Objective.Assistive robots can be developed to restore or provide more autonomy for individuals with motor impairments. In particular, power wheelchairs can compensate lower-limb impairments, while robotic manipulators can compensate upper-limbs impairments. Recent studies have shown that Brain-Computer Interfaces (BCI) can be used to operate this type of devices. However, activities of daily living and long-term use in real-life contexts such as home require robustness and adaptability to complex, changing and cluttered environments which can be problematic given the neural signals that do not always allow a safe and efficient use. This article describes assist-as-needed sensor-based shared control (SC) methods relying on the blending of BCI and depth-sensor-based control.Approach.The proposed assistance targets the BCI-teleoperation of effectors for tasks that answer mobility and manipulation needs in a at-home context. The assistance provided by the proposed methods was evaluated through a wheelchair mobility and reach-and-grasp laboratory-based experiments in a controlled environment, as part of a clinical trial with a quadriplegic patient implanted with a wireless 64-channel ElectroCorticoGram recording implant named WIMAGINE.Main results.Results showed that the proposed methods can assist BCI users in both tasks. Indeed, the time to perform the tasks and the number of changes of mental tasks were reduced. Moreover, unwanted actions, such as wheelchair collisions with the environment, and gripper opening that could result in the fall of the object were avoided.Significance.The proposed methods are steps toward at-home use of BCI-teleoperated assistive robots. Indeed, the proposed SC methods improved the performance of the two assistive devices.Clinical trial, registration number: NCT02550522.

Power wheelchairs (PWCs) significantly enhance mobility for individuals with disabilities but are often challenging to master, requiring extensive training. Traditional training methods can be risky, resource-intensive, and difficult to implement. Virtual reality (VR) offers a safer, customizable, and effective alternative, as demonstrated in rehabilitation contexts. We developed a multisensory VR simulator incorporating vestibular feedback to enhance the sense of presence and mitigate cybersickness. Our studies show effective skill transfer from the virtual environment to real-world PWC use, validated with actual users in clinical trials. This demonstration highlights the capabilities of our mechanical simulator, featuring navigation scenes from previous trials and ongoing work with virtual agents. The simulator’s immersive and adaptive design addresses the challenges of PWC training, offering a practical and innovative solution for clinicians and users alike.

Abstract Objective The objective of this study was to evaluate users’ driving performances with a Power Wheelchair (PWC) driving simulator in comparison to the same driving task in real conditions with a standard power wheelchair. Methods Three driving circuits of progressive difficulty levels (C1, C2, C3) that were elaborated to assess the driving performances with PWC in indoor situations, were used in this study. These circuits have been modeled in a 3D Virtual Environment to replicate the three driving task scenarios in Virtual Reality (VR). Users were asked to complete the three circuits with respect to two testing conditions during three successive sessions, i.e. in VR and on a real circuit (R). During each session, users completed the two conditions. Driving performances were evaluated using the number of collisions and time to complete the circuit. In addition, driving ability by Wheelchair Skill Test (WST) and mental load were assessed in both conditions. Cybersickness, user satisfaction and sense of presence were measured in VR. The conditions R and VR were randomized. Results Thirty-one participants with neurological disorders and expert wheelchair drivers were included in the study. The driving performances between VR and R conditions were statistically different for the C3 circuit but were not statistically different for the two easiest circuits C1 and C2. The results of the WST was not statistically different in C1, C2 and C3. The mental load was higher in VR than in R condition. The general sense of presence was reported as acceptable (mean value of 4.6 out of 6) for all the participants, and the cybersickness was reported as acceptable (SSQ mean value of 4.25 on the three circuits in VR condition). Conclusion Driving performances were statistically different in the most complicated circuit C3 with an increased number of collisions in VR, but were not statistically different for the two easiest circuits C1 and C2 in R and VR conditions. In addition, there were no significant adverse effects such as cybersickness. The results show the value of the simulator for driving training applications. Still, the mental load was higher in VR than in R condition, thus mitigating the potential for use with people with cognitive disorders. Further studies should be conducted to assess the quality of skill transfer for novice drivers from the simulator to the real world. Trial registration Ethical approval n$$^\circ$$ ∘ 2019-A001306-51 from Comité de Protection des Personnes Sud Mediterranée IV. Trial registered the 19/11/2019 on ClinicalTrials.gov in ID: NCT04171973.

This paper evaluates the haptic perception of directional cues conveyed through one or two handles mounted on a walker, with the objective of devising haptic rendering techniques for aiding people with diverse mobility, sensory, and cognitive impairments. We designed a haptic handle composed of a cylindrical soft plastic casing, which houses five custom voice-coil actuators distributed around the handle. We carried out a human subject study enrolling 14 participants to investigate the impact of using uni-manual or bi-manual conditions and to identify the most effective tactile patterns in a navigation assistance scenario. We tested the use of either vibration bursts or pressure "taps" to convey different directions of motion, relying on the concept of the apparent haptic motion illusion. Results show that the proposed technique is an effective approach for providing navigational cues. We identified specific patterns that were highly effective both in uni or bi-manual conditions in conveying directional instructions towards the front (93.7%), the back (90.5%), the left (97.2%), and the right (84.5%) directions, highlighting the viability of both strategies and their adaptability to various single or dual-handle mobility devices. No significant difference was found between providing vibratory or tapping signals.

This article describes the robotic assistive technologies developed for users of electrically powered wheelchairs, within the framework of the European Union’s Interreg ADAPT (Assistive Devices for Empowering Disabled People Through Robotic Technologies) project. In particular, special attention is devoted to the integration of advanced sensing modalities and the design of new shared control algorithms. In response to the clinical needs identified by our medical partners, two novel smart wheelchairs with complementary capabilities and a virtual reality (VR)-based wheelchair simulator have been developed. These systems have been validated via extensive experimental campaigns in France and the United Kingdom.

This paper presents a new vision-based navigation assistant for power wheelchairs, called SpheriCol. Inspired by the parking assist system in cars, an omnidirectional image captured by a twin-fisheye camera is overlaid with colored distance markers from range sensors mounted on the wheelchair, to generate an augmented view of the surrounding environment. Such an image is displayed in real time to the user on a screen. To evaluate the effectiveness of the proposed system, able-bodied subjects and older adults with motor impairments have been asked to drive a consumer-grade power wheelchair equipped with SpheriCol, via a standard joystick. Our clinical trials with different obstacle courses, consistently indicate that SpheriCol is effective in improving safety and comfort, and in supporting a driver's decision during challenging but prevalent maneuvers, such as reversing out of an elevator, corridor centering, and turning on the spot.

This paper presents a generic power wheelchair dynamic model. As a first contribution, this paper proposes to use a generic model composed of a geometric model and a lumped model in order to be compliant with a wide range of existing commercially available wheelchairs. In this model, a set of essential parameters are enough to accurately replicate the dynamic behavior of a wheelchair. As a second contribution, this paper presents an identification method of a n-wheel type power wheelchair. The presented model is restricted to the sagittal plane only, which is sufficient to study the reliability of the identification and validation methods. Moreover, a Motion Cueing Algorithm based on the proposed model controls a simulator mechanical platform. The generic model has been then validated through a user study with 18 able-bodied participants evaluating the self-motion perception with our multisensory power wheelchair driving simulator. Results show that the simplified model is sufficient to provide accurate sensations to the user with respect to their experience while driving a power wheelchair.

PURPOSE In France, tens of thousands of people use a wheelchair. Driving powered wheelchairs (PWCs) present risks for users and their families. The risk of collision in PWC driver increases with severity of disability and may reduce their independence to drive. The European ADAPT project has developed a robotic assistance add-on for PWCs to prevent collisions and improve their driving performance. MATERIALS AND METHODS The aim of the SWADAPT2 study is to assess the benefit of this robotic assistance add-on arranged on a Standard Quickie Salsa M2 PWC in a population of PWC drivers with neurological disorders and driving difficulties. Eighteen (18) participants tested the system on three circuits of increasing difficulty, with and without the robotic assistance add-on. RESULTS The benefit of the robotic assistance add-on was important especially on the more difficult circuits without impacting cognitive load or driving speed. The number of collisions was significantly reduced when using robotic assistance add-on from 2.16 to 0.36 on circuit 2 (p = 0.009) and from 7.3 to 1.33 on circuit 3 (p = 0.0009). Task load demand was not increased with the assistance. CONCLUSION Finally, this system seems to be indicated to assist and improve driving safety for PWC drivers in driving difficulty. Evaluation was performed in controlled environments; therefore, further evaluation in real-world scenarios is needed to reach technology readiness.

Feedback solutions are a privileged form of assistance in order to increase mobility and independence of people with both motor and visual impairments. Indeed, it empowers the ability of the person to make decisions and take actions based on the provided information. Moreover, it maintains the use of the walker, and thus the residual locomotor skills. We here propose the SWALKIT, an open-source, cost-efficient, lightweight, easy to install and generic augmented walker kit. The SWALKIT can be equipped on any walker without requiring modifications of the structure or advanced technical knowledge. Vibrotactile feedback is provided through the handles to indicate the proximity of obstacles on the way of the user. The open source project is reproducible thanks to the online repository https://github.com/IH2A/Swalkit. In this paper, we present the design of the SWALKIT based on a user-centered approach following target users and therapists guidelines. Then, we present a technical validation study performed with 14 able-bodied blindfolded participants on a cardboard circuit. They were asked to use a standard walker with and without activation of the SWALKIT system. Results of this pilot study showed the efficiency and reliability of the proposed solution. Finally, we provide feedback after 2 months of daily life use by a target user.

In this paper, we consider a multi-sensor arrangement of proximity sensors that forms a proximity array. A general modeling methodology is considered within the framework of Sensor-based Control. It incorporates multiple sensor signals from the proximity array by giving primary emphasis on the interaction screw. To prove its effectiveness, modeling approach is applied to the task of plane-to-plane positioning. We discuss the development of two sensor-based task functions for the specific task considered. The validity of the methodology is provided using relevant experimental results.

Power wheelchairs are one of the main solutions for people with reduced mobility to maintain or regain autonomy and a comfortable and fulfilling life. However, driving a power wheelchair in a safe way is a difficult task that often requires training methods based on real-life situations. Although these methods are widely used in occupational therapy, they are often too complex to implement and unsuitable for some people with major difficulties. In this context, we collaborated with clinicians to develop a Virtual Reality based power wheelchair simulator. This simulator is an innovative training tool adapted to any type of situations and impairments. In this paper, we present a clinical study in which 29 power wheelchair regular users were asked to complete a clinically validated task designed by clinicians within two conditions: driving in a virtual environment with our simulator and driving in real conditions with a real power wheelchair. The objective of this study is to compare performances between the two conditions and to evaluate the Quality of Experience provided by our simulator in terms of Sense of Presence and Cybersickness. Results show that participants complete the tasks in a similar amount of time for both real and virtual conditions, using respectively a real power wheelchair and our simulator. Results also show that our simulator provides a high level of Sense of Presence and provokes only slight to moderate Cybersickness discomforts resulting in a valuable Quality of Experience.

Objectives The objective of this study is to highlight the effect of a robotic driver assistance module of powered wheelchair (PWC), using infrared sensors and accessorizing a commercial wheelchair) on the reduction of the number of collisions in standardized circuit in a population with neurological disorders by comparing driving performance with and without assistance. Methods This is a prospective, single-center, controlled, repeated measure design, single-blind pilot study including patients with neurological disabilities who are usual drivers of electric wheelchairs. The main criterion for evaluating the device is the number of collisions with and without the assistance of a prototype anti-collision system on three circuits of increasing complexity. Travel times, cognitive load, driving performance, and user satisfaction are also analyzed. Results 23 Patients, 11 women and 12 men with a mean age of 48 years old completed the study. There was a statistically significant reduction in the number of collisions on the most complex circuit: 61% experienced collisions without assistance versus 39% with assistance (p = 0.038). Conclusion This study concludes that the PWC driving assistance module is efficient in terms of safety without reducing the speed of movement in a population of people with disabilities who are habitual wheelchair drivers. The prospects are therefore to conduct tests on a target population with driving failure or difficulty who could benefit from this device so as to allow them to travel independently and safely.

Objectives: The objective of this study is to highlight the interest of a robotic driver assistance module of Powered Wheelchair (PWC), using infrared sensors and accessorizing a commercial wheelchair, on the reduction of the number of collisions in circuit standardized, in a population with neurological disorders using an electric wheelchair, by comparing driving performance with and without assistance. Methods: This is a prospective, single-center, controlled, randomized, single-blind pilot study including patients with neurological disabilities who are usual drivers of electric wheelchairs. The main criterion for evaluating the device is the number of collisions without and with the assistance of a prototype anti-collision system on 3 circuits of increasing complexity. Travel times, cognitive load, driving performance and user satisfaction are also analyzed. Results: 23 patients completed the study. There is a statistically significant reduction in the number of collisions on the most complex circuit. Conclusions: this study therefore concludes that the PWC driving assistance module is efficient in terms of safety without reducing the speed of movement in a population of people with disabilities who are habitual wheelchair drivers. The prospects are therefore to conduct tests on the target population with driving failure or difficulty who could benefit from this device in order to allow them to travel independently in safety.

Pour une personne en situation de handicap, utilisatrice d'un fauteuil roulant electrique, disposer d'un outil de prediction de la faisabilite d'effectuer un trajet de A a B compte-tenu de la charge batterie disponible, represente un interet majeur. Ce point est si sensible que certains utilisateurs de fauteuils roulants limitent leurs deplacements de peur de tomber en panne et de ne pas pouvoir rentrer chez eux. Ce document s'appuie sur une modelisation energetique du fauteuil roulant electrique afin de fournir a l'utilisateur un outil de prediction energetique pour l'aider a evaluer la possibilite d'effectuer un trajet aller-retour. Cette etude propose une modelisation parametrique des coefficients lies aux differentes energies consommees. Celle-ci est appliquee sur un fauteuil roulant electrique 4 roues puis est comparee aux parametres obtenus pour un fauteuil roulant electrique 6 roues. Cette modelisation energetique est finalement evaluee sur un trajet en exterieur.

Autonomy and social inclusion can reveal themselves everyday challenges for people experiencing mobility impairments. These people can benefit from technical aids such as power wheelchairs to access mobility and overcome social exclusion. However, power wheelchair driving is a challenging task which requires good visual, cognitive and visuo-spatial abilities. Besides, a power wheelchair can cause material damage or represent a danger of injury for others or oneself if not operated safely. Therefore, training and repeated practice are mandatory to acquire safe driving skills to obtain power wheelchair prescription from therapists. However, conventional training programs may reveal themselves insufficient for some people with severe impairments. In this context, Virtual Reality offers the opportunity to design innovative learning and training programs while providing realistic wheelchair driving experience within a virtual environment. In line with this, we propose a user-centered design of a multisensory power wheelchair simulator. This simulator addresses classical virtual experience drawbacks such as cybersickness and sense of presence by combining 3D visual rendering, haptic feedback and motion cues. It relies on a modular and versatile workflow enabling not only easy interfacing with any virtual display, but also with any user interface such as wheelchair controllers or feedback devices. This paper presents the design of the first implementation as well as its first commissioning through pretests. The first setup achieves consistent and realistic behavior.

Power wheelchairs allow people with motor disabilities to have more mobility and independence. However, driving safely such a vehicle is a daily challenge particularly in urban environments while navigating on sidewalks, negotiating curbs or dealing with uneven grounds. Indeed, differences of elevation have been reported to be one of the most challenging environmental barrier to negotiate, with tipping and falling being the most common accidents power wheelchair users encounter. It is thus our challenge to design assistive solutions for power wheelchair navigation in order to improve safety while navigating in such environments. To this aim, we propose a shared-control algorithm which provides assistance while navigating with a wheelchair in an environment consisting of negative obstacles. We designed a dedicated sensor-based control law allowing trajectory correction while approaching negative obstacles e.g. steps, curbs, descending slopes. This shared control proposed method takes into account the humanin-the loop factor. In this study, our solution the ability of our system to ensure a safe trajectory while navigating on a sidewalk is demonstrated through simulation, thus providing a proof-of-concept of our method.

The use of a power wheelchair allows to maintain mobility by providing better access to daily activities and thus positive impact on the quality of life. However, driving a power wheelchair is a complex task, particularly within an environment consisting of negative obstacles (e.g. steps, sidewalk edges). In this context, falling accidents can occur while driving a power wheelchair on a sidewalk. Therefore, driving assistance is required to prevent from falling off a curb edge. In order to meet these expectations, we here propose a semi-autonomous shared control framework assisting the user while driving on a sidewalk. We present simulations as well as an experiment carried out with our system embedded on a standard wheelchair. In both cases, our method allows progressive velocity adaptation when approaching a curb edge resulting in the wheelchair avoiding the risk of falling. The obtained results thus provide a proof of concept of our method.

Smart powered wheelchairs can increase mobility and independence for people with disability by providing navigation support. This support can be supplied in the form of autonomous or semi-autonomous obstacle avoidance systems. However, for rehabilitation or learning purposes, it would be of great benefit for wheelchair users to have a better understanding of the surrounding environment while driving. Therefore, another way of providing navigation support is to communicate information through a dedicated and adapted feedback interface. We here propose a framework in which feedback is provided by sending forces through the wheelchair controller as the user steers the wheelchair. This solution is based on a low complex optimization framework able to perform smooth trajectory correction and to provide obstacle avoidance. The impact of the proposed haptic guidance solution on user driving performance was assessed during this pilot study for validation purposes through an experiment with 4 able-bodied participants. They were asked to drive a power wheelchair on an obstacle course with and without activation of the force feedback. Results of this pilot study showed that the number of collisions significantly decreased while force feedback was activated, thus validating the proposed framework.