Electric Wheelchair Research Articles

Operator-centric joystick mapping for intuitive manual operation of differential drive robots

Intuitive joystick-based mobile robot operations are critical in terms of work efficiency in tasks where humans and robots work closely, such as in smart factories or electric wheelchairs. An operator-centric joystick mapping algorithm, based on a questionnaire study of 101 respondents, was proposed to determine the expected movement direction of a differential drive robot according to the joystick direction of the operator. The proposed approach considers the kinematic constraints of differential drive robots and maps the operator’s joystick control input to the robot velocity command by efficiently conveying the intention of the operator. This method generates a smooth robot velocity command from the continuous movement of the joystick without a sudden change in acceleration. The proposed algorithm was evaluated by 22 test subjects maneuvering a two-dimensional joystick module to control a virtual robot in a simulated environment visiting waypoints, and demonstrated superior performance when compared with two standard algorithms. The proposed algorithm was also implemented as a hardware system with a physical differential drive robot for testing in a real environment.

Quantitative Measurement of the Pressure and Shear Stress Acting on the Body of a Wheelchair User Using a Wearable Sheet-Type Sensor: A Preliminary Study.

To provide a safer sitting environment for wheelchair users, it is important to quantitatively measure the forces acting on the contact surface between the seat and the person in the wheelchair. In addition to the pressure acting on the buttocks, shear forces have received particular attention in recent years; however, measuring shear force is more difficult than measuring pressure. To obtain this measurement, a thin and flexible sensor that can be used in a natural state on a wheelchair is needed. Therefore, we constructed a measurement system using our previously developed wearable sheet-type sensor (0.9 mm thick). In this study, preliminary tests were conducted using human dummies before testing on humans. Sensors were placed in four locations on the humanoid dummy’s back and buttocks, and the electric wheelchair was tilted and reclined five times each. The results showed that the sensor output pattern was reproducible and valid enough to proceed to the next step. However, the shear force in the internal and external directions was greater than expected, which indicates that the equipment and testing methods must be reviewed. On the basis of the results obtained in this preliminary study, preparations will be made for testing on human subjects.

Trajectory Tracking and Collision Avoidance on Smart Wheel Chair

There have been many developments of wheelchairs as mobility aids, including electric wheelchairs. Wheelchairs sometimes still require manual steering. Therefore, in this research, a smart wheelchair is developed that can move automatically to the destination position from a predetermined position with a trajectory tracking system. The system deploys the odometry method, orientation angle using the output of the IMU-9DOF sensor with Kalman filter, and collision avoidance to avoid collisions with obstacles in front of it. The use of the Kalman filter improves the angle output that is close to the reference. In the trajectory tracking test, the wheelchair can approach the given reference position with a maximum error of 20 cm for the x-axis and 2 cm for the y-axis. The wheelchair collision avoidance test has been able to avoid collisions, as it successfully detects an obstacle less than 40 cm and avoids the collision correspondingly.

An Electric Wheelchair Manipulating System Using SSVEP-Based BCI System.

Most people with motor disabilities use a joystick to control an electric wheelchair. However, those who suffer from multiple sclerosis or amyotrophic lateral sclerosis may require other methods to control an electric wheelchair. This study implements an electroencephalography (EEG)-based brain–computer interface (BCI) system and a steady-state visual evoked potential (SSVEP) to manipulate an electric wheelchair. While operating the human–machine interface, three types of SSVEP scenarios involving a real-time virtual stimulus are displayed on a monitor or mixed reality (MR) goggles to produce the EEG signals. Canonical correlation analysis (CCA) is used to classify the EEG signals into the corresponding class of command and the information transfer rate (ITR) is used to determine the effect. The experimental results show that the proposed SSVEP stimulus generates the EEG signals because of the high classification accuracy of CCA. This is used to control an electric wheelchair along a specific path. Simultaneous localization and mapping (SLAM) is the mapping method that is available in the robotic operating software (ROS) platform that is used for the wheelchair system for this study.

Perceptions of street trees among Polish residents with motor disabilities

IntroductionSustainable cities ensure social inclusiveness for vulnerable communities through environmental solutions. Easy access to public facilities for all is a step to reduce inequalities and is linked to Goals 10 and 11 out of the Sustainable Development Goals. The main purpose of the study was to verify whether street trees in footways and footpaths affect walking. MethodsData was obtained from a Computer Assisted Web Interview (CAWI) conducted in January–February 2022 among 212 for people with a limited range of mobility (the users of walking frames, walkers, rollators, crutches, and manual or electric wheelchairs). ResultsThe results indicate that although street trees may cause sidewalk tiles to bulge, aggravate allergies, or present elevated risk in the case of falling branches, they are ultimately a desirable element of the streetscape. People are ready to experience some inconveniences (sidewalk tiles with small holes) just to allow better habitat for street trees. Moreover, trees planted along the footways/footpaths stimulate physical activity and people prefer having big trees in streetscapes. ConclusionsThe results of the study suggest a need for in-situ research of the impact that small holes in sidewalk tiles (size, pattern, location in the tile) have on the vibrations experienced by users while getting around. Studies on the correlation between the perception of pedestrian circulation comfort and the speed of walking on the tiles with holes should be continued.

Electric Wheelchair Hybrid Operating System Coordinated with Working Range of a Robotic Arm

Electric wheelchair-mounted robotic arms can help patients with disabilities to perform their activities in daily living (ADL). Joysticks or keypads are commonly used as the operating interface of Wheelchair-mounted robotic arms. Under different scenarios, some patients with upper limb disabilities such as finger contracture cannot operate such interfaces smoothly. Recently, manual interfaces for different symptoms to operate the wheelchair-mounted robotic arms are being developed. However, the stop the wheelchairs in an appropriate position for the robotic arm grasping task is still not easy. To reduce the individual’s burden in operating wheelchair in narrow spaces and to ensure that the chair always stops within the working range of a robotic arm, we propose here an operating system for an electric wheelchair that can automatically drive itself to within the working range of a robotic arm by capturing the position of an AR marker via a chair-mounted camera. Meanwhile, the system includes an error correction model to correct the wheelchair’s moving error. Finally, we demonstrate the effectiveness of the proposed system by running the wheelchair and simulating the robotic arm through several courses.

Fourteen-year change in activities of daily living of a quadriplegic, ventilator-managed patient injured by high cervical spinal cord injury during infancy: a case report

BackgroundRehabilitation of patients with high cervical spinal cord injury (CSCI) to improve activities of daily living (ADL) is challenging due to severe paralysis. In addition, pediatric patients with CSCI are rare, and literature describing ADL changes as the patient grows are limited. In this case report, we present the long-term change in ADL over time in a girl with severe high CSCI from an injury during infancy.Case presentationA 2 years and 6 months old girl, who was injured in a traffic accident, was diagnosed with C3 CSCI, resulting in complete quadriplegia and respiratory paralysis below C3. Thus, she was managed with a ventilator. Rehabilitation for quadriplegia, respiratory dysfunction, and autonomic neuropathy was started on the fifth day after the injury while she was in the intensive care unit. Six months after the injury, the patient was transferred to a hospital. Thereafter, she was discharged with nursing and care guidance provided to her family and environmental changes at home. Afterwards, she continued to acquire skills through writing training using a mouse stick, computer operation training, and electric wheelchair operation training, which enabled her to improve her ADL despite her severe disability. In terms of education, she was able to go through a regular elementary school, a regular junior high school, and then to a senior high school of a support school.ConclusionsWe believe that training that utilizes current technology and changes in the environment that are appropriate for daily life are important for improving the ADL of children with severe CSCI.

A Dataset for Temporal Semantic Segmentation Dedicated to Smart Mobility of Wheelchairs on Sidewalks.

In smart mobility, the semantic segmentation of images is an important task for a good understanding of the environment. In recent years, many studies have been made on this subject, in the field of Autonomous Vehicles on roads. Some image datasets are available for learning semantic segmentation models, leading to very good performance. However, for other types of autonomous mobile systems like Electric Wheelchairs (EW) on sidewalks, there is no specific dataset. Our contribution presented in this article is twofold: (1) the proposal of a new dataset of short sequences of exterior images of street scenes taken from viewpoints located on sidewalks, in a 3D virtual environment (CARLA); (2) a convolutional neural network (CNN) adapted for temporal processing and including additional techniques to improve its accuracy. Our dataset includes a smaller subset, made of image pairs taken from the same places in the maps of the virtual environment, but from different viewpoints: one located on the road and the other located on the sidewalk. This additional set is aimed at showing the importance of the viewpoint in the result of semantic segmentation.

Development of an intention estimation model based on gaze and face information for electric wheelchair operation support

AbstractIn recent years, various user interfaces have been developed to meet the diverse needs of physically disabled persons. In this paper, we developed a method to identify gazing and facial movements based on gaze time and eye/face information and developed an electric wheelchair that can be operated with the user's natural gazing and facial movements. This intention estimation model is composed of 1DCNN and LSTM layers. First, 1DCNN is used to extract features from gaze and face information, and then the extracted features are input to LSTM to estimate the user's intentions regarding movement. The evaluation experiments suggest that the combination of gaze and face information improves the estimation accuracy and contributes to the classification. Furthermore, it was confirmed that adding a convolutional filter layer to the LSTM layer improved the accuracy.

Effect of time windows in LSTM networks for EEG-based BCIs

People with impaired motor function could be helped by an effective brain–computer interface (BCI) based on a real-time electroencephalogram (EEG) and artificial intelligence algorithms. However, current methodologies for interpreting patient instructions from an EEG are not accurate enough to be completely safe in a real-world situation , where a poor decision would place their physical integrity at risk, such as when traveling in an electric wheelchair in a city. For various reasons, such as the low signal-to-noise ratio of portable EEGs or the effects of signal contamination (disturbances due to user movement, temporal variation of the features of EEG signals, etc.), a long short-term memory network (LSTM) (a type of recurrent neural network) that is able to learn data flow patterns from EEG signals could improve the classification of the actions taken by the user. In this paper, the effectiveness of using an LSTM with a low-cost wireless EEG device in real time is tested, and the time window that maximizes its classification accuracy is studied. The goal is to be able to implement it in the BCI of a smart wheelchair with a simple coded command protocol, such as opening or closing the eyes, which could be executed by patients with reduced mobility. Results show a higher resolution of the LSTM with an accuracy range between 77.61 and 92.14% compared to traditional classifiers (59.71%), and an optimal time window of around 7 s for the task done by users in this work. In addition, tests in real-life contexts show that a trade-off between accuracy and response times is necessary to ensure detection.

‘When I use the electric wheelchair, I can be myself’ – real-life stories about occupational identity construction

Background Young and adult users of electric wheelchairs (EWs) describe how EWs have personal, functional, emotional, and symbolic values and are considered by some to be part of the self. Aim The aim of this study was to increase our understanding of how occupational identity is constructed in the daily practices of EW users. Material and methods Context-based, in-depth oral stories and filmed sequences of daily practice enactments of persons who have used an EW since childhood were the basis for the narrative analysis. Findings The findings elucidate how the informants enact and tell about their identity-development in response to daily and relational practices, and its relevance to the informant’s sense of self, belonging, competence, life-prospects, conduct, and awareness of shifting values, and this was likewise demonstrated in different appearances and roles related to social recognition. A model illustrating the findings is proposed. Conclusions and significance Contextual values and exploring experiences, such as possibilities to develop competences and roles, along with encountering social recognition, but also hindering regulations and adversities, influence the development of occupational identities. Findings in this study can contribute to increased understanding, conscious political decisions, as well as a more person-centred approach within healthcare.

계단 이동이 가능한 전동휠 구조 설계에 관한 연구

In this paper, we would like to report the advanced structure of electric-powered wheel that can go upstairs or downstairs. One of the reasons of electric wheelchair accidents that occur recently is the rollover accident from wheel jamming at a step or stairs. Commercially available electric-powered wheels have a serious problem with malfunctioning of electric wheels. When the gap or step difference is larger than 5 cm, the electric wheel is not working properly. We have intensively investigated this matter by using a variable track wheel method rather than the conventional triangular wheel method that had been studied mostly in the past. We have engineered a prototype electric wheel with a variable track wheel which is tested at various conditions. Our result shows that the performance of the electric-powered wheel with variable track wheel is stable for both of flatland and stairs due to the contracting action of actuator.

Effect of Load Cell Load Calibration on Electric Wheelchair

A wheelchair is an assistive device for patients who are seriously injured or ill. Especially for people with disabilities or people who can't walk using their feet. For patients who experience total paralysis such as pain in the nerves to move the wheelchair, someone needs to push the wheelchair. If there is no one around the patient, the patient has difficulty moving the wheelchair using his hands and feet to change positions. In this research, an electric wheelchair has been created using a load cell control with body position as the driving output. Based on the test results, if the body leans forward then the wheelchair moves forward, if the body leans back then the wheelchair moves backwards, If the body leans to the left then the wheelchair moves to the left and if the body leans to the right then the wheelchair moves to the right. This study aims to analyze the ability of the load cell as the propulsion output of the electric wheelchair to the user's weight. In the results of the study, it can be seen that body weight can have a greater effect if the user's mass is getting heavier.

Electric Wheelchair Design and its Impacts on Life among the Disabled Individuals: A Review

Electric Wheelchair Design and its Impacts on Life among the Disabled Individuals: A Review

Autonomous detection and ascent of a step for an electric wheelchair

With the number of individuals using a wheelchair on the rise, the issue of removing architectural barriers, or at least overcoming them, has to be faced to improve independence, inclusiveness, and participation of wheelchair users. Some electric wheelchairs can climb and descend stairs and obstacles, however, the actual operations required to do so safely may be complex and may require an experienced or trained user. To overcome this issue, a method to first detect and classify a step and then autonomously climb it safely is proposed here. The same method is then applied and tested on an actual stair-climbing wheelchair prototype to prove its reliability in different conditions.

전동휠체어 구동용 표면 부착형 영구자석 동기전동기 최적 설계

This paper proposes the optimal design of a surface-mounted permanent magnet synchronous motor for electric wheelchair applications. The Finite Element Method (FEM) ensures an accurate analysis of the motor. However, its calculation time is too large. Moreover, as the objective function or design variable increases, the computation time increases exponentially. Therefore, a multi-objective function optimization algorithm was applied to reduce the FEM’s analysis time. The optimal design is compared with a commercial motor with the same power output. The stacking length was reduced by 42.0% and the volume was reduced by 34.3%. To validate the proposed design’s functionality, a prototype motor was fabricated and tested. The experiment’s results demonstrated a high similarity to those of the theoretical analysis.

Design and Implementation of Solar Based Electric Wheelchair

This paper concentration on the reducing expenditure for the mechanically setup & designation of a solar based electric wheelchair with solid structure design and control system for the handicapped persons. In a country like India, most of the people distressed of temporary or permanent disabilities due to illnesses or accidents there are some person can’t afford to be expensive electric wheelchair. That’s why a developed of electric wheel chair is proposed in this paper which contains more features and a developed control system along with the reduced of manufacturing price & design about two to three times of recent market cost.

Reprint of: An embedded lightweight SSVEP-BCI electric wheelchair with hybrid stimulator

Electric wheelchairs, as mobile auxiliary equipment, improve the quality of life and self-independence of the disabled. The brain-computer interface (BCI) is used to establish a direct connection between the brain and the wheelchair, which adopts the electroencephalogram (EEG) signal to control the wheelchair. Compared with other types of BCI, the steady-state visual evoked potentials (SSVEP)-BCI is more suitable to control the electric wheelchair due to the advantages of higher information transmission rate (ITR), higher signal-to-noise ratio (SNR), and less training. However, the existing SSVEP-BCI electric wheelchairs need to be equipped with at least one personal computer to drive the visual stimulator and process EEG signals in real-time. As a result, the electric wheelchair system is complicated, bulky, and limited in movement flexibility, so it is difficult to popularize in real-life scenarios. Therefore, to improve the portability and applicability of the SSVEP-BCI electric wheelchair, a lightweight SSVEP-BCI system is needed, which should be as light and energy-saving as possible while meeting functional requirements.This paper presents an embedded lightweight SSVEP-BCI electric wheelchair with a hybrid stimulator. A hybrid hardware-driven visual stimulator is designed, which combines the advantages of liquid crystal display (LCD) and light-emitting diode (LED) to achieve lower energy consumption than the traditional LCD stimulator. In addition, a lightweight BCI framework is designed to realize BCI program functions on the embedded platform for achieving similar performance as those on a personal computer. Experiments on real systems show that our embedded lightweight SSVEP-BCI electric wheelchair can be successfully operated by all eight subjects with a 93.9% average success rate of command operation. In addition, compared with the traditional LCD stimulator, the hybrid hardware-driven visual stimulator can save up to 27% of energy.

Development of an Intention Estimation Model Based on Gaze and Face Information for Electric Wheelchair Operation Support

Development of an Intention Estimation Model Based on Gaze and Face Information for Electric Wheelchair Operation Support

Development of Electromyography Signal Contraction Detection Using the Double Threshold Method for Controlling Wheelchair

The consequence of spinal cord injury (SCI) is the malfunction of some parts of the body. This observation especially applies to trauma at the cervical level, because both patients' hands and legs are no longer functioning. The purpose of this study was to determine the mechanism of the comparator treshold system in electric wheelchairs for patients with paralysis. The research contribution is to get a treshold mechanism that can make a wheelchair run smoothly without being affected by the strength of the user's unstable muscle contractions. To set the muscle reference value, connect the transmitter to Android using USB Cable. On Android there are 2 settings modes, namely manual and auto settings. The method used in auto mode is the transmitter will take 100 contraction and 100 relaxation data and multiplied by certain constants to get the upper and lower threshold values. In setting the threshold manually, the value is set based on the strength of the patient's contractions that are displayed on Android manually. Where in the threshold setting manually obtained response 93.3% of forward movement, 100% of turn left movement, 100% of turn right movement and 93.3% of backward movement. Meanwhile, the threshold setting automatically gets 80% response for forward movements, 93.3% for turn left movements, 86.6% for turn right movements and 93.3% for backward movements. The results of the tapping into 4 parts of the muscle can be implemented to detect muscle contractions so that the wheelchair can move according to orders. The problem obtained in this study is that there are many tapping points on the face so that it interferes with the comfort and time of installing electrodes on the face, also the patient's muscle reference setting system on Android still needs the help of others. In the future, it is expected to reduce tapping points and improve the efficiency of muscle threshold settings.