Usability Evaluation of a Novel Robotic Power Wheelchair for Indoor and Outdoor Navigation

A study on the formative usability testing for modular powered wheelchair

The increasing prevalence of mobility impairments underscores the urgent need for accessible and affordable mobility aids. To overcome the mobility limitations of people with disabilities, there is an increasing need for the development of lightweight and portable powered wheelchairs that can be easily loaded. This study aimed to perform an early health technology assessment and a formative usability evaluation on a modular (detachable) powered wheelchair. It aimed to gauge device satisfaction among users, pinpoint areas for improvement, and detect any unforeseen errors to inform future development. Engaging 16 participants, including powered wheelchair users, healthcare professionals, and caregivers, the research evaluated the wheelchair's functionality in various scenarios, emphasizing safety, effectiveness, and convenience. Statistical analyses of task performance and satisfaction surveys highlighted that, while powered wheelchair users successfully completed tasks focusing on driving and power control, healthcare professionals and caregivers encountered difficulties with the wheelchair's assembly and disassembly. Despite general positivity, the surveys indicated mixed satisfaction levels regarding safety, validity, and convenience, with specific issues related to frame durability, seat comfort, and control mechanisms. These findings suggest that refining the wheelchair's design and addressing user concerns could significantly enhance satisfaction and mobility services. Future efforts will include a thorough review of an advanced prototype and further satisfaction assessments.

Effects of track-based stair climbing robot on muscle activity, usability, and psychological anxiety: a preliminary study

This study investigated the effects of using the LiftCar-150 track-based stair-climbing robot on muscle activity, usability, and psychological anxiety. While stair-climbing robots enhance mobility for individuals with physical disabilities, existing research has predominantly focused on engineering perspectives, with limited attention to user-centered outcomes. Ten healthy participants and an 80 kg dummy rider completed stair-climbing tasks at slow (5 m/min) and fast (7 m/min) speeds. Muscle activity in the middle trapezius (MT), erector spinae (ES), multifidus (MF), gluteus maximus (Gmax), gluteus medius (Gmed), and anterior deltoid (AD) muscles was recorded by electromyography. Usability was evaluated in terms of safety, efficiency, and satisfaction using a 5-point Likert scale, while psychological anxiety was assessed with a visual analog scale (VAS) ranging from 0 to 10. Results showed that during stair ascent, activities of the back extensors (ES and MF) and gluteus muscles (Gmax and Gmed) significantly increased compared to descent, while anterior deltoid activity was higher during descent. Usability scores averaged 4.05 for stability, 4.1 for efficiency, and 3.7 for satisfaction. Perceived psychological anxiety scores were 4.2 ± 0.3 and 5.4 ± 0.5 at slow speed, and 3.5 ± 0.2 and 5.7 ± 0.4 at fast speed during ascent and descent, respectively. While operators recognized the robot's stability and efficiency, satisfaction levels were neutral, and specific muscle activation was increased. These findings provide essential insights into optimizing the design and usability of stair-climbing robots to better address user needs.

Smart Nursing Wheelchairs: A New Trend in Assisted Care and the Future of Multifunctional Integration

As a significant technological innovation in the fields of medicine and geriatric care, smart care wheelchairs offer a novel approach to providing high-quality care services and improving the quality of care. The aim of this review article is to examine the development, applications and prospects of smart nursing wheelchairs, with particular emphasis on their assistive nursing functions, multiple-sensor fusion technology, and human-machine interaction interfaces. First, we describe the assistive functions of nursing wheelchairs, including position changing, transferring, bathing, and toileting, which significantly reduce the workload of nursing staff and improve the quality of care. Second, we summarized the existing multiple-sensor fusion technology for smart nursing wheelchairs, including LiDAR, RGB-D, ultrasonic sensors, etc. These technologies give wheelchairs autonomy and safety, better meeting patients' needs. We also discussed the human-machine interaction interfaces of intelligent care wheelchairs, such as voice recognition, touch screens, and remote controls. These interfaces allow users to operate and control the wheelchair more easily, improving usability and maneuverability. Finally, we emphasized the importance of multifunctional-integrated care wheelchairs that integrate assistive care, navigation, and human-machine interaction functions into a comprehensive care solution for users. We are looking forward to the future and assume that smart nursing wheelchairs will play an increasingly important role in medicine and geriatric care. By integrating advanced technologies such as enhanced artificial intelligence, intelligent sensors, and remote monitoring, we expect to further improve patients' quality of care and quality of life.

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

OBJECTIVE

To 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).

DESIGN

Within-subjects cross-sectional study. Driving performance and usability were evaluated using quantitative measures and standardized tools, respectively.

SETTING

Laboratory settings that simulated common EPW outdoor driving tasks.

PARTICIPANTS

10 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).

INTERVENTION

Not 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).

RESULTS

MEBot 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.

CONCLUSIONS

MEBot 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.

The Interface Usage Skills Test: An Open Source Tool for Quantitative Evaluation in Real Time for Clinicians and Researchers

Assistive machines endow people with limited mobility the opportunity to live more independently. However, operating these machines poses risks to the safety of the human operator as well as the surrounding environment. Thus, proper user training is an essential step towards independent control and use of functionally assistive machines. The human operator can use a variety of control interfaces to issue control signals to the device, depending on the residual mobility and level of injury of the human operator. Proficiency in operating the interface of choice precedes the skill in operating the assistive machine. In this systems paper, we present an open source tool for automatically and objectively quantifying user skill in operating various interface devices.

Mini-review: Robotic wheelchair taxonomy and readiness

Robotic wheelchair research and development is a growing sector. This article introduces a robotic wheelchair taxonomy, and a readiness model supported by a mini-review. The taxonomy is constructed by power wheelchair and, mobile robot standards, the ICF and, PHAATE models. The mini-review of 2797 articles spanning 7 databases produced 205 articles and 4 review articles that matched inclusion/exclusion criteria. The review and analysis illuminate how innovations in robotic wheelchair research progressed and have been slow to translate into the marketplace.

Analysis of Whole-Body Vibration Using Electric Powered Wheelchairs on Surface Transitions

Wheelchair users are exposed to whole-body vibration (WBV) when driving on sidewalks and in urban environments; however, there is limited literature on WBV exposure to power wheelchair users when driving during daily activities. Further, surface transitions (i.e., curb-ramps) provide wheelchair accessibility from street intersections to sidewalks; but these require a threshold for water drainage. This threshold may induce high WBV (i.e., root-mean-square and vibration-daily-value accelerations) when accessibility guidelines are not met. This study analyzed the WBV effects on power wheelchairs with passive suspension when driving over surfaces with different thresholds. Additionally, this study introduced a novel power wheelchair with active suspension to reduce WBV levels on surface transitions. Three trials were performed with a commercial power wheelchair with passive suspension, a novel power wheelchair with active suspension, and the novel power wheelchair without active suspension driving on surfaces with five different thresholds. Results show no WBV difference among EPWs across all surfaces. However, the vibration-dose-value increased with higher surface thresholds when using the passive suspension while the active suspension remained constant. Overall, the power wheelchair with active suspension offered similar WBV effects as the passive suspension. While significant vibration-dose-value differences were observed between surface thresholds, all EPWs maintained WBV values below the ISO 2631-1 health caution zone.

Curb Negotiation With Dynamic Human-Robotic Wheelchair Collaboration

Wheelchair users often face architectural barriers such as curbs, limiting their accessibility, mobility, and participation in their communities. The mobility enhancement robotic (MEBot) wheelchair was developed to navigate over such architectural barriers. Its application allows wheelchair users to negotiate curbs automatically while the user remains in control. The application was optimized from a manual to a semiautomated process based on wheelchair users' feedback. The optimized application was evaluated by experienced wheelchair users who navigated over curbs of different heights. Participants evaluated MEBot in terms of effectiveness, workload demand, and usability. Ten participants successfully ascended and descended curbs of different heights at an average completion time of 55.7 ± 19.5 and 30.3 ± 9.1 s, respectively. MEBot maintained stability during the process, while participants reported low levels of effort, frustration, and overall cognitive demand to operate MEBot. Furthermore, participants were satisfied with the ease of learning and using the MEBot curb negotiation application to overcome the curbs but suggested less wheel adjustment for comfort and a faster pace to overcome curbs during real-world conditions.

Automated Curb Recognition and Negotiation for Robotic Wheelchairs

Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs. Users with physical and/or sensory impairments may find it challenging to negotiate such barriers. Hence, a Curb Recognition and Negotiation (CRN) system was developed to increase user's speed and safety when negotiating a curb. This article describes the CRN system which combines an existing curb negotiation application of a mobility enhancement robot (MEBot) and a plane extraction algorithm called Polylidar3D to recognize curb characteristics and automatically approach and negotiate curbs. The accuracy and reliability of the CRN system were evaluated to detect an engineered curb with known height and 15 starting positions in controlled conditions. The CRN system successfully recognized curbs at 14 out of 15 starting positions and correctly determined the height and distance for the MEBot to travel towards the curb. While the MEBot curb alignment was 1.5 ± 4.4°, the curb ascending was executed safely. The findings provide support for the implementation of a robotic wheelchair to increase speed and reduce human error when negotiating curbs and improve accessibility.

Usability Studies of an Egocentric Vision-Based Robotic Wheelchair

Motivated by the need to improve the quality of life for the elderly and disabled individuals who rely on wheelchairs for mobility, and who may have limited or no hand functionality at all, we propose an egocentric computer vision based co-robot wheelchair to enhance their mobility without hand usage. The robot is built using a commercially available powered wheelchair modified to be controlled by head motion. Head motion is measured by tracking an egocentric camera mounted on the user’s head and faces outward. Compared with previous approaches to hands-free mobility, our system provides a more natural human robot interface because it enables the user to control the speed and direction of motion in a continuous fashion, as opposed to providing a small number of discrete commands. This article presents three usability studies, which were conducted on 37 subjects. The first two usability studies focus on comparing the proposed control method with existing solutions while the third study was conducted to assess the effectiveness of training subjects to operate the wheelchair over several sessions. A limitation of our studies is that they have been conducted with healthy participants. Our findings, however, pave the way for further studies with subjects with disabilities.

Usability evaluation of attitude control for a robotic wheelchair for tip mitigation in outdoor environments

Tips and falls are the most prominent causes of wheelchair accidents that occur when driving on uneven terrains and less accessible environments. The Mobility Enhancement Robotic Wheelchair (MEBot) was designed to improve the stability of Electric Powered Wheelchairs (EPW) when driving over these environments. MEBot offers six independently height-adjustable wheels to control attitude of its seat over uneven and angled terrains. Its attitude control application uses an inertial measurement unit to detect seat angles changes to adjust each wheel-height accordingly. MEBot was compared to commercial EPWs in terms of EPW performance (seat angle changes and response time) and participant perception (satisfaction and task-load demand) towards each device. Ten participants drove their own EPW and MEBot for five trials each through driving tasks that replicated outdoor environments. Results showed less change in the pitch angle when driving up and down a 10° slope using MEBot (5.6 ± 1.6°, 6.6 ± 0.5°) compared to the participants' own EPW (14.6 ± 2.6°, 12.1 ± 2.6°). However, MEBot required 7.8 ± 3.0 s to self-adjust to the minimum angle when driving over the tasks. Participants reported no difference in satisfaction and task load demand between EPWs due to similarities in comfort and ease-of-use. Improving the speed and efficiency of MEBot's attitude control application will be addressed in future work based upon participants' feedback.

Improving wheelchair route planning through instrumentation and navigation systems

Route planning is an important tool to reach points of interest. The current technology offers options for public transportation and pedestrians on the road and sidewalks, respectively. However, for people who use electric powered wheelchairs (EPW) as their primary means of mobility, the level of accessibility and EPW battery consumption are important during route planning. This paper introduces the concept of an accessible route navigation application to reduce EPW battery consumption. The application, called eNav, uses five layers of information including OpenStreetMaps (OSM), airborne laser scanner (ALS), Point-of-Interests (POIs), public transportation, and crowdsourcing. eNav collects these layers of information to provide the shortest, most accessible, and most comfortable routes that consume the least amount of EPW battery. Additionally, the paper presents the Mobility Enhancement roBot (MEBot), a legged-wheeled power wheelchair, to drive over architectural barriers and less accessible environments. The paper proposes the use of MEBot as a sixth layer of information to inform eNav and road authorities about sidewalk/route conditions, to improve road accessibility, and to provide an energy efficient route planning for non-MEBot users.

A Heuristic Approach to Overcome Architectural Barriers Using a Robotic Wheelchair

The Mobility Enhancement roBotic (MEBot) wheelchair was developed to improve the safety and accessibility of wheelchair users when facing architectural barriers. MEBot uses pneumatic actuators attached to its frame and six wheels to provide curb ascending/descending for heights up to 20.3 cm. To improve MEBot's application, this study used a heuristic approach with power wheelchair users to evaluate and improve the MEBot application at different curb heights. Wheelchair users were trained on MEBot's features to operate its curb ascending/descending application. Three trials were carried out with wheelchair users ascending and descending three curbs of different height. Quantitative variables were analyzed to improve the sequential steps to ascend/descend curbs. Additionally, the application's effectiveness and efficiency were measured by the number of completed tasks, change in seat angle, and task completion time. Results showed that participants completed each trial and applied alternative strategies to traverse different curb heights. Furthermore, results suggested the combination and/or re-arrangement of steps to reduce task completion time. MEBot demonstrated its effectiveness to ascend/descend different curb heights with a heterogeneous participant sample. Future work will incorporate participant's most efficient strategies to improve the ascending/ascending process and the efficiency of the MEBot application.