A prototype power assist wheelchair that provides for obstacle detection and avoidance for those with visual impairments

SWADAPT2: benefits of a collision avoidance assistance for powered wheelchair users in driving difficulty

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.

An autonomous wheelchair with health monitoring system based on Internet of Thing

Assistive powered wheelchairs will bring patients and elderly the ability of remain mobile without the direct intervention from caregivers. Vital signs from users can be collected and analyzed remotely to allow better disease prevention and proactive management of health and chronic conditions. This research proposes an autonomous wheelchair prototype system integrated with biophysical sensors based on Internet of Thing (IoT). A powered wheelchair system was developed with three biophysical sensors to collect, transmit and analysis users' four vital signs to provide real-time feedback to users and clinicians. A user interface software embedded with the cloud artificial intelligence (AI) algorithms was developed for the data visualization and analysis. An improved data compression algorithm Minimalist, Adaptive and Streaming R-bit (O-MAS-R) was proposed to achieve a higher compression ratio with minimum 7.1%, maximum 45.25% compared with MAS algorithm during the data transmission. At the same time, the prototype wheelchair, accompanied with a smart-chair app, assimilates data from the onboard sensors and characteristics features within the surroundings in real-time to achieve the functions including obstruct laser scanning, autonomous localization, and point-to-point route planning and moving within a predefined area. In conclusion, the wheelchair prototype uses AI algorithms and navigation technology to help patients and elderly maintain their independent mobility and monitor their healthcare information in real-time.

SWADAPT1: assessment of an electric wheelchair-driving robotic module in standardized circuits: a prospective, controlled repeated measure design pilot study

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.

Shared control methodology based on head positioning and vector fields for people with quadriplegia

Mobile robotic systems are used in a wide range of applications. Especially in the assistive field, they can enhance the mobility of the elderly and disable people. Modern robotic technologies have been implemented in wheelchairs to give them intelligence. Thus, by equipping wheelchairs with intelligent algorithms, controllers, and sensors, it is possible to share the wheelchair control between the user and the autonomous system. The present research proposes a methodology for intelligent wheelchairs based on head movements and vector fields. In this work, the user indicates where to go, and the system performs obstacle avoidance and planning. The focus is developing an assistive technology for people with quadriplegia that presents partial movements, such as the shoulder and neck musculature. The developed system uses shared control of velocity. It employs a depth camera to recognize obstacles in the environment and an inertial measurement unit (IMU) sensor to recognize the desired movement pattern measuring the user’s head inclination. The proposed methodology computes a repulsive vector field and works to increase maneuverability and safety. Thus, global localization and mapping are unnecessary. The results were evaluated by simulated models and practical tests using a Pioneer-P3DX differential robot to show the system’s applicability.

Shared Control of an Electric Wheelchair Considering Physical Functions and Driving Motivation

Individuals with severe physical impairments have difficulties operating electric wheelchairs (EWs), especially in situations where fine steering abilities are required. Automatic driving partly solves the problem, although excessive reliance on automatic driving is not conducive to maintaining their residual physical functions and may cause more serious diseases in the future. The objective of this study was to develop a shared control system that can be adapted to different environments by completely utilizing the operating ability of the user while maintaining the motivation of the user to drive. The operating characteristics of individuals with severe physical impairments were first analyzed to understand their difficulties when operating EWs. Subsequently, a novel reinforcement learning-based shared control method was proposed to adjust the control weight between the user and the machine to meet the requirements of fully exploiting the operating abilities of the users while assisting them when necessary. Experimental results showed that the proposed shared control system gradually adjusted the control weights between the user and the machine, providing safe operation of the EW while ensuring full use of the control signals from the user. It was also found that the shared control results were deeply affected by the types of users.

User-centered design of a depth data based obstacle detection and avoidance system for the visually impaired

The development of a novel depth-data based real-time obstacle detection and avoidance application for visually impaired (VI) individuals to assist them in navigating independently in indoors environments is presented in this paper. The application utilizes a mainstream, computationally efficient mobile device as the development platform in order to create a solution which not only is aesthetically appealing, cost-effective, lightweight and portable but also provides real-time performance and freedom from network connectivity constraints. To alleviate usability problems, a user-centered design approach has been adopted wherein semi-structured interviews with VI individuals in the local context were conducted to understand their micro-navigation practices, challenges and needs. The invaluable insights gained from these interviews have not only informed the design of our system but would also benefit other researchers developing similar applications. The resulting system design along with a detailed description of its obstacle detection and unique multimodal feedback generation modules has been provided. We plan to iteratively develop and test the initial prototype of the system with the end users to resolve any usability issues and better adapt it to their needs.

Learning Shared Control by Demonstration for Personalized Wheelchair Assistance

An emerging research problem in assistive robotics is the design of methodologies that allow robots to provide personalized assistance to users. For this purpose, we present a method to learn shared control policies from demonstrations offered by a human assistant. We train a Gaussian process (GP) regression model to continuously regulate the level of assistance between the user and the robot, given the user's previous and current actions and the state of the environment. The assistance policy is learned after only a single human demonstration, i.e. in one-shot. Our technique is evaluated in a one-of-a-kind experimental study, where the machine-learned shared control policy is compared to human assistance. Our analyses show that our technique is successful in emulating human shared control, by matching the location and amount of offered assistance on different trajectories. We observed that the effort requirement of the users were comparable between human-robot and human-human settings. Under the learned policy, the jerkiness of the user's joystick movements dropped significantly, despite a significant increase in the jerkiness of the robot assistant's commands. In terms of performance, even though the robotic assistance increased task completion time, the average distance to obstacles stayed in similar ranges to human assistance.

A review of principles in design and usability testing of tactile technology for individuals with visual impairments

To lay the groundwork for devising, improving, and implementing new technologies to meet the needs of individuals with visual impairments, a systematic literature review was conducted to: a) describe hardware platforms used in assistive devices, b) identify their various applications, and c) summarize practices in user testing conducted with these devices. A search in relevant EBSCO databases for articles published between 1980 and 2014 with terminology related to visual impairment, technology, and tactile sensory adaptation yielded 62 articles that met the inclusion criteria for final review. It was found that while earlier hardware development focused on pin matrices, the emphasis then shifted toward force feedback haptics and accessible touch screens. The inclusion of interactive and multimodal features has become increasingly prevalent. The quantity and consistency of research on navigation, education, and computer accessibility suggest that these are pertinent areas of need for the visually impaired community. Methodologies for usability testing ranged from case studies to larger cross-sectional studies. Many studies used blindfolded sighted users to draw conclusions about design principles and usability. Altogether, the findings presented in this review provide insight on effective design strategies and user testing methodologies for future research on assistive technology for individuals with visual impairments.

Driving interface based on tactile sensors for electric wheelchairs or trolleys

This paper introduces a novel device based on a tactile interface to replace the attendant joystick in electric wheelchairs. It can also be used in other vehicles such as shopping trolleys. Its use allows intuitive driving that requires little or no training, so its usability is high. This is achieved by a tactile sensor located on the handlebar of the chair or trolley and the processing of the information provided by it. When the user interacts with the handle of the chair or trolley, he or she exerts a pressure pattern that depends on the intention to accelerate, brake or turn to the left or right. The electronics within the device then perform the signal conditioning and processing of the information received, identifying the intention of the user on the basis of this pattern using an algorithm, and translating it into control signals for the control module of the wheelchair. These signals are equivalent to those provided by a joystick. This proposal aims to help disabled people and their attendees and prolong the personal autonomy in a context of aging populations.

Design and validation of an intelligent wheelchair towards a clinically-functional outcome

BACKGROUND

Many people with mobility impairments, who require the use of powered wheelchairs, have difficulty completing basic maneuvering tasks during their activities of daily living (ADL). In order to provide assistance to this population, robotic and intelligent system technologies have been used to design an intelligent powered wheelchair (IPW). This paper provides a comprehensive overview of the design and validation of the IPW.

METHODS

The main contributions of this work are three-fold. First, we present a software architecture for robot navigation and control in constrained spaces. Second, we describe a decision-theoretic approach for achieving robust speech-based control of the intelligent wheelchair. Third, we present an evaluation protocol motivated by a meaningful clinical outcome, in the form of the Robotic Wheelchair Skills Test (RWST). This allows us to perform a thorough characterization of the performance and safety of the system, involving 17 test subjects (8 non-PW users, 9 regular PW users), 32 complete RWST sessions, 25 total hours of testing, and 9 kilometers of total running distance.

RESULTS

User tests with the RWST show that the navigation architecture reduced collisions by more than 60% compared to other recent intelligent wheelchair platforms. On the tasks of the RWST, we measured an average decrease of 4% in performance score and 3% in safety score (not statistically significant), compared to the scores obtained with conventional driving model. This analysis was performed with regular users that had over 6 years of wheelchair driving experience, compared to approximately one half-hour of training with the autonomous mode.

CONCLUSIONS

The platform tested in these experiments is among the most experimentally validated robotic wheelchairs in realistic contexts. The results establish that proficient powered wheelchair users can achieve the same level of performance with the intelligent command mode, as with the conventional command mode.

A systematic review on the pros and cons of using a pushrim-activated power-assisted wheelchair

OBJECTIVE

To determine the (dis)advantages of transition to a power-assisted wheelchair, and derive the clinical implications for its use or prescription.

DATA SOURCES

Relevant articles published prior to May 2012 were identified using PubMed, Cochrane Library, REHABDATA, CIRRIE and CINAHL databases.

REVIEW METHODS

Clinical or (randomized) controlled trials, published in a peer-reviewed journal, comparing power-assisted wheelchair use and hand-rim or powered wheelchair use were eligible. Data quality and validity were assessed by two reviewers independently using the Checklist for Measuring Quality developed by Downs and Black.

RESULTS

A systematic search yielded 15 cross-over trails with repeated measurement design and one qualitative interview. Methodological quality scored between 9 and 15 points out of the maximum score of 32. Ten studies measuring body function and structure reported reduced strain on the arm and cardiovascular system during power-assisted propulsion compared to hand-rim propulsion. Twelve studies measuring activities and social participation reported precision tasks easier to perform with a hand-rim wheelchair and tasks which require more torque were easier with a power-assisted wheelchair. Social participation was not altered significantly by the use of a hand-rim, powered or power-assisted wheelchair.

CONCLUSION

Power-assisted propulsion might be beneficial for subjects in whom independent hand-rim wheelchair propulsion is endangered by arm injury, insufficient arm strength or low cardiopulmonary reserves. Also, subjects who have difficulty propelling a wheelchair in a challenging environment can benefit from power-assisted wheelchair use. Caution is warranted for the additional width and weight in relation to the usual mode of transportation and access to the home environment.

A robotic wheelchair trainer: design overview and a feasibility study

Background

Experiencing independent mobility is important for children with a severe movement disability, but learning to drive a powered wheelchair can be labor intensive, requiring hand-over-hand assistance from a skilled therapist.

Methods

To improve accessibility to training, we developed a robotic wheelchair trainer that steers itself along a course marked by a line on the floor using computer vision, haptically guiding the driver's hand in appropriate steering motions using a force feedback joystick, as the driver tries to catch a mobile robot in a game of "robot tag". This paper provides a detailed design description of the computer vision and control system. In addition, we present data from a pilot study in which we used the chair to teach children without motor impairment aged 4-9 (n = 22) to drive the wheelchair in a single training session, in order to verify that the wheelchair could enable learning by the non-impaired motor system, and to establish normative values of learning rates.

Results and Discussion

Training with haptic guidance from the robotic wheelchair trainer improved the steering ability of children without motor impairment significantly more than training without guidance. We also report the results of a case study with one 8-year-old child with a severe motor impairment due to cerebral palsy, who replicated the single-session training protocol that the non-disabled children participated in. This child also improved steering ability after training with guidance from the joystick by an amount even greater than the children without motor impairment.

Conclusions

The system not only provided a safe, fun context for automating driver's training, but also enhanced motor learning by the non-impaired motor system, presumably by demonstrating through intuitive movement and force of the joystick itself exemplary control to follow the course. The case study indicates that a child with a motor system impaired by CP can also gain a short-term benefit from driver's training with haptic guidance.