Search Results (278)

Background/Objectives: Maintaining a stationary manual wheelchair wheelie is a highly demanding dynamic postural control task that can be biomechanically modeled as an inverted pendulum. Although skilled wheelchair users employ a Proactive Balance Strategy (PBS) characterized by small rhythmic wheel movements, its underlying biomechanical control mechanism remains incompletely understood. This study investigated whether the PBS serves as a functional analogue of the human standing ankle strategy by examining the dynamic relationships among wheelchair orientation, center of pressure, and center of mass dynamics. Methods: Forty healthy adults with prior wheelchair wheelie training performed stationary wheelie trials on a force platform while three-dimensional kinematic and kinetic data were collected simultaneously. Results: Cross-correlation analysis demonstrated a strong inverse relationship between wheelchair pitch angle and rear-wheel displacement (r = −0.73, phase lag = 0.032 s). A moderate inverse relationship was also observed between the horizontal center of pressure (COP_x) and horizontal center-of-mass acceleration (COM_accx) (r = −0.61) with a near-zero mean phase lag (−0.003 s). Conclusions: These findings support a functional biomechanical analogy between PBS and the ankle strategy during standing balance. The coordinated kinematic and kinetic relationships indicate that stationary wheelie balance is maintained through continuous regulation of rear-wheel position, which changes the wheel–ground contact point and thereby modulates the COP and whole-body dynamics. The observed biomechanical coupling is compatible with the proactive characteristics proposed for PBS. Although this study involved healthy adults with prior wheelie experience rather than daily wheelchair users, the findings provide a quantitative biomechanical framework for understanding stationary wheelchair wheelie balance and may inform future wheelchair skills training and rehabilitation strategies. Full article

This study presents the concept design of a wireless-controlled powered transport chair for caregiver-assisted handling and short-duration seated movement in care facilities. No prototype has been fabricated and no structural, metrological, or human testing has been performed; every value reported is a design requirement, not a measured result. The intended users are adult patients who tolerate supported sitting and retain enough trunk control to remain seated with the support rails and restraint engaged, together with a trained caregiver; patients needing full postural support or a lying transfer are outside the intended use. The device integrates powered low-speed mobility, height adjustment, a powered fore–aft seat extension that bridges the residual gap left at the bed base, local and wireless control, an independent hardwired emergency stop, and load-cell seated weight measurement. The frame is designed to accommodate a patient of up to 150 kg. A Raspberry Pi provides the user interface, while an independent hardware layer governs all powered motion. Candidate frame materials are compared qualitatively. Verification covers proof-load testing, worst-case static stability, load-cell calibration, control and emergency-stop response, power-loss recovery, battery endurance, and usability testing with caregivers and patients. Participatory design with wheelchair users and caregivers is planned before fabrication. Full article

Background/Objectives: Urban accessibility is a key determinant of participation for manual wheelchair users, yet accessibility experiences vary according to physical impairment, self-efficacy in wheeled mobility, and wheelchair mobility proficiency. This scoping review examined urban accessibility challenges in relation to these three dimensions. Methods: Following PRISMA-ScR guidelines, eight databases were searched for English-language peer-reviewed studies published from January 2015 to May 2025. Eligible studies addressed outdoor or urban mobility challenges among manual wheelchair users in relation to at least one dimension. Two reviewers independently screened records, assessed full texts, and extracted data using a standardized form. Findings were synthesized within an International Classification of Functioning, Disability and Health-informed framework. Fourteen studies were included. Results: The evidence base was methodologically diverse and fragmented; no study examined all three dimensions simultaneously, and wheelchair mobility proficiency received the least attention. Greater physical impairment was associated with more perceived barriers and higher effort. Self-efficacy influenced avoidance of or engagement in mobility tasks beyond physical functioning. Wheelchair mobility proficiency, supported by training, experience, and wheelchair fit, was associated with managing ramps, uneven surfaces, and other environmental demands, but was rarely assessed using standardized performance measures. Conclusions: Urban accessibility reflects interactions among physical functioning, self-efficacy, wheelchair mobility proficiency, assistive-device characteristics, and environmental conditions. Accordingly, urban mobility should be understood as a person–wheelchair–environment interaction rather than solely as an interaction between the individual and the built environment. Integrative studies using standardized measures and more systematic reporting of wheelchair fit and configuration are needed to inform impairment-inclusive urban planning, rehabilitation, and policy. Full article

Background/Objectives: To map the literature and describe the meaning, use, and experience of power mobility for children with complex non-ambulant cerebral palsy (Gross Motor Classification System (GMFCS) levels IV–V and Manual Abilities Classification System (MACS) levels III–V). Methods: Included searches in five electronic databases, grey literature, and hand searches with no restrictions on date, study type, or language, as well as independent duplicate screening and data extraction. Outcomes and experiences were mapped to the integrated F-words Interdependence Human Activity Assistive Technology (iHAAT) framework. Results: In total, 90 studies, from randomized trials to case reports and qualitative designs, included 916 children (10 months–18 years; 432 GMFCS IV; 262 GMFCS V; 222 GMFCS IV/V), with 351 parents, therapists, or educators. Only 32 studies reported MACS levels. Power wheelchairs were used by 724 children (68 used switches rather than joysticks). Other children used modified ride-on cars, specialty pediatric devices, or platform/smart training devices. Based on 22 studies where this information was provided, alternate access/control methods were primarily used by children classified at GMFCS/MACS V, but there was considerable variability. Introduction predominantly occurred in natural settings with limited training or support. Significant and meaningful improvements in power mobility use were reported for intensive play-based, child-led, and caregiver-supported approaches; for virtual training with joystick users; and for skills-training approaches with older children who already achieved functional power wheelchair use. Conclusions: Children classified at GMFCS IV and V may benefit from power mobility experience to promote fitness, functioning, friends, family, fun, and future outcomes. Their use and experience of power mobility may be interdependent with parents, therapists, and educators, changing attitudes and perceptions of child potential. Full article

Gesture recognition systems powered by artificial intelligence provide a promising solution for mobility and independence for individuals with physical disabilities. However, the deployment of such systems remains limited due to some challenges related to robustness, different user requirements, affordability for lower income people, and adaptation to low-resource environments. This study presents a systematic review of gesture-controlled intelligent wheelchair systems published recently. After searching academic databases, 600 studies were found. After removing duplicate and irrelevant studies and applying the inclusion and exclusion criteria, 72 of the most relevant studies were selected for detailed analysis. The review identifies three major approaches: vision-based methods, sensor-based techniques, and signal-based techniques utilizing electromyography (EMG) and inertial measurement units (IMU), and hybrid multimodal frameworks. A comparative study is conducted to analyze performance metrics, computational requirements, datasets, and validation strategies among these approaches. The findings identify several critical research gaps, including limited real-world testing, insufficient handling of pathological tremors, weak environmental robustness, and the lack of culturally aligned gesture vocabularies. The findings identify important design considerations and research directions for developing robust, affordable, and accessible intelligent wheelchair systems suitable for underserved people in low-resource environments. Full article

Air cell-based wheelchair seat cushions are widely used for pressure ulcer prevention in individuals with limited mobility. However, the influence of ambient pressure variations on the mechanical surface pressure acting on users has not been systematically investigated. This study presents a dedicated measurement concept to quantify these effects under controlled laboratory conditions. Surface pressure was quantified using a dual-range FSR sensor calibration, achieving a minimum resolution of 0.0012 N/cm² per digit. Five representative scenarios were investigated, covering ambient pressure reductions between 30 hPa (elevator rides) and 250 hPa (aircraft takeoff). Measurements were conducted across 150 series, combining five initial internal cushion pressures and six load levels. Ambient pressure reductions led to measurable increases in surface pressure across all conditions, ranging from 11.2 ± 11.0% (30 hPa) to 62.0 ± 45.3% (250 hPa). Risk assessment based on a pressure–time cell death model revealed risk category changes in up to 66.7% of all conditions. Mean reductions in time to cell death ranged from 16 min (30 hPa) to 55 min (250 hPa), following a logarithmic relationship (adjusted R² = 0.984). These findings highlight ambient pressure variation as a previously unrecognized influencing factor on pressure ulcer risk in wheelchair users with air cell-based seat cushions. Full article

The objective of this feasibility study was to demonstrate and evaluate a remotely tongue-controlled wheelchair mounted assistive robotic manipulator (ARM), for the first time with end users: three individuals with cervical spinal cord injury. For three days, they remotely tongue-controlled the wheelchair and the ARM (WMARM) to complete two activities of daily living (ADL): Driving the wheelchair and ARM to a remote setting to (1) pick up a bottle and (2) pick up a ball. The participants controlled the system using full manual control by tongue and through semi-automation. Finally, the participants answered a NASA Task Load Index (TLX) questionnaire and a semi-structured interview. Results: All participants were able to remotely control the WMARM by tongue. Semi-automation resulted in shorter task completion time, gripping time and fewer commands as compared with manual control. Semi-automation decreased the measured mental load in the NASA TLX questionnaire by an average of 57%. The participants rated high satisfaction with the system. Conclusion: It was possible for the users with tetraplegia to control the wheelchair with the ARM using their tongue to perform ADL in Wi-Fi-based remote setting. This proposed system has the potential to increase independence and social interaction of individuals with tetraplegia. Full article

Background/Objectives: Wheelchair users with multiple sclerosis (MS) often face barriers that restrict participation in physical activity and exercise training. This manuscript reports on participant feedback to guide evaluating and refining a novel exercise training program, Seated Physical activity INtervention (SPIN). SPIN was adapted from the Guidelines for Exercise in MS (GEMS) approach using a three-step community-engaged research framework based on meeting the needs of wheelchair users with MS. Methods: Semi-structured interviews were conducted with 9 participants who completed the 16-week SPIN intervention. The key SPIN intervention components were the exercise prescription, exercise equipment, and behavioral coaching grounded in Social Cognitive Theory. Formative interview domains included overall experience, enjoyable and missing components, delivery modifications, barriers, lessons learned, and additional research topics of interest. Data were analyzed and reported using a rapid qualitative analysis approach. Results: Interviews averaged 16 ± 10 min. Participants reported enjoying SPIN, noting program strengths as being flexible and appropriate for individuals with MS, receiving coaching calls by knowledgeable staff that offered support and accountability, and receiving exercise equipment and video demonstrations. Participants also identified strategies for enhancing the program such as including peer support, offering real-time feedback during exercise, and adding other wellness behavior topics (e.g., diet). Conclusions: The results offer helpful ideas to consider when developing exercise training programs for wheelchair users with MS and other disabilities that may improve health and well-being. Full article

Background: This study examined the independent and combined associations of hand-grip strength (HGS) and arm muscle mass index with risk of non-alcoholic fatty liver disease (NAFLD) in individuals who use wheelchairs. Methods: Eighty-five individuals aged ≥ 30 years who use wheelchairs were enrolled as volunteers from sports welfare facilities for individuals with disabilities in “G” and “C” provinces. HGS was measured using a dynamometer, whereas the arm muscle mass index was assessed using a body composition analyzer. Risk of NAFLD was defined as a hepatic steatosis index (HSI) > 36 and Framingham steatosis index (FSI) ≥ 23. Results: The low-HGS group (HSI, odds ratio [OR] = 3.589, p = 0.013; FSI, OR = 2.710, p = 0.031) had a significantly higher NAFLD risk compared to the high-HGS group (reference, OR = 1). The low-arm-muscle-mass-index group showed a higher risk of NAFLD (HSI, OR = 2.762, p = 0.043; FSI, OR = 3.493, p = 0.007) compared to the high-arm-muscle-mass-index group (reference, OR = 1). Combining the low-HGS + low-arm-muscle-mass-index group (HSI, OR = 6.849, p = 0.006; FSI, OR = 6.957, p = 0.002) showed a significantly higher risk of NAFLD compared to the high-HGS + high-arm-muscle-mass-index group (reference, OR = 1), even after adjusting for covariates (HSI, OR = 7.352, p = 0.006; FSI, OR = 7.406, p = 0.003). Conclusions: Low HGS and low arm muscle mass index are independently associated with a higher risk of NAFLD in individuals who use wheelchairs, with low HGS plus low arm muscle mass index further increasing this risk. Full article

Advanced sensor signal analysis is increasingly important for intelligent health management in human-centered environments, where continuous perception and real-time interpretation of motion-related signals are essential for safe and adaptive assistance. In this study, we propose a vision-based sensor signal analysis framework for automated ergonomic risk assessment of wheelchair users during cabinet interaction. The proposed framework integrates YOLOv11 for human detection, MHFormer for monocular 3D pose reconstruction, and a fuzzy logic-enhanced RULA model for continuous ergonomic risk quantification from video-derived motion signals. To support model development and evaluation, we constructed a dedicated wheelchair cabinet-operation dataset comprising 30 participants, including 14 experienced wheelchair users and 16 trained simulation participants, across five representative cabinet-operation scenarios. The raw dataset contained approximately 5 h of RGB video and about 150,000 original frames. To reduce redundancy caused by highly similar consecutive frames and to mitigate overfitting risk, representative frames were sampled from the continuous video sequences, resulting in 10,000 images for annotation and model development. Based on the proposed framework, raw visual sensor signals are transformed into temporally continuous kinematic representations and ergonomic risk scores, enabling non-contact and real-time health-state interpretation in assistive living environments. The proposed method achieved an average joint-angle estimation RMSE of 7.5°, representing an approximately 60% reduction compared with a Kinect v2-based motion capture baseline (18.6°), which is widely used for low-cost ergonomic evaluation. In benchmark evaluation, the proposed method achieved 84% risk-classification accuracy with a Cohen’s kappa of 0.66, outperforming representative baseline approaches. The results further indicated that low revolving-door and low-drawer operations were associated with higher and more sustained ergonomic risk exposure than sliding-door interaction. These findings demonstrate that vision-based sensor signal analysis can provide an effective solution for intelligent health management, ergonomic monitoring, and perception-driven assessment in accessible and assistive autonomous living systems. Full article

Wheelchair users face significant mobility limitations related to both medical issues (e.g., musculoskeletal strain, pressure ulcers) and urban accessibility challenges. This pilot study introduces a sensor system integrating an inertial measurement unit (IMU), GPS (Global Positioning System), and a pressure-measuring seat to monitor distance travelled, speed, and posture in relation to real-world conditions. Seven participants navigated an approximately 800-metre outdoor course, divided into 13 sections, while real-time data were recorded. The results showed an average speed of 1.24 ± 0.41 m/s with peak speeds of up to 2.67 m/s. The centre of pressure on the seat fluctuated by an average of 25 mm in the x and y directions (left-right: COPx, back-forward: COPy). The data for average speed, COPx, and COPy showed significant differences between most of the 13 sections, with large, very large, and huge effect sizes. Comparing the speed, COPx, and COPy data with respect to distance travelled, and correlating them between the seven participants by applying the rank-sum method to the mean R² and calculating Kendall’s W, revealed that speed, COPx, and COPy were influenced by course conditions (R² medians between 0.013 and 0.499; W = 0.7857, strong agreement; χ²p = 0.0281). Small R² values indicate more individualised participant behaviour, while large R² values highlight the stronger influence of course conditions on the parameters. This non-invasive and cost-effective system provides objective motion data that can be used for future research in wheelchair design and rehabilitation strategies. Despite its advantages, this study was limited to able-bodied participants, so further clinical trials with individuals with mobility impairments are needed. Full article

Brain–computer interfaces (BCIs) are essential in assistive technologies to restore mobility in individuals with motor impairments. Although electroencephalography (EEG)-based brain-controlled wheelchairs have been extensively studied, most tongue-controlled systems rely on physical tongue movements, intraoral devices, or limited offline commands, which reduces the usability and comfort. This study introduces an EEG-based tongue motor imagery (MI) BCI for intuitive and entirely mental wheelchair control. By leveraging preserved motor function and the cortical representation of the tongue, the system enables natural four-directional control through imagined tongue movements. Six imagined tongue actions—touching the left and right mouth corners, the upper and lower lips, and producing left and right cheek bulges—were designed to elicit alpha-band event-related desynchronization (ERD) patterns over the tongue motor cortex. EEG data were collected from 15 healthy participants using a 14-channel consumer-grade EMOTIV EPOC X headset. Alpha-band ERD features were extracted and classified using linear discriminant analysis, support vector machine, naïve Bayes, and artificial neural networks (ANNs). Simpler command sets yielded the highest accuracy: two-class tasks achieved 76.19%, while the performance decreased with increasing task complexity. The ANN achieved superior results in multi-class scenarios. The proposed tongue MI method offers initial support for developing a BCI control strategy for assistive technology; however, further improvements in classification techniques, user training, and real-time validation are needed to improve the robustness and practical usability. Full article

The development of Smart Tourism often overlooks the “Wilderness Last Mile”, leading to the spatial exclusion of people with disabilities in mountain areas. This problem exists because standard tourist maps and urban-centric accessibility models rely on averaged terrain data, failing to identify critical micro-scale barriers (e.g., short, sudden steep ascents) that pose severe safety and traction risks for off-road wheelchair users. To address this gap, this article presents a novel GIS methodology for planning accessible off-road tourism for electric Specialized Off-Road Wheelchairs. The proposed four-stage analytical model includes (1) graph-based trail network topologization to enable precise routing; (2) traction safety verification utilizing high-resolution (1 × 1 m) Digital Elevation Model (DEM) micro-segmentation to detect hidden slope barriers; (3) multi-criteria evaluation combining a user-calibrated Difficulty Index (EDI) and a Tourism Quality Index (TQI); and (4) a hub optimization algorithm that prioritizes locations maximizing the diversity of accessible routes. The method was empirically tested in a case study of the Bieszczady Mountains (Poland), calibrating the model with the technical limits (25% max slope) of a prototype wheelchair. The experimental results clearly validate the model’s superiority over traditional approaches: the micro-segmentation successfully identified hidden terrain traps, disqualifying 55% of the standard trail network that would have otherwise been deemed safe by average-slope assessments. Furthermore, the model identified a contiguous safe network of 153 km and pinpointed the optimal rental hub location, ensuring the highest inclusivity and route variety. Ultimately, this approach transforms raw spatial data into safe, ready-made tourism products, providing a precise tool with which to implement Universal Design in natural environments. Full article

Upper extremity (UE) pain and pathology are prevalent among manual wheelchair users (MWUs) due to repetitive loading demands, highlighting the need for tools to identify high-risk tasks and inform injury prevention. This study investigated the feasibility of classifying activity intensity for wheelchair-related tasks using wearable sensors and supervised machine learning. Twenty-four MWUs with chronic spinal cord injury completed a standardized mobility course and simulated activities of daily living while UE electromyography (EMG) and inertial measurement unit (IMU) data were collected. Signals segmented into 3, 5, and 10 s windows, and time- and frequency-domain features were extracted and labeled as low, moderate, or high intensity. Multiple classification algorithms were evaluated using subject-dependent and subject-independent cross-validation, and dimensionality reduction was explored to assess class separability. Subject-dependent analyses demonstrated performance above chance but below 75% accuracy, with decision tree models demonstrating superior performance, particularly when trained on data segmented into 5 s windows. IMU features outperformed EMG features, but combining signal types enhanced performance. Subject-independent analyses revealed similar overall accuracy across signal types, but decreased high-intensity classification for EMG data, indicating subject dependency. Findings support the potential of wearable sensor-based machine learning with population-specific findings for activity intensity classification in MWUs, while highlighting challenges related to inter-subject variability for injury risk prediction. Full article

This study proposes an exploratory framework for identifying stress locations during travel with low-speed mobility devices (LMDs), such as electric wheelchairs. In this framework, stress factors perceived during LMD travel were identified through a post-ride questionnaire, and the travel route was divided into 100 m segments to enable location-specific stress evaluation. The identified factors were quantified using environmental data to construct an environment-based stress estimation index. Based on these quantified factors, a Composite Stress Score (CSS) was calculated to estimate stress levels along the route. Experiments with healthy adult participants were conducted to examine the feasibility of the proposed method. The results identified poor road surface conditions and vibrations, encounters with other road users, and narrow sidewalks as key stress factors during LMD travel. To examine whether the proposed method captures stress-related responses, correlations between CSS-based stress estimates and heart rate variability (HRV) indices were analyzed. The results showed that CSS calculated from poor road surface/vibrations, encounters with other road users, and narrow sidewalks exhibited moderate negative correlations with SDNN, suggesting that higher CSS values may correspond to increased physiological stress responses. These findings provide preliminary support for the exploratory feasibility of estimating potential stress locations during LMD travel using environmental data. However, the generalizability of the results is limited due to the specific experimental route and the use of healthy adult participants. Full article