Mobile Testing Research Articles

Simple Mobility Tests Predict Use of Assistive Devices in Older Adults.

Assistive devices (ADs) for ambulation are commonly provided to improve safety and independence in older adults. Despite the common use of these devices, there are no standard prescribing guidelines, and non-health care providers, including caregivers and family members, often make decisions about the need for ADs. Identifying factors or a single screening test associated with AD use would benefit clinicians and non-health care caregivers in making decisions to adopt an AD for patients, clients, and family members. The purpose of this cross-sectional study was to identify the test that best predicts ADs for ambulation and non-AD use among community-dwelling individuals. Eighty-five older adults (81.6 ± 8.2 years old) who underwent outpatient physical therapy participated in this study. They participated in a series of tests, including the Timed Up and Go, handgrip and quadriceps strength, the 30-second chair-rise test, the 5-m fast gait speed, the Functional Independence Measure, the locomotive syndrome tests (stand-up test, 2-step test [2ST], and the Locomo-5 Checklist), and numeric pain scales. Mann-Whitney U tests were used to identify differences between those who did and did not use an AD for ambulation. Logistic regression analyses were used to examine which test best predicted AD use. 80% of participants (n = 68) used an AD for ambulation. There were significant differences in all test variables between users and nonusers (P = .033 to P < .001), except for quadriceps strength, age, and pain (all P > .05). Only the 2ST was a significant predictor of AD use, with a cutoff distance of the toe-to-toe stride shorter than 93% of body height (sensitivity: 72%, and specificity: 82%, P = .048). Simple functional measures differed between those who did and did not use ADs for ambulation; however, only the 2ST predicted AD status. Individuals who cannot step 93% of their body height may be appropriate for an AD. If comprehensive clinical evaluations are not available to make decisions about AD use, the 2ST can be used to make clinical recommendations for an AD for ambulation.

Integrating testing volume into bandit algorithms for infectious disease surveillance

Abstract Mobile testing services provide opportunities for active surveillance of infectious diseases for hard-to-reach and/or high-risk individuals who do not know their disease status. Identifying as many infected individuals as possible is important for mitigating disease transmission. Recently, multi-armed bandit sampling approaches have been adapted and applied in this setting to maximize the cumulative number of positive tests collected over time. However, these algorithms have not considered the possibility of variability in the number of tests administered across testing sites. What impact this variability has on the ability of these approaches to maximize yield is currently unknown. Therefore, we investigate this question by extending existing sampling frameworks to directly account for variability in testing volume while also maintaining the computational tractability of the previous methods. Through a simulation study based on human immunodeficiency virus infection characteristics in the Republic of the Congo (Congo-Brazzaville) as well as an application to COVID-19 testing data in Connecticut, we find improved long- and short-term performances of the new methods compared to several existing approaches. Based on these findings and the ease of computation, we recommend use of the newly developed methods for active surveillance of infectious diseases when variability in testing volume may be present.

Smartphone-Based Assessment of Mobility and Manual Dexterity in Adult People with Spinal Muscular Atrophy.

More responsive, reliable, and clinically valid endpoints of disability are essential to reduce size, duration, and burden of clinical trials in adult persons with spinal muscular atrophy (aPwSMA). The aim is to investigate the feasibility of smartphone-based assessments in aPwSMA and provide evidence on the reliability and construct validity of sensor-derived measures (SDMs) of mobility and manual dexterity collected remotely in aPwSMA. Data were collected from 59 aPwSMA (23 walkers, 20 sitters and 16 non-sitters) and 30 age-matched healthy controls (HC). SDMs were extracted from five smartphone-based tests capturing mobility and manual dexterity, which were administered in-clinic and remotely in daily life for four weeks. Reliability (Intraclass Correlation Coefficients, ICC) and construct validity (ability to discriminate between HC and aPwSMA and correlations with Revised Upper Limb Module, RULM and Hammersmith Functional Scale - Expanded HFMSE) were quantified for all SDMs. The smartphone-based assessments proved feasible, with 92.1% average adherence in aPwSMA. The SDMs allowed to reliably assess both mobility and dexterity (ICC > 0.75 for 14/22 SDMs). Twenty-one out of 22 SDMs significantly discriminated between HC and aPwSMA. The highest correlations with the RULM were observed for SDMs from the manual dexterity tests in both non-sitters (Typing, ρ= 0.78) and sitters (Pinching, ρ= 0.75). In walkers, the highest correlation was between mobility tests and HFMSE (5 U-Turns, ρ= 0.79). This exploratory study provides preliminary evidence for the usability of smartphone-based assessments of mobility and manual dexterity in aPwSMA when deployed remotely in participants' daily life. Reliability and construct validity of SDMs remotely collected in real-life was demonstrated, which is a pre-requisite for their use in longitudinal trials. Additionally, three novel smartphone-based performance outcome assessments were successfully established for aPwSMA. Upon further validation of responsiveness to interventions, this technology holds potential to increase the efficiency of clinical trials in aPwSMA.

Revue à 18 ans de recul minimum, de 10 patients présentant une luxation périlunaire isolée du carpe

Objective: To evaluate, in long-term, the functional abilities and the occurrence of osteoarthritis in patients treated for a posterior perilunate carpal dislocation without bone lesion associated.Patients and method: This was a monocentric retrospective observational study on patients operated on at the University Hospital of Guadeloupe for a posterior perilunate dislocation without bone lesion associated with a minimum of 18 years of follow-up. Ten patients were included with a mean follow-up of 22.8 years. The evaluation criteria were clinical (PRWE, QuickDASH, pain, grip strength, wrist joint mobility, Watson and Reagan tests, Cooney functional score) and radiographic (Gilula curves, carpal height, carpal ulnar translation, scapholunate and radiolunar angles, scapholunate and triquetro-lunar interlines in statics and dynamics, Herzberg’s classification of complications).Results: The average Cooney score was 67.5/100. Mean PRWE and QuickDASH scores were 33.9 and 24.8 respectively. The mean flexion-extension arc on the injured side was 71.5° (66,7% compared to the healthy side). Mean grip strength was 27kg (72,8% compared to the healthy side). The prevalence of osteoarthritis was 60%, with three A types, two A1 types, one B type and four B1 types according to Herzberg.Conclusion: The factors influencing the long-term prognosis are the initial displacement of the lunate, the quality of the reduction and the presence of chronic carpal instability, particularly scapholunate. The high prevalence of osteoarthritis in our series (60%) is apparently not correlated with the functional capacities of patients over the long term.

Consistency of different functional mobility tests in older people with Parkinson’s disease

Consistency of different functional mobility tests in older people with Parkinson’s disease

Functional and Structural Long-Term Effects of Repetitive Instrument-Assisted Manual Therapy (IAMT) of the Lumbar Back on the Dorsal Myofascial Chain Among Female Soccer Players: A Randomized, Placebo-Controlled Pilot Trial.

Instrument-assisted manual therapy (IAMT) is suitable for optimizing movement prerequisites, such as range of motion, flexibility, microcirculation, and pain inhibition along myofascial chains, potentially leading to a reduction in hamstring injuries. To date, however, IAMT's modes of action remain largely unclear. This study aimed to examine the functional and structural effects of repetitive IAMT after 2.5 and five weeks. Sixteen healthy female soccer players (age: 21.4 (±5.1) years) were randomly grouped into an intervention group and a placebo control group. The intervention group received nine IAMT sessions twice weekly at the right lumbar region. The placebo group received a single pressureless "therapy" at baseline. In addition to structural ultrasound analyses (absolute motion and shear motion), functional mobility tests (passive straight leg raise (PSLR) test and lumbar and thoracic double inclinometry) were performed 4.0 (±2.0) days after the fourth IAMT and 3.4 (±1.1) days after the ninth IAMT in both groups. Hamstring flexibility in the PSLR test improved significantly after the ninth IAMT compared with the placebo group (p< 0.05, effect size: 0.913). No systematic differences were seen at the structural level. Repetitive IAMT can improve hamstring flexibility. Further studies in larger groups and diverse collectives are necessary to additionally test the postulated preventive effect also on hamstring injuries. Whether ultrasound is the right method for detecting structural changes in this context needs to be verified in the future.

Advancing Element Identification for Web and Mobile Automation

Element identification is a cornerstone of automation testing, directly influencing the reliability, scalability, and efficiency of test scripts. With the rapid evolution of web and mobile applications, traditional element identification methods—such as XPath, CSS Selectors, and static attributes—are increasingly challenged by dynamic DOM structures, shadow DOMs, virtual DOMs, and hybrid frameworks. These challenges are further amplified in mobile environments, where gestures, native elements, and platform-specific attributes add layers of complexity. This paper explores the advancements in element identification techniques that address these challenges for both web and mobile automation testing. It presents a comparative analysis of traditional methods and emerging solutions, highlighting their limitations in modern application scenarios. The study introduces hybrid strategies, including context-aware locators, heuristic-based identification, and early implementations of adaptive and self-healing locators. It also examines the role of cross-platform tools like Selenium, Appium, and Cypress in tackling identification issues. Furthermore, the paper emphasizes the importance of unified approaches that bridge web and mobile testing, particularly in hybrid applications with embedded web views. Future trends, such as collaborative tagging standards between development and testing teams, are discussed to provide a forward-looking perspective on overcoming element identification bottlenecks. By addressing key pain points and proposing innovative techniques, this paper aims to guide testers, developers, and tool creators in adopting resilient, scalable, and adaptable element identification strategies that meet the demands of modern software applications.

Effects of combining thoracic lymphatic pump technique and exercises on patients with chronic mechanical low back pain

Purpose. The study aimed to compare the effects of combining thoracic lymphatic pump technique (TLPT) and exercises versus exercises alone on pain intensity, lumbar spine mobility, and functional disability in patients with chronic mechanical low back pain (CMLBP), the second most common orthopedic condition. Methods. Fifty-two CMLBP patients, whose mean age was 25 years, were classified into 2 equal groups randomly. Group (A) received exercises (hamstring stretching, lower back stretching, abdominal strengthening, and trunk extensor strengthening). Group (B) received the same exercises plus the thoracic lymphatic pump technique. Both groups received 12 sessions on nonconsecutive days. All patients were evaluated using the Visual Analogue Scale (VAS) for pain intensity, the Modified-Modified Schober test (MMST) for lumbar mobility (flexion-extension), and the Oswestry Disability Index (ODI) for functional disability. Assessments were performed prior to and after the end of treatment. For data analysis, the unpaired t-test, chi-squared test, and mixed MANOVA test were used. Results. The study found significant improvements in pain intensity, lumbar mobility (flexion, extension), and functional disability in both groups (P &lt; 0.05), with no significant difference in pain intensity or lumbar spine mobility. However, group (B) had a statistically significant advantage in functional disability (P &lt; 0.05). Conclusion. The addition of the thoracic lymphatic pump technique to therapeutic exercises significantly enhances pain, lumbar spine mobility, and functional abilities in CMLBP patients than therapeutic exercises alone.

Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science.

This study presents a fit-for-purpose lab and field evaluation of commercially available portable sensor systems for PM, NO2, and/or BC. The main aim of the study is to identify portable sensor systems that are capable of reliably quantifying dynamic exposure gradients in urban environments. After an initial literature and market study resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked under laboratory and real-word conditions. We evaluated the comparability to reference analyzers, sensor precision, and sensitivity towards environmental confounders (temperature, humidity, and O3). Moreover, we evaluated if the sensor accuracy can be improved by applying a lab or field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM (R2 = 0.68-0.9, Uexp = 16-66%, BSU = 0.1-0.7 µg/m3) and BC (R2 = 0.82-0.83), but maturity of the tested NO2 sensors is still low (R2 = 0.38-0.55, Uexp = 111-614%) and additional efforts are needed in terms of signal noise and calibration, as proven by the performance after multilinear calibration (R2 = 0.75-0.83, Uexp = 37-44%)). The horizontal accuracy of the built-in GPS was generally good, achieving <10 m accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and the resulting impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

Mapless Path Planning for Mobile Robot Based on Improved Deep Deterministic Policy Gradient Algorithm.

In the traditional Deep Deterministic Policy Gradient (DDPG) algorithm, path planning for mobile robots in mapless environments still encounters challenges regarding learning efficiency and navigation performance, particularly adaptability and robustness to static and dynamic obstacles. To address these issues, in this study, an improved algorithm frame was proposed that designs the state and action spaces, and introduces a multi-step update strategy and a dual-noise mechanism to improve the reward function. These improvements significantly enhance the algorithm's learning efficiency and navigation performance, rendering it more adaptable and robust in complex mapless environments. Compared to the traditional DDPG algorithm, the improved algorithm shows a 20% increase in the stability of the navigation success rate with static obstacles along with a 25% reduction in pathfinding steps for smoother paths. In environments with dynamic obstacles, there is a remarkable 45% improvement in success rate. Real-world mobile robot tests further validated the feasibility and effectiveness of the algorithm in true mapless environments.

Designing tests for some physical abilities and predicting the level of performance skill for academic school football players at the ages of (13-14) years

The study aims to design tests to measure some physical abilities in the study sample, to find standard grades and levels for some tests of physical abilities in the study sample, preparing equations to predict the level of performance skill of soccer players in terms of mobility tests in the research sample. The researcher used the descriptive approach, and the research community was selected from football academy players with ages (13-14) years in Raparin. The research sample was selected intentionally, which included (260) players. So as to reach the results, the researcher used a set of statistical programs by using SPSS. It was concluded to find and determine the grades and standard levels modified for the research sample in the physical tests. It is concluded that these tests can be accepted as an evaluation method and indicator to show the player's physical and skillful condition, and to define an equation to predict the level of performance skill in terms of physical abilities.

An Iterative Approach to Usability Evaluation: A Workplace Wellness Mobile Application Example.

Without a gold standard for mobile app usability testing, this paper outlines a case study of how a not-for-profit organization tested the usability of a public-facing mobile app designed to promote the health and wellbeing of workers in Canada by offering accessible resources conveniently through one's mobile phone. Although the app was developed by a third-party vendor, usability testing and refinement was left to the organization due to budgetary and time constraints. The app underwent three rounds of iterative usability testing. The first phase consisted of observing participants using the app followed by an interview. The second and third phases involved participants following task-based instructions and answering survey questions. All phases uncovered issues which helped to improve and refine the usability of the app before the launch to the public. This work offers a case study example of how low-cost in-house usability testing could be employed.

2358 Evaluation of a novel screening protocol for respiratory viral infections in long-term care homes

Abstract Introduction Respiratory viral illnesses (RVI) pose a serious threat to LTC residents. Those with frailty often experience non-specific presentations causing delayed diagnosis and treatment of infection. To facilitate early RVI detection, a screening protocol was developed to evaluate changes in cognitive and functional status of LTC residents using the Single Question in Delirium (SQiD) with new Single Question in Functioning (SQiF) and Single Question in Reduced Mobility (SQiRM). This study aims to address: (i) If novel (SQiD/SQiF/SQiRM) screening was superior to public health in detecting COVID-19 in LTC, and; (ii) Did combining the novel and public health screening improve detection of COVID-19. Methods The novel screening protocol was integrated into daily screening for RVI at three LTC homes in Nova Scotia, Canada. Daily assessments were recorded in consenting residents. If any of the novel protocol was positive, the 4As Test (4AT) and Hierarchal Assessment of Balance and Mobility (HABAM) were evaluated and a positive 4AT and/or HABAM triggered an RVI swab for COVID-19. Area under the curve (AUC,) sensitivity and specificity analysis using PCR tests as the reference criterion was utilised. Between October 2021 to February 2024, 378 LTC residents consented to participate, resulting in 142 positive COVID-19 PCR tests. Preliminary results show public health screening had a sensitivity of 68.3%, specificity of 52.1% and AUC of 0.60. Novel protocol exhibited sensitivity of 12.0%, specificity of 85.2% and AUC of 0.49. Combining public health and novel screening yielded a sensitivity of 80.3%, specificity of 32.3% with a AUC of 0.59. Conclusions Preliminary results suggest that incorporating public health and novel protocol screening for daily RVI assessments in LTC is advantageous. Predictive accuracy is slightly less with combined screening, but sensitivity of the combined screening protocols remains high. Other information Ethical approval obtained from Nova Scotia Health Research Ethics Board # 1026558.

Short-Term Coupling Associations Between State Loneliness and Cognitive Performance in Daily Life Among Older Adults.

Despite extensive efforts to study individual differences in loneliness and neurocognitive health, little is known about how within-person changes in state loneliness relate to cognitive performance. This study addressed this gap by examining the association between within-person variation in state loneliness and cognitive performance assessed objectively in daily life. Participants were 313 community-dwelling older adults (70-90 years) who reported momentary feelings of loneliness and completed smartphone-based cognitive tests 5 times daily for 14 consecutive days. Mobile cognitive tests assess visual associative memory, processing speed, and spatial memory. At the day level, average state loneliness levels were negatively related to cognitive performance on the same day and subsequent day. Consistent with the day-level analysis, momentary assessments of increased loneliness were consistently linked to worse cognitive performance on concurrent assessments. However, moments characterized by lower cognitive performance predicted higher levels of loneliness 3-4hr later (next occasion), but not vice versa. The findings suggest a prospective association between loneliness and cognitive performance, with higher daily loneliness negatively associated with cognitive performance on the same day and predicting worse performance the following day. Notably, within a single day, lower cognitive performance at a given moment predicted elevated loneliness later in the day. This highlights a complex, reciprocal relationship-loneliness predicting and being predicted by cognitive performance depending on timescale.

Impact of Classical Music Listening on Cognitive and Functional Performances in Middle-Aged Women

The purpose of this study was to examine the impact of listening to classical music on functional (upper and lower body strength, functional mobility and aerobic endurance) and cognitive (attentional capacities and working memory (WM)) performances in women aged between 50 and 60 years old. A total of 24 middle-aged women were enrolled to participate in this study. Their functional and cognitive performances were assessed under two-auditory conditions (no-music vs. with music conditions) using the Timed Up and Go (TUG) test for functional mobility, the Arm Curl test and 30 s Chair Stand Tests for the upper and lower body strength, respectively, and the 2 min Step test for aerobic endurance. To assess the attentional capacities and the WM, a simple reaction time (SRT) test and Corsi Block-Tapping Task were used, respectively. As a result, we found that listening to music significantly decreased the scores of the TUG test (p &lt; 0.001) and capacities (p &lt; 0.05), and increased the 2 min Step test values (p &lt; 0.001) compared to the no-music condition. However, no significant changes were found for the upper and lower body strength and WM. We conclude that listening to classical music, i.e., Mozart’s Symphony, is effective in improving functional mobility, aerobic endurance and attentional capacities in middle-aged women. However, these gains were absent for muscle strength and WM, suggesting that the positive effects of music on functional and cognitive performances were dependent on a specific task.

Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.

Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented mobility testing and subsequent data processing, as well as the added workload and complexity of this multi-step process. To simplify sensor-based mobility testing in diagnosing PD, we analyzed data from 262 PD participants and 50 controls performing several motor tasks wearing a sensor on their lower back containing a triaxial accelerometer and a triaxial gyroscope. Using ensembles of heterogeneous machine learning models incorporating a range of classifiers trained on a set of sensor features, we show that our models effectively differentiate between participants with PD and controls, both for mixed-stage PD (92.6% accuracy) and a group selected for mild PD only (89.4% accuracy). Omitting algorithmic segmentation of complex mobility tasks decreased the diagnostic accuracy of our models, as did the inclusion of kinesiological features. Feature importance analysis revealed that Timed Up and Go (TUG) tasks to contribute the highest-yield predictive features, with only minor decreases in accuracy for models based on cognitive TUG as a single mobility task. Our machine learning approach facilitates major simplification of instrumented mobility testing without compromising predictive performance.

L Test Subtask Segmentation for Lower-Limb Amputees Using a Random Forest Algorithm.

Functional mobility tests, such as the L test of functional mobility, are recommended to provide clinicians with information regarding the mobility progress of lower-limb amputees. Smartphone inertial sensors have been used to perform subtask segmentation on functional mobility tests, providing further clinically useful measures such as fall risk. However, L test subtask segmentation rule-based algorithms developed for able-bodied individuals have not produced sufficiently acceptable results when tested with lower-limb amputee data. In this paper, a random forest machine learning model was trained to segment subtasks of the L test for application to lower-limb amputees. The model was trained with 105 trials completed by able-bodied participants and 25 trials completed by lower-limb amputee participants and tested using a leave-one-out method with lower-limb amputees. This algorithm successfully classified subtasks within a one-foot strike for most lower-limb amputee participants. The algorithm produced acceptable results to enhance clinician understanding of a person's mobility status (>85% accuracy, >75% sensitivity, >95% specificity).

Evaluating the feasibility of a tele-diagnostic auditory brainstem response service in a rural context.

There is a noticeable gap in access to audiology services in South Africa, and the gap is intensified in rural areas. Often, primary healthcare (PHC) facilities have an unequal ratio of audiologists to patients in need. Telehealth can expand the range of hearing healthcare services. This study aimed to determine whether, for infants, tele-diagnostic Auditory Brainstem Response (ABR) assessment results conducted within a mobile clinic van are comparable to face-to-face diagnostic ABR results in rural Winterveldt, Pretoria North, South Africa. The study utilised a quantitative, prospective cross-sectional comparative within-subject design. Each participant received both face-to-face and mobile tele-diagnostic ABR tests, which were then compared to evaluate the feasibility of mobile tele-diagnostic ABR testing. The Student's t-test was used to determine whether there was a difference between face-to-face and tele-diagnostic tests, and Bland -Altman plots were used to assess the level of agreement between the ABR testing results. There was a strong correlation (p 0.001) between face-to-face and mobile tele-diagnostic ABR test results for both neurological and audiological ABR tests. The study found that there was no statistical significance between face-to-face and tele-diagnostic ABR measures; additionally, the results were within clinically acceptable and normative measures. Tele-diagnostic ABR offered within a mobile clinic van is feasible as it produces similar and clinically acceptable results when compared to the traditional assessment method.Contribution:This feasibility study is a positive indicator that tele-diagnostic ABR testing through a mobile clinic van may be considered to accelerate the delivery of hearing healthcare services to the infant population in rural communities.

Extraction and empirical evaluation of GUI-level invariants as GUI Oracles in mobile app testing

ContextMobile apps (software) are used in almost all aspects of daily life by billions of people. Given the widespread use of mobile apps in various domains, the demand for systematic testing of their Graphical User Interfaces (GUI) is crucial. Despite the significant advances in automated mobile app testing over the last decade, certain challenges remain, most notably the app-specific GUI test-oracle problem, which can significantly hinder the effective detection of defects in mobile apps. In this study, we introduce the use of GUI-level invariants, referred to as GUI invariants, as app-specific GUI oracles in GUI test cases to address this challenge. MethodsWe propose a semi-automatic solution to extract GUI invariants and use them as app-specific GUI oracles in test cases. We use the mutation testing technique to evaluate the (fault detection) effectiveness of the GUI oracles used. In addition, we evaluate their quality aspects, namely correctness, understandability, and compatibility, from the perspective of human experts using a questionnaire survey. ResultsThe empirical results show that the GUI oracles used are effective and helpful, as they improved the fault-detection effectiveness of the empirical test suites ranging from 18% to 32%. These results also highlight the efficacy of GUI oracles used in identifying various defects, including crashing and non-crashing functional issues, and surpassing the performance of existing tools in fault-detection rates. Additionally, the questionnaire survey outcomes indicate that the GUI oracles used are correct, understandable, and compatible. ConclusionsBased on the empirical results, we can conclude that using GUI invariants as GUI oracles can be useful and effective in mobile app testing.

Do automated vehicle trials test society? Testing mobility futures in the West Midlands

Do automated vehicle (AV) trials in everyday environments like urban streets constitute social tests? This article answers this question with a firm no and yes, based on field study of automated mobility testbeds in the United Kingdom, with a focus on the West Midlands. Engaging with the social studies of testing and automobility futures research, this article examines how AV tests in real-world settings do double duty as tests of society, even as they are marked by social deficits. I develop this analysis by juxtaposing two very different perspectives on automated mobility testing, those of 1) UK AV experts, and 2) residents, artists and researchers who live or work in the West Midlands Future Mobility testbed. I develop two claims. First, I show how real-world testing of automated vehicles remains vehicle-centric, to the point that testing for social aspects for some experts is only conceivable in a simulator. Second, through participatory listening walks I show how AV testing in society raises significant challenges for local communities in the absence of demonstrable benefits in the present. I conclude that the testbed in question does not currently enable the exploration of societal mobility futures, but fieldwork in this environment can help us understand what this would take.