Immersive participatory design of assistive robots to support older adults.

Assistive robots have the potential to support independence, enhance safety, and lower healthcare costs for older adults, as well as alleviate the demands of their care partners. However, ensuring that these robots will effectively and reliably address end-user needs in the long term requires user-specific design factors to be considered during the robot development process. To identify these design factors, we embedded Stretch, a mobile manipulator created by Hello Robot Inc., in the home of an older adult with motor impairments and his care partner for four weeks to support them with everyday activities. An occupational therapist and a robotics engineer lived with them during this period, employing an immersive participatory design approach to co-design and customise the robot with them. We highlight the benefits of this immersive participatory design experience and provide insights into robot design that can be applied broadly to other assistive technologies.

Fall detection from a manual wheelchair: preliminary findings based on accelerometers using machine learning techniques.

Automated fall detection devices for individuals who use wheelchairs to minimize the consequences of falls are lacking. This study aimed to develop and train a fall detection algorithm to differentiate falls from wheelchair mobility activities using machine learning techniques. Thirty, healthy, ambulatory, young adults simulated falls from a wheelchair and performed other wheelchair-related mobility activities in a laboratory. Neural Network classifiers were used to train the algorithm developed based on data retrieved from accelerometers mounted at the participant's wrist, chest, and head. Results indicate excellent accuracy to differentiate between falls and wheelchair mobility activities. The sensors mounted at the wrist, chest, and head presented with an accuracy of 100%, 96.9%, and 94.8%, respectively, using data from 258 falls and 220 wheelchair mobility activities. This pilot study indicates that a fall detection algorithm developed in a laboratory setting based on fall accelerometer patterns can accurately differentiate wheelchair-related falls and wheelchair mobility activities. This algorithm should be integrated into a wrist-worn devices and tested among individuals who use a wheelchair in the community.

Sensitivity of Apple Watch fall detection feature among wheelchair users.

A reliable fall detection device is crucial to minimize long-term consequences of falls among wheelchair users. This study examines the sensitivity of Apple Watch to detect intentional falls from a wheelchair. Twenty-five able bodied (age: 21.9 ± 2.5 years) participated in a protocol in which they intentionally fell out of a wheelchair in a laboratory setting. Each participant wore an Apple Watch Series 5 and performed 3 falls in the forward, right and left sideways, and backward directions onto a crash pad totaling 12 falls each. The Apple Watch was manually checked after each fall to determine if the device registered a fall. From 300 fall trials captured, the Apple Watch detected 14 falls showing a sensitivity of 4.7%, a false negative rate of 95.3%. Logistic regression showed that participant's height, impact force, lower limb functioning, and fall direction are parameters that may influence the ability of the Apple Watch to detect falls from a wheelchair. The Apple Watch fall detection feature presented with a very poor sensitivity to detect intentional falls from a wheelchair among able bodied young adults. Due to the high incidence and consequences of falls, a reliable fall detection device specific for wheelchair users is warranted.

The feasibility of an automatic prompting system in assisting people with traumatic brain injury in cooking tasks.

Purpose: Individuals with traumatic brain injury (TBI) often experience difficulties in performing kitchen-related sequencing tasks due to cognitive deficits. The primary aim of this study is to examine the feasibility of a context-aware automatic prompting system in assisting individuals with TBI in multi-step cooking tasks.Method: Sixteen individuals with TBI participated in the study. A randomized cross-over design was used to compare the automatic prompting method with a conventional user-controlled method through a tablet device. Participant performance under each prompting method was assessed using the Performance Assessment of Self-Care Skills in terms of independence, safety, and adequacy. Subjective workload and qualitative feedback were also collected.Results: The automatic method, when compared with the user-controlled method, significantly decreased the amount of external assistance required by participants, received higher ratings in user perceived ease-of-use, and was considered less stressful for participants. However, the user-controlled method showed strengths in offering participants more flexibility in terms of controlling on the timing of prompts.Conclusions: The results provided insight into the potential benefits and user perceptions of a context-aware prompting system. The information could contribute to the future development of advanced prompting technology for people with cognitive impairments in completing sequential tasks.Implications for RehabilitationFor people with traumatic brain injury, the context-aware prompting method showed advantages in improving user performance, receiving better ratings on ease-of-use, and decreasing stress levels, compared to the user-controlled prompting method in completing multi-step cooking tasks.Future prompting systems for people with cognitive impairments may allow users to control the pace of prompting and use sensing information as back-up assistance in critical situations. In this way, the system may help users monitor their actions and offer confirmations, especially at steps with safety concerns, thus enhancing the sense of security and reducing the stress from self-monitoring.

Use of Assistive Technology for Cognition Among People With Traumatic Brain Injury: A Survey Study.

A survey was designed and administered in this study to assess the use of assistive technology for cognition (ATC), especially portable electronic ATC, among veterans with traumatic brain injury (TBI). The aim of the survey was to obtain information on current ATC devices and applications use, users' experience with different features of ATC, and relevant training/support for their ATC. Twenty-nine veterans with TBI participated in this study. Results showed that portable electronic ATC, especially smartphones and a variety of apps, were widely used by the participants to compensate for cognitive limitations. Portable electronic devices such as smartphones and smart pads received higher usability ratings than paper-based tools. More than 75% of participants did not go through a service delivery process for these electronic ATC. The information collected in the study provided a more updated picture of ATC use, especially portable electronic ATC use, among people with TBI. It also potentially informs the future development of ATC and supports the need for training and an appropriate acquisition process of portable electronic ATC devices.

Interrater Reliability of the Power Mobility Road Test in the Virtual Reality-Based Simulator-2.

OBJECTIVE: To assess interrater reliability of the Power Mobility Road Test (PMRT) when administered through the Virtual Reality-based SIMulator-version 2 (VRSIM-2). DESIGN: Within-subjects repeated-measures design. SETTING: Participants interacted with VRSIM-2 through 2 display options (desktop monitor vs immersive virtual reality screens) using 2 control interfaces (roller system vs conventional movement-sensing joystick), providing 4 different driving scenarios (driving conditions 1-4). Participants performed 3 virtual driving sessions for each of the 2 display screens and 1 session through a real-world driving course (driving condition 5). The virtual PMRT was conducted in a simulated indoor office space, and an equivalent course was charted in an open space for the real-world assessment. After every change in driving condition, participants completed a self-reported workload assessment questionnaire, the Task Load Index, developed by the National Aeronautics and Space Administration. PARTICIPANTS: A convenience sample of electric-powered wheelchair (EPW) athletes (N=21) recruited at the 31st National Veterans Wheelchair Games. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Total composite PMRT score. RESULTS: The PMRT had high interrater reliability (intraclass correlation coefficient [ICC]>.75) between the 2 raters in all 5 driving conditions. Post hoc analyses revealed that the reliability analyses had >80% power to detect high ICCs in driving conditions 1 and 4. CONCLUSIONS: The PMRT has high interrater reliability in conditions 1 and 4 and could be used to assess EPW driving performance virtually in VRSIM-2. However, further psychometric assessment is necessary to assess the feasibility of administering the PMRT using the different interfaces of VRSIM-2.

Stability and Workload of the Virtual Reality-Based Simulator-2.

OBJECTIVE: To assess the stability of clinicians' and users' rating of electric-powered wheelchair (EPW) driving while using 4 different human-machine interfaces (HMIs) within the Virtual Reality-based SIMulator-version 2 (VRSIM-2) and in the real world (accounting for a total of 5 unique driving conditions). DESIGN: Within-subjects repeated-measures design. SETTING: Simulation-based assessment in a research laboratory. PARTICIPANTS: A convenience sample of EPW athletes (N=21) recruited at the 31st National Veterans Wheelchair Games. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Composite PMRT scores from the Power Mobility Road Test (PMRT); Raw Task Load Index; and the 6 subscale scores from the Task Load Index developed by the National Aeronautics and Space Administration (NASA-TLX). RESULTS: There was moderate stability (intraclass correlation coefficient between .50 and .75) in the total composite PMRT scores (P<.001) and the users' self-reported performance scores (P<.001) among the 5 driving conditions. There was a significant difference in the workload among the 5 different driving conditions as reflected by the Raw Task Load Index (P=.009). Subanalyses revealed this difference was due to the difference in the mental demand (P=.007) and frustration (P=.007) subscales. Post hoc analyses revealed that these differences in the NASA-TLX subscale scores were due to the differences between real-world and virtual driving scores, particularly attributable to the conditions (1 and 3) that lacked the rollers as a part of the simulation. CONCLUSIONS: Further design improvements in the simulator to increase immersion experienced by the EPW user, along with a standardized training program for clinicians to deliver PMRT in VRSIM-2, could improve the stability between the different HMIs and real-world driving.

Preliminary evaluation of variable compliance joystick for people with multiple sclerosis.

Upper-limb fatigue is a common problem that may restrict people with multiple sclerosis (MS) from using their electric powered wheelchair effectively and for a long period of time. The objective of this research is to evaluate whether participants with MS can drive better using a variable compliance joystick (VCJ) and customizable algorithms than with a conventional wheelchair joystick. Eleven participants were randomly assigned to one of two groups. The groups used either the VCJ in compliant or noncompliant isometric mode and a standard algorithm, personally fitted algorithm, or personally fitted algorithm with fatigue adaptation running in the background in order to complete virtual wheelchair driving tasks. Participants with MS showed better driving performance metrics while using the customized algorithms than while using the standard algorithm with the VCJ. Fatigue adaptation algorithms are especially beneficial in improving overall task performance while using the VCJ in isometric mode. The VCJ, along with the personally fitted algorithms and fatigue adaptation algorithms, has the potential to be an effective input interface for wheelchairs.

Assessment of wheelchair driving performance in a virtual reality-based simulator.

OBJECTIVE: To develop a virtual reality (VR)-based simulator that can assist clinicians in performing standardized wheelchair driving assessments. DESIGN: A completely within-subjects repeated measures design. METHODS: Participants drove their wheelchairs along a virtual driving circuit modeled after the Power Mobility Road Test (PMRT) and in a hallway with decreasing width. The virtual simulator was displayed on computer screen and VR screens and participants interacted with it using a set of instrumented rollers and a wheelchair joystick. Driving performances of participants were estimated and compared using quantitative metrics from the simulator. Qualitative ratings from two experienced clinicians were used to estimate intra- and inter-rater reliability. RESULTS: Ten regular wheelchair users (seven men, three women; mean age ± SD, 39.5 ± 15.39 years) participated. The virtual PMRT scores from the two clinicians show high inter-rater reliability (78-90%) and high intra-rater reliability (71-90%) for all test conditions. More research is required to explore user preferences and effectiveness of the two control methods (rollers and mathematical model) and the display screens. CONCLUSIONS: The virtual driving simulator seems to be a promising tool for wheelchair driving assessment that clinicians can use to supplement their real-world evaluations.