Electric-powered Wheelchair Research Articles

Perceptions and assessment of a novel robotic wheelchair transfer system

Objectives Wheelchair transfers risk injury to users and caregivers. Conventional transfer devices are injury-prone and time inefficient. The Powered Personal Transfer System (PPTS), utilizing a modified Electric Powered Wheelchair (EPW) and a hospital bed, provides a no-lift solution for bed-to-wheelchair transfers. Objective 1: Assess PPTS workload compared to existing methods. Objective 2: Evaluate PPTS EPW in daily mobility tasks. Objective 3: Perform Rehabilitation Engineering and Assistive Technology Society of North America (RESNA) wheelchair standards testing for PPTS EPW stability and performance. Methods Fifteen professional and family caregivers, experienced in assisting EPW users, performed transfers between the bed and EPW using the PPTS. Subsequently, participants drove the PPTS EPW providing ratings on the ease of performing mobility tasks. Wheelchair testing was conducted following RESNA standards. Setting : Simulated bedroom in a laboratory setting. Results Participants reported low workload demands for employing the PPTS and indicated a preference for the PPTS over existing transfer devices/methods. Ease of performing everyday mobility tasks was not significantly different between the modified PPTS and the commercially available original manufacturer equipment EPW (p > 0.05). RESNA wheelchair standards testing confirmed that the PPTS EPW preserves functionality, stability and performance when compared to similar commercially available EPWs. Conclusion The PPTS demonstrated promise in offering a practical, low demanding, and safe solution for transfers. It has the potential to enhance user and caregiver safety by reducing the incidence of caregiver injuries associated with assisting in transfer tasks. In addition to its efficiency and ease of use, it is an advancement in assistive technology for wheelchair transfers.

Safety-Based Speed Control of a Wheelchair Using Robust Adaptive Model Predictive Control.

Electric-powered wheelchairs play a vital role in ensuring accessibility for individuals with mobility impairments. The design of controllers for tracking tasks must prioritize the safety of wheelchair operation across various scenarios and for a diverse range of users. In this study, we propose a safety-oriented speed tracking control algorithm for wheelchair systems that accounts for external disturbances and uncertain parameters at the dynamic level. We employ a set-membership approach to estimate uncertain parameters online in deterministic sets. Additionally, we present a model predictive control scheme with real-time adaptation of the system model and controller parameters to ensure safety-related constraint satisfaction during the tracking process. This proposed controller effectively guides the wheelchair speed toward the desired reference while maintaining safety constraints. In cases where the reference is inadmissible and violates constraints, the controller can navigate the system to the vicinity of the nearest admissible reference. The efficiency of the proposed control scheme is demonstrated through high-fidelity speed tracking results from two tasks involving both admissible and inadmissible references.

Optimization of Wheelchair Control via Multi-Modal Integration: Combining Webcam and EEG

Even though Electric Powered Wheelchairs (EPWs) are a useful tool for meeting the needs of people with disabilities, some disabled people find it difficult to use regular EPWs that are joystick-controlled. Smart wheelchairs that use Brain–Computer Interface (BCI) technology present an efficient solution to this problem. This article presents a cutting-edge intelligent control wheelchair that is intended to improve user involvement and security. The suggested method combines facial expression analysis via a camera with EEG signal processing using the EMOTIV Insight EEG dataset. The system generates control commands by identifying specific EEG patterns linked to facial expressions such as eye blinking, winking left and right, and smiling. Simultaneously, the system uses computer vision algorithms and inertial measurements to analyze gaze direction in order to establish the user’s intended steering. The outcomes of the experiments prove that the proposed system is reliable and efficient in meeting the various requirements of people, presenting a positive development in the field of smart wheelchair technology.

Methodology based on machine learning through neck motion and POF-based pressure sensors for wheelchair operation

Polymer Optical Fiber (POF)-based sensors have gained recognition in recent years for biomedical applications because of their low cost, physical properties, and feasibility. A novel methodology is proposed here for classifying neck movements using POF- based pressure sensors and machine learning algorithms. To address this, signal pre-processing, feature extraction, and selection methods are implemented, considering variance, root mean square, and Hjorth parameters. Linear Discriminant Analysis, Support Vector Machine, k-Nearest Neighbors (kNN), and Decision Tree (DT) were used for classification. A maximum accuracy of 0.91 was obtained with kNN and DT for recognizing four neck movements by using the best discriminant nine features. These findings indicate that the proposed methodology is suitable for neck-motion classification using POF-based pressure sensors. Future work will focus on the implementation of this strategy for the design of intelligent Human Machine Interfaces based on electric-powered wheelchairs, which would allow for more independence for people with upper- and lower-limb disabilities.

Investigation of the Performance of Plugging Braking System as a Hill Descent Control (HDC) for Electric-Powered Wheelchair

Recently, a study on Electric Powered Wheelchairs (EPWs) has become significant because they can enhance the mobility of individuals with disabilities. One of the issues on EPW is during descending on a slope because it is difficult to control the speed and prevent it from slipping. Moreover, the manual braking system is frequently used for speed control by pressing the brake lever. The complexity of the task increases significantly when dealing with elderly or paralyzed users with physical limitations. Consequently, the risk of collisions and injuries is elevated. This research seeks to develop a hill descent control (HDC) system for an EPW to address these challenges. By implementing HDC into EPW, the EPW's speed can be controlled, thus increasing the safety of the EPW while descending on the slope. In this study, the plugging brake system is introduced as a hill descent control (HDC) mechanism to inhibit the acceleration of the EPW and ensure it maintains a constant speed during downhill descents. The plugging voltage will be controlled based on the desired speed of 0.6 m/s. To maintain the speed of the EPW, the PID control is used as a control strategy for HDC. The simulation work in Matlab Simulink has analyzed the performance of the plugging brake system with HDC. The results obtained from the simulation reveal that, despite starting with a high initial braking speed of 2.5 m/s, the Electric Powered Wheelchair (EPW) can consistently maintain its velocity at the desired target value of v_d = 0.6 m/s during the descent on the slope. Furthermore, the amplitude response for the PID control shows the settling time is 2.3 s, and the steady-state error is ±0.05. Based on the simulation results, it can be approved that the proposed HDC in the plugging brake system can prevent the EPW from accelerating while descending on the slope and improve the safety of the EPW.

A heuristic-based approach for assessing usability in electric powered wheelchairs: A preliminary investigation

ObjectiveAn important issue related to electric powered wheelchair (EPW) is usability. Recent studies did not use heuristic evaluation and did not consider users’ and developers’ participation in the usability evaluation process of the EPW, especially when it has to be driven using alternative commands. Thus, this study investigates the use of heuristics to evaluate the usability of EPW driven by alternative commands, considering the opinion of users and assistive technology (AT) development professionals. MethodsThe study was carried out with 54 participants: 28 EPW users (Group I) and 26 AT developers (Group II). We built a set of 25 heuristics that affects EPW usability. Participants rated each of the 25 heuristics according to their importance for the usability of EPW using the five-point Likert scale. We used the R Software to perform the Wilcoxon Mann–Whitney test as a statistical comparisons test between Group I and II. ResultsThe results showed a statistically significant difference (p<0.05) between Group I and II in the evaluation of 16 heuristics. We identified an important set of heuristics that could help evaluate and improve the usability of EPW. ConclusionThe findings highlighted the importance of considering users’ and developers’ points of view in developing an EPW and its evaluation criteria. It could help the design of the device match the user's needs and expectations. The set of heuristics in this study can be adapted to evaluate other devices’ usability using the heuristic evaluation approach.

Power-assist on slope with velocity compensation for attendant-propelled electric wheelchairs

Up to now, numerous electric-powered wheelchairs (EPWs) have been developed for the disabled and the elderly. Among these EPWs, the traditional attendant-propelled power-assist wheelchairs (APAWs) usually run at a preset speed and greatly reduce the attendant's burden. Since the attendant's operating feeling is essential for the widespread use of the APAWs, many control approaches have been studied and developed. In the power-assist of our developed APAW, the speed of the wheelchair is controlled by the attendant's force to keep an appropriate burden with a natural operational feeling. In this study, we clarify the fact that the handle velocity of the APAW inevitably changes when passing through a slope, which causes the attendant to have an uncomfortable feeling. This phenomenon and its result in the uncomfortable feeling have not been reported yet. Consequently, in order to reduce or eliminate such uncomfortable feelings, we construct an APAW model on the slope and propose a velocity compensation method. From simulations and experiments, the validity of the proposed velocity compensation control is verified.

Compressive sensing applied to SSVEP-based brain–computer interface in the cloud for online control of a virtual wheelchair

People with severe motor disabilities have great challenges in achieving independence, particularly driving or controlling manually robotic wheelchairs. Existing assistive technologies for robotic wheelchair control often fail to address user needs adequately, becoming necessary an appropriate evaluation of usability and user’s satisfaction for these systems. In fact, user experience and satisfaction are crucial in determining effectiveness, usability and acceptance of these technologies. The aim is to enhance the quality of life of individuals with severe motor disabilities, increasing their independence to perform some daily activities, such as locomotion. This study proposes a cloud Steady-State Visual Evoked Potential (SSVEP)-based Brain–Computer Interface (BCI) system to evaluate its performance through the user experience in commanding a virtual electric-powered wheelchair in a training simulator. Moreover, this study compares traditional wheelchair command modes, such as input interfaces using JoyStick (JS) and Eye Tracker (ET), through standardized questionnaires to measure motivation, ease of use, workload, discomfort, sense of presence and other relevant parameters. The analysis of user experience reveals high levels of motivation, enjoyment, and usability when using the cloud SSVEP-based BCI proposed here. Although our BCI demands higher mental work and discomforts than both ET and JS, its potential for improving the user’s performance is demonstrated here. The findings of this research provide valuable insights for researchers and practitioners in the field of assistive technologies, enabling the development of more personalized systems based on the user’s experience. The main contributions of this study lie in a cloud BCI approach and a comprehensive evaluation methodology to evaluate the user’s experience.

Electric powered wheelchair control using user-independent classification methods based on surface electromyography signals.

Wheelchairs are one of the most popular assistive technology (AT) among individuals with motor impairments due to their comfort and mobility. People with finger problems may find it difficult to operate wheelchairs using the conventional joystick control method. Therefore, in this research study, a hand gesture-based control method is developed for operating an electric-powered wheelchair (EPW). This study selected a comfort-based hand position to determine the stop maneuver. An additional exploration was undertaken to investigate four gesture recognition methods: linear regression (LR), regularized linear regression (RLR), decision tree (DT), and multi-class support vector machine (MC-SVM). The first two methods, LR and RLR, have promising accuracy values of 94.85% and 95.88%, respectively, but each new user must be trained. To overcome this limitation, this study explored two user-independent classification methods: MC-SVM and DT. These methods effectively addressed the finger dependency issue and demonstrated remarkable success in recognizing gestures across different users. MC-SVM has about 99.05% of both precision and accuracy, and the DT has about 97.77% accuracy and precision. All six participants were successful in controlling the EPW without any collisions. According to the experimental results, the proposed approach has high accuracy and can address finger dependency issues.

Design and Manufacturing of Electronic Detachable Wheelchair

Abstract: The electric-powered wheelchair is a wheelchair that is propelled by means of an electric motor rather than manual power. Motorized wheelchairs are useful for those who are not able to impel a manual wheelchair or who may need to employ a wheelchair for distances or over terrain which would be strenuous in a manual wheelchair. They may also be used not just by people with conventional mobility impairments, but also by people with cardiovascular and fatigue-based conditions. Electric wheelchairs have enhanced the quality of life for many people with physical disabilities through the mobility they afford. The selection of power chair will rely on many factors; including the kind of surface setting the chair will be driven over, the need to settle thresholds and curbs, and clearance widths in accustomed environment. The most fundamental job of the chair is to take input from the user, usually in the form of a small joystick, and decipher that motion into power to the wheels to move the person in the preferred direction. The last few years have seen abundant improvements and models that give the user unmatched control of the wheelchair in terms of both user effort and vehicle aptitude

Evaluation of Power Wheelchair Dynamic Suspensions for Tip Prevention in Non-ADA Compliant Surfaces

ObjectiveTo evaluate the driving performance and usability of a mobility enhancement robot (MEBot) wheelchair with 2 innovative dynamic suspensions compared with commercial electric powered wheelchair (EPW) suspensions on non-American with Disabilities Act (ADA) compliant surfaces. The 2 dynamic suspensions used pneumatic actuators (PA) and electro-hydraulic with springs in series electrohydraulic and spring in series (EHAS). DesignWithin-subjects cross-sectional study. Driving performance and usability were evaluated using quantitative measures and standardized tools, respectively. SettingLaboratory settings that simulated common EPW outdoor driving tasks. Participants10 EPW users (5 women, 5 men) with an average age of 53.9±11.5 years and 21.2±16.3 years of EPW driving experience (N=10). InterventionNot applicable. Main Outcome Measure(s)Seat angle peaks (stability), number of completed trials (effectiveness), Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST), and systemic usability scale (SUS). ResultsMEBot with dynamic suspensions demonstrated significantly better stability (all P<.001) than EPW passive suspensions on non-ADA-compliant surfaces by reducing seat angle changes (safety). Also, MEBot with EHAS suspension significantly completed more trials over potholes compared with MEBot with PA suspension (P<.001) and EPW suspensions (P<.001). MEBot with EHAS had significantly better scores in terms of ease of adjustment (P=.016), durability (P=.031), and usability (P=.032) compared with MEBot with PA suspension on all surfaces. Physical assistance was required to navigate over potholes using MEBot with PA suspension and EPW suspensions. Also, participants reported similar responses regarding ease of use and satisfaction toward MEBot with EHAS suspension and EPW suspensions. ConclusionsMEBot with dynamic suspensions improve safety and stability when navigating non-ADA-compliant surfaces compared with commercial EPW passive suspensions. Findings indicate MEBot readiness for further evaluation in real-world environments.

Participatory Action Design and Engineering of Powered Personal Transfer System for Wheelchair Users: Initial Design and Assessment.

Caregivers that assist with wheelchair transfers are susceptible to back pain and occupational injuries. The study describes a prototype of the powered personal transfer system (PPTS) consisting of a novel powered hospital bed and a customized Medicare Group 2 electric powered wheelchair (EPW) working together to provide a no-lift solution for transfers. The study follows a participatory action design and engineering (PADE) process and describes the design, kinematics, and control system of the PPTS and end-users' perception to provide qualitative guidance and feedback about the PPTS. Thirty-six participants (wheelchair users (n = 18) and caregivers (n = 18)) included in the focus groups reported an overall positive impression of the system. Caregivers reported that the PPTS would reduce the risk of injuries and make transfers easier. Feedback revealed limitations and unmet needs of mobility device users, including a lack of power seat functions in the Group-2 wheelchair, a need for no-caregiver assistance/capability for independent transfers, and a need for a more ergonomic touchscreen. These limitations may be mitigated with design modifications in future prototypes. The PPTS is a promising robotic transfer system that may aid in the higher independence of powered wheelchair users and provide a safer solution for transfers.

The effect of differences in powered wheelchair joystick shape on subjective and objective operability

Various-shaped joysticks steer electric-powered wheelchairs (EPWs); however, an operability evaluation has not been fully conducted. This study evaluated the subjective and objective operability of various-shaped joysticks in 22 younger and 22 older adults. Participants operated an EPW on an experimental course using nine different-shaped joysticks, before ranking each joystick by their operability (1 = best, 9 = worst) as a primary outcome. Movement time (MT) and driving accuracy (DA) were also measured. Despite no significant differences in the primary outcome between joysticks, the I-shaped joystick with rounded tips (neutral grip) was ranked higher than the others. MT did not differ between joysticks, but DA was higher for the thin-columnar I-shaped joystick (pinch grip) than for the U- and T-shaped joysticks (pronated grip). MT and DA scores for young adults were significantly better than those for older adults. Further studies should be conducted to clarify possible factors related to EPW operability.

IoT-Based Discomfort Monitoring and a Precise Point Positioning Technique System for Smart Wheelchairs

The Internet is becoming increasingly important in our daily lives, allowing people to exchange and receive a wide variety of data. It can be utilized in a variety of ways for maximum benefit. For example, the concept of the Internet of Things (IoT) suggests that objects can be linked to the Internet. Based on this concept, in this paper, we describe the creation of modern smart-wheelchair accessories. These make the wheelchair simple to use, suitable for the elderly, and foldable. A health monitoring accessory is one of the critical functions. The Internet of Things is central to the concept of an electric-powered smart wheelchair. Residential communication networks connect electrical appliances and services, enable monitoring, and provide access from which to control various devices. The controls of a smart wheelchair comprise three essential components: a smart device that connects to the wheelchair, an Internet network, and a microcontroller. The results of our tests enable remote operation of the electric-powered wheelchair; command and control are excellent. Most significantly, our method provides consumers with an extra stage of security.

Optimal selection of an electric power wheelchair using an integrated COPRAS and EDAS approach based on Entropy weighting technique

The decision to purchase the best available electric power wheelchair (EPWC) for a person with a disability in a low-resource context is very stressful, whether it is based on financial circumstances or the availability of medical solutions. The study's objective is to assess the EPWC options available on the market, focused on a set of conflicting criteria. In this research, three multi-criteria decision-making (MCDM) approaches are used to make decisions. ENTROPY method for weightage calculation of various parameters, COPRAS and EDAS methods for evaluating and ranking alternatives are applied. Both COPRAS and EDAS are applied separately for ranking of selected wheelchair models, and to check the robustness of the applied method, sensitivity analysis on cost criterion is carried out. The result shows that for both methods, EPWC-1 is the top priority model to buy, whereas EPWC-7 is the worst model for COPRAS, and EPWC-10 is the worst model for EDAS among the ten alternatives.

Object Detection, Localization and Tracking-Based Deep Learning for Smart Wheelchair

In this article, we present our work regarding the development of advanced driver-assistance systems for an electric-powered wheelchair. Our project aims at improving the autonomy of people with reduced mobility. After conducting a clinical study, we identified several use-cases. In this paper, we introduce the detection, localization and tracking of points of interest in the immediate surroundings of the chair in an indoor environment, i.e.: doors, handles, light switches, etc. The aim is not only to improve perception around the chair but also to enable semi-autonomous driving towards these targets. First, we introduce a repurposing of YOLOv3, the object detection algorithm, to our use case. Then, we show our use of the Intel Realsense camera for depth estimation. Finally, we describe our adaptation of the SORT algorithm to track 3D interest points. To validate our approach, we realized several experiments in a controlled indoor environment. The detection, distance estimation, and tracking pipeline is tested using our custom dataset. This includes corridors, doors, handles, and switches. One of the scenarios studied to validate the proposed platform includes not only the detection and tracking of objects but also the movement of the wheelchair towards one of these points of interest.

Preliminary assessment of a multimodal electric-powered wheelchair simulator for training of activities of daily living

Preliminary assessment of a multimodal electric-powered wheelchair simulator for training of activities of daily living

A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020.

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

Comparative Study Between Integrator Backstepping and Fuzzy Logic Control Applied to an Electric Powered Wheelchair

The aim of this paper is the control of electric powered wheelchairs (EPW) which was made for people suffering of temporary or permanent disabilities due to illnesses or accidents. The EPW is powered by two Permanent Magnet Synchronous Motors (PMSM) that are characterized by high efficiency, high torque, low noise and robustness; hence the dynamic model of the both EPW-motors is presented in the first. After that, a comparative study is made between two nonlinear command theory; Integrator Backstepping based on the second method of Lyapunov which combine the choice of the energy function with the laws control, and, fuzzy logic introduced to approach human reasoning with the help of an adequate representation of knowledge. To evaluate the performance of the two controls, numerical simulations are presented to show the evolution of electrical and mechanical quantities, the energy consumed and the squared error of the displacement and velocity. However, the reference trajectory used is that generated by the fifth-degree polynomial interpolation, which ensures a regular trajectory that is continuous in positions, velocities and accelerations.

Usability evaluation of an electric-powered wheelchair driven by eye tracking

Usability evaluation of an electric-powered wheelchair driven by eye tracking