preferred interaction model from their lived experiences. The outcome of the research will also be a software architecture that enables people with severe vision impairments to seamlessly access information about their surroundings.

A Control System Using Speech Recognition AMR in Robotic System

Voice command is currently a vital task for developing smart assistive devices, especially since the frequency of accidents continues to climb, posing a huge shift in handicapped people’s lifestyles which makes producing a material to support them in their daily lives a significant challenge. One of the proposed options is to add an embedded system with a machine learning algorithm represented by voice recognition to assist handicapped people. In this paper, we have implemented a voice command control system in Arabic through an AMR Voice application in Smartphone with a microcontroller demonstrates a sophisticated integration of hardware and software technologies. The utilization of Bluetooth technology which acts as a communication channel with the LED light circuit , which will then be connected to the Arduino to create a system based on voice commands.

Assistive device to control prosthetic hand movements using machine learning approach

Smart Assistive devices developed to support the disabled people suffered with Monoplegia. The Monoplegia kind of a paralysis which have the impact on one arm or one leg. The person affected with this disease unable to move the hand or leg to perform their regular activities. The rehabilitation process of paralysis affected patient involves make them to perform their activities by own with the help of an assistive smart device. The device must be capable to identify the user intension of activity and assist them to perform the same task. The proposed work makes use of 3D prosthetic hand to replace the inactive hands of the patients. The prosthetic hands are synthetic extensions that are used to support or supplement the affected or disabled parts. The Electromyography sensors installed on this prosthetic hand produces the biomedical signal that records muscle contractions. These sensors are capable of detecting muscle movements and high variations in real time. The proposed work makes use of Electromyography (EMG) signals to build an assist system and identify the intended activity. These enables patients with hand paralyzed to perform the inactive hand functions.

Smartphone: A smart assistive device for people visual disabilities among COVID-19 pandemic.

Smartphones are becoming one of the most indispensable gadgets for everyone in today's digital world, with the continued incorporation of computer technology. For the past few years, the interaction between human and smartphone content has been improved significantly with innovative technologies using gestures, haptic, and sound instead of visual-based interaction. Such technologies are in the form of built-in features and accessible apps. Such an advanced way of interface design helps to access not only the content in phones but also assist to perform daily living activities. Evidence shows that such smartphones technology help in executing a wide range of functioning among people with visual impairment. Today, the COVID-19 pandemic causes a challenge to everyone, including one living with a vision loss, in maintaining the daily supplies and civic life. Unfortunately, the majority of such people cannot access smartphones, so they depend on a simple basic phone. It is the time to promote the benefits of such evolving smartphones technology in all the corners of the health-care sectors, practitioners, special educators, and even family members. Meanwhile, the relevant ministerial divisions of the Government of India need to develop a clear policy to augment access to smartphones, particularly among people with visual disabilities.

Adaptability of Assistive Mobility Devices and the Role of the Internet of Medical Things: Comprehensive Review.

BackgroundWith the projected upsurge in the percentage of people with some form of disability, there has been a significant increase in the need for assistive mobility devices. However, for mobility aids to be effective, such devices should be adapted to the user’s needs. This can be achieved by improving the confidence of the acquired information (interaction between the user, the environment, and the device) following design specifications. Therefore, there is a need for literature review on the adaptability of assistive mobility devices.ObjectiveIn this study, we aim to review the adaptability of assistive mobility devices and the role of the internet of medical things in terms of the acquired information for assistive mobility devices. We review internet-enabled assistive mobility technologies and non–internet of things (IoT) assistive mobility devices. These technologies will provide awareness of the status of adaptive mobility technology and serve as a source and reference regarding information to health care professionals and researchers.MethodsWe performed a literature review search on the following databases of academic references and journals: Google Scholar, ScienceDirect, Institute of Electrical and Electronics Engineers, Springer, and websites of assistive mobility and foundations presenting studies on assistive mobility found through a generic Google search (including the World Health Organization website). The following keywords were used: assistive mobility OR assistive robots, assistive mobility devices, internet-enabled assistive mobility technologies, IoT Framework OR IoT Architecture AND for Healthcare, assisted navigation OR autonomous navigation, mobility AND aids OR devices, adaptability of assistive technology, adaptive mobility devices, pattern recognition, autonomous navigational systems, human-robot interfaces, motor rehabilitation devices, perception, and ambient assisted living.ResultsWe identified 13,286 results (excluding titles that were not relevant to this study). Then, through a narrative review, we selected 189 potential studies (189/13,286, 1.42%) from the existing literature on the adaptability of assistive mobility devices and IoT frameworks for assistive mobility and conducted a critical analysis. Of the 189 potential studies, 82 (43.4%) were selected for analysis after meeting the inclusion criteria. On the basis of the type of technologies presented in the reviewed articles, we proposed a categorization of the adaptability of smart assistive mobility devices in terms of their interaction with the user (user system interface), perception techniques, and communication and sensing frameworks.ConclusionsWe discussed notable limitations of the reviewed literature studies. The findings revealed that an improvement in the adaptation of assistive mobility systems would require a reduction in training time and avoidance of cognitive overload. Furthermore, sensor fusion and classification accuracy are critical for achieving real-world testing requirements. Finally, the trade-off between cost and performance should be considered in the commercialization of these devices.

Designing a Smart Bath Assistive Device Based on Measuring Inner Water Temperature for Bathing Temperature Monitoring.

Today, taking a bath is not only a means to keep clean, but also to reduce fatigue and stress. However, taking a bath with hot water for a long time can also be dangerous, leading to scalding or even a heart attack. To prevent these risks, several studies based on measuring bio-signals have been conducted, but due to high prices, difficulty of use, and restricted functions, these studies’ recommendations cannot be easily adopted by the public. Therefore, developing accurate methods to measure bathing temperature and bathing time should be the most direct approach to solve these problems. In this study, a smart bath assistive device based on an inner water temperature measurement function is proposed. Prior to development of the device, a bathing environment was emulated with six temperature sensors affixed to different depths to find the optimal depth for measuring bathing temperature. According to the measurement results, the device was designed in a mushroom shape with the cap part floating on the water’s surface and housing the electronic components, and temperature sensors within the stem part were immersed in the water approximately 5 cm below the surface to measure the inner water temperature. Due to the low-power consuming Advanced RISC Machine (ARM) processor and waterproof design, the device is able to float in hot water and monitor the bathing temperature variation over a long period of time. The device was compared alongside a commercial analog bathing thermometer to verify the performance of temperature measurements. In addition, a compensation algorithm was developed and programmed into the device to improve the accuracy of measurements. Processed data is transmitted by Bluetooth to a dedicated Android app for data display and storage. The final results show that the proposed device is highly accurate and stable for monitoring bathing temperature.

A thermally flexible and multi-site tactile sensor for remote 3D dynamic sensing imaging

A flexible, multi-site tactile and thermal sensor (MTTS) based on polyvinylidene fluoride (resolution 50 50) is reported. It can be used to implement spatial mapping caused by tactile and thermal events and record the two-dimensional motion trajectory of a tracked target object. The output voltage and current signal are recorded as a mapping by sensing the external pressure and thermal radiation stimulus, and the response distribution is dynamically observed on the three-dimensional interface. Through the mapping relationship between the established piezoelectric and pyroelectric signals, the piezoelectric component and the pyroelectric component are effectively extracted from the composite signals. The MTTS has a good sensitivity for tactile and thermal detection, and the electrodes have good synchronism. In addition, the signal interference is less than 9.5% and decreases as the pressure decreases after the distance between adjacent sites exceeds 200 mm. The integration of MTTS and signal processing units has potential applications in human-machine interaction systems, health status detection and smart assistive devices.

Intelligent Assistive System for Visually Disabled Persons

There is increasin demand for smart widgets which make people more comfortable. Though many research works have done on current existing devices/systems for visually impaired people are not providing facilities them enough. The imperceptible people read Braille scripted books only, so here developing a new device that will assist the visually impaired people and also providing desired language reading facility. This smart assistive device will help visually impaired people gain increased independence and freedom in society. This device has an obstacle detection sensor to intimate the obstacles to the visually impaired person and a camera connected to Raspberry pi to convert image to text using Optical Character Recognition (OCR). The read data is converted to speech using text to speech synthesizer. This will useful for visually impaired people for surviving in outdoor environment as well as reading books which are in normal script. The read data can be stored in database for further reading and it can be retrieve by giving a command.

Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury.

Effective neurological rehabilitation requires long term assessment and treatment. The rapid progress of virtual reality-based assistive technologies and tele-rehabilitation has increased the potential for self-rehabilitation of various neurological injuries under clinical supervision. The objective of this study was to develop a fuzzy inference mechanism for a smart mobile computing system designed to support in-home rehabilitation of patients with neurological injury in the hand by providing an objective means of self-assessment. A commercially available tablet computer equipped with a Bluetooth motion sensor was integrated in a splint to obtain a smart assistive device for collecting hand motion data, including writing performance and the corresponding grasp force. A virtual reality game was also embedded in the smart splint to support hand rehabilitation. Quantitative data obtained during the rehabilitation process were modeled by fuzzy logic. Finally, the improvement in hand function was quantified with a fuzzy rule database of expert opinion and experience. Experiments in chronic stroke patients showed that the proposed system is applicable for supporting in-home hand rehabilitation. The proposed virtual reality system can be customized for specific therapeutic purposes. Commercial development of the system could immediately provide stroke patients with an effective in-home rehabilitation therapy for improving hand problems.

Low-power depth-based descending stair detection for smart assistive devices

Assistive technologies aim at improving personal mobility of individuals with disabilities, increasing their independence and their access to social life. They include mechanical mobility aids that are increasingly employed amongst the older people who rely on them. However, these devices might fail to prevent falls due to the under-estimation of approaching hazards. Stairs and curbs are among these potential dangers present in urban environments and living accommodations, which increase the risk of an accident. We present and evaluate a low-complexity algorithm to detect descending stairs and curbs of any shape, specifically designed for low-power real-time embedded platforms. Based on a passive stereo camera, as opposed to a 3D active sensor, we assessed the detection accuracy, processing time and power consumption. Our goal being to decide on three possible situations (safe, dangerous and potentially unsafe), we achieve to distinguish more than 94 % dangers from safe scenes within a 91 % overall recognition rate at very low resolution. This is accomplished in real-time with robustness to indoor/outdoor lighting conditions. We show that our method can run for a day on a smartphone battery.

Smart Assistive Device for Visually Impaired People

Smart Assistive Device for Visually Impaired People