Search Results (163)

Background: Self-report physical activity (PA) scales, accelerometry, and heart rate (HR) monitoring are reliable tools for PA measurement for children with cerebral palsy (CP); however, there are limitations for those who are primary wheelchair users. The purpose of our study was to evaluate face and construct validity of the PROMIS^® Pediatric PA parent proxy short form 8a in measuring PA amount and intensity in children with CP who are non-ambulatory. Methods: Face validity: Semi-structured interviews with parents and pediatric physical therapists (PTs) were conducted about the appropriateness of each item on the PROMIS^® Pediatric PA short form. Construct validity: Children with CP who were non-ambulatory participated in a one-week observational study. PA amount and intensity were examined using PA monitors (Actigraph GT9X) and HR monitors (Fitbit Charge 4). Activity counts and time in sedentary and non-sedentary intensity zones were derived and compared to the PROMIS^® T-scaled score. Results: Twenty-two physical therapists (PTs) and fifteen parents participated in the interviews, and ten children completed 1-week PA observation. Eight and seven participants completed sufficient time of uninterrupted PA and HR monitor wear, respectively. Parents and PTs agreed that several questions were not appropriate for children with CP who were non-ambulatory. PA intensity via activity counts derived from wrist worn monitors showed a strong positive correlation with the PROMIS^® PA measure. Conclusions: Construct validity in our small sample was established between PROMIS^® scores and accelerometry activity counts when documenting PA amount and intensity; however, there were some differences on PROMIS^® face validity per parent and PT respondents. Despite some concerns regarding face validity, the PROMIS^® Pediatric PA parent proxy short form 8a shows promise as a valid measure of physical activity amount and intensity in non-ambulatory children with CP, warranting further investigation and refinement. Full article

Manual wheelchair users are at high risk of upper limb overuse injuries due to repetitive propulsion mechanics. To address this, we developed a novel detachable push–pull dual-propulsion device that enables both forward and backward propulsion, aiming to reduce shoulder strain and promote balanced muscle engagement. This study presents a protocol to evaluate the device’s biomechanical impact and ergonomic effects, focusing on objective, quantitative analysis using a repeated-measures within-subject design. Thirty participants with spinal cord injury will perform standardized propulsion trials under two conditions: push and pull. Motion capture and surface electromyography (EMG) will assess upper limb kinematics and muscle activation. Each propulsion mode will be repeated over a 10-m track, and maximum voluntary contraction (MVC) data will be collected for EMG normalization. The protocol aims to provide objective evidence on the propulsion efficiency, muscle distribution, and ergonomic safety of the device. Findings will inform future assistive technology development and rehabilitation guidelines for manual wheelchair users. Full article

Background/Objectives: Children at Gross Motor Function Classification System (GMFCS) levels IV and V experience severe motor impairments, yet the effects of passive wheelchair rides on their physiological parameters remain unexplored. This study aimed to examine the acute physiological response to passive bike in non-ambulant children with physical disabilities. Methods: This quasi-experimental study included 24 non-ambulant participants with cognitive impairments (6–21 years old, 50% female). After a 10-min rest, participants underwent a 10-min passive wheelchair bike. Muscle activity, oxygen consumption, and heart rate variability were assessed. Results: Passive bike rides significantly increased muscle activity in the right upper (p = 0.050), left upper (p = 0.008), and left lower trapezius (p = 0.038), with increases of 97–112%. However, no significant changes were observed in oxygen consumption or cardiorespiratory parameters. Conclusions: This study suggests that passive wheelchair bike rides increase trapezius muscle activity in children with severe disabilities at GMFCS levels IV and V, offering potential benefits for this population. Full article

Background: Individuals with neuromuscular diseases (NMDs) have low physical activity levels and an increased risk of cardiovascular and pulmonary diseases. Respiratory gas kinetics obtained during cardiopulmonary exercise testing (CPET) may provide valuable insights into disease mechanisms and cardiorespiratory fitness in individuals with NMD. Recovery from exercise is an important marker of exercise performance and overall physical health, and impaired recovery is strongly associated with poor health outcomes. This study evaluates recovery metrics in individuals with NMD after performing maximal exertion during CPET. Methods: A total of 34 individuals with NMD and 15 healthy volunteers were recruited for the study. CPET was performed using a wearable metabolic system and a wheelchair-accessible total body trainer to peak exertion. Recovery metrics assessed were (i) the time to reach 50% O₂ recovery compared with peak exercise and (ii) the ratios of ventilation and respiratory gases between peak exercise and the highest values observed during recovery (overshoot). Results: The NMD group had a significantly longer time to reach 50% O₂ recovery (T1/2 VO₂: 105 ± 43.4 vs. 76 ± 36.4 s, p = 0.02), lower respiratory overshoot (17.1 ± 13.0% vs. 28.8 ± 9.03%), and lower ventilation/VO₂ (31.9 ± 28.3 vs. 52.2 ± 23.5) compared to the control group. Conclusions: This study observes significantly impaired recovery metrics following peak exercise in individuals with NMD compared to controls. These insights may improve the understanding of exercise recovery and mechanics, thus improving prognostication and optimizing exercise prescriptions for individuals with NMD. Full article

Background: Assessment of physical competencies is one way to enhance uptake and maintain participation in a leisure-time physical activity (LTPA) for manual wheelchair (MWC) users. Weineck’s model explains physical competencies through eight physical qualities. The use of this model may influence MWC users’ motivation for participation in LTPA. The aim of this study was to identify and categorize existing assessment tools designed for MWC users of physical qualities (strength, speed, power, muscular endurance, cardiovascular endurance, balance, and flexibility). Methods: A mapping review was conducted following the “Preferred reporting items for systematic reviews and meta-analyses (PRISMA)” guidelines. Two reviewers selected articles that documented assessment tools for the physical qualities of MWC users. Tools were extracted from each article to categorize them in a list. Results: A total of 149 articles that contained assessments of physical qualities were included in the review. A total of 97 assessment tools were extracted and categorized according to the eight physical qualities. Conclusions: These assessments are categorized into physical qualities that would facilitate the creation of test batteries aimed at assessing physical qualities in MWC users. This study is the first step in the construction of a test battery to assess the physical qualities of MWC users. Full article

Human–machine interface (HMI) systems are increasingly utilized to develop assistive technologies for individuals with disabilities and older adults. This study proposes two HMI systems using piezoelectric sensors to detect facial muscle activations from eye and tongue movements, and accelerometers to monitor head movements. This system enables hands-free wheelchair control for those with physical disabilities and speech impairments. A prototype wearable sensing device was also designed and implemented. Four commands can be generated using each sensor to steer the wheelchair. We conducted tests in offline and real-time scenarios to assess efficiency and usability among older volunteers. The head–machine interface achieved greater efficiency than the face–machine interface. The simulated wheelchair control tests showed that the head–machine interface typically required twice the time of joystick control, whereas the face–machine interface took approximately four times longer. Participants noted that the head-mounted wearable device was flexible and comfortable. Both modalities can be used for wheelchair control, especially the head–machine interface for patients retaining head movement. In severe cases, the face–machine interface can be used. Moreover, hybrid control can be employed to satisfy specific requirements. Compared to current commercial devices, the proposed HMIs provide lower costs, easier fabrication, and greater adaptability for real-world applications. We will further verify and improve the proposed devices for controlling a powered wheelchair, ensuring practical usability for people with paralysis and speech impairments. Full article

Background/Objectives: The study explores the integration of human feedback into the control loop of mobile robots for real-time obstacle detection and avoidance using EEG brain–computer interface (BCI) methods. The goal is to assess the possible paradigms applicable to the most current navigation system to enhance safety and interaction between humans and robots. Methods: The research explores passive and active brain–computer interface (BCI) technologies to enhance a wheelchair-mobile robot’s navigation. In the passive approach, error-related potentials (ErrPs), neural signals triggered when users comment or perceive errors, enable automatic correction of the robot navigation mistakes without direct input or command from the user. In contrast, the active approach leverages steady-state visually evoked potentials (SSVEPs), where users focus on flickering stimuli to control the robot’s movements directly. This study evaluates both paradigms to determine the most effective method for integrating human feedback into assistive robotic navigation. This study involves experimental setups where participants control a robot through a simulated environment, and their brain signals are recorded and analyzed to measure the system’s responsiveness and the user’s mental workload. Results: The results show that a passive BCI requires lower mental effort but suffers from lower engagement, with a classification accuracy of 72.9%, whereas an active BCI demands more cognitive effort but achieves 84.9% accuracy. Despite this, task achievement accuracy is higher in the passive method (e.g., 71% vs. 43% for subject S2) as a single correct ErrP classification enables autonomous obstacle avoidance, whereas SSVEP requires multiple accurate commands. Conclusions: This research highlights the trade-offs between accuracy, mental load, and engagement in BCI-based robot control. The findings support the development of more intuitive assistive robotics, particularly for disabled and elderly users. Full article

Background/Objectives: Physical activity is recommended for people with physical disabilities and is beneficial not only for physical health but also for mental health. This study aimed to evaluate the quality of life (QoL), pulmonary health, and cardiovascular health among a group of older men with physical disabilities who participated in an exercise program. Methods: This study included 23 participants in the exercise group (EG) as an experimental group and 23 in the culture group (CG) as a control group. All participants were ≥65 years, with one or more physical disabilities, and used wheelchairs or crutches for mobility. The participants were each provided with the exercise program for 8 weeks. Assessments included a QoL, pulmonary function test, brachial–ankle pulse wave velocity (baPWV), and factors of metabolic syndrome. The exercise program consisted of aerobics, strength training using dumbbells and tubes, and mat exercises for three days a week for 8 weeks. The culture program included singing, drawing, and writing. Results: The interaction effects by time and group showed that EG had a superior change compared to CG in QoL (physical function, pain, fatigue, social), forced vital capacity, baPWV, triglycerides, and high-density lipoprotein cholesterol (p < 0.05). Conclusions: Participation in the exercise program positively influenced mental, pulmonary, and cardiovascular health in older men with physical disabilities. Our research results will provide useful information for rehabilitation and social security research to improve the health of elderly people with physical disabilities. Full article

This study examines how the use of postural and mobility devices evolves in home environments for children with GMFCS IV cerebral palsy, focusing on parents’ perspectives on benefits, outcomes, and challenges. As children grow, changes in muscle strength, motor function, and daily activity demands necessitate adjustments in assistive devices to maintain mobility and postural support. Data from 10 parents, collected through descriptive statistics and qualitative interviews, covered device types, usage patterns, and family impacts across developmental stages from preschool to adulthood. Device needs shift significantly with growth, transitioning from early gait trainers and postural support devices to advanced mobility devices, such as power wheelchairs, which become essential in adulthood. Parents reported positive outcomes, including improved emotional well-being, social participation, and independent mobility, alongside reduced caregiving burdens. However, challenges persist, including financial constraints, frequent device replacements, and limited training for users and caregivers. These insights highlight the need for more adaptable device designs and enhanced family-centered support programs to better assist caregivers in managing device transitions. This study addresses a gap by exploring the real-world outcomes of home-based device use, providing data and parental insights to inform device design, clinical practices, and family-centered support programs. Future research should focus on enhancing device functionality, customization, and accessibility to improve quality of life and promote greater independence for individuals with cerebral palsy. Full article

Electric wheelchairs are the primary means of transportation that enable individuals with disabilities to move independently to their desired locations. This paper introduces a novel, low-cost smart wheelchair system designed to enhance the mobility of individuals with severe disabilities through hand gesture recognition. Additionally, the system aims to support low-income individuals who previously lacked access to smart wheelchairs. Unlike existing methods that rely on expensive hardware or complex systems, the proposed system utilizes an affordable webcam and an Nvidia Jetson Nano embedded computer to process and recognize six distinct hand gestures—“Forward 1”, “Forward 2”, “Backward”, “Left”, “Right”, and “Stop”—to assist with wheelchair navigation. The system employs the “You Only Look Once version 8n” (YOLOv8n) model, which is well suited for low-spec embedded computers, trained on a self-collected hand gesture dataset containing 12,000 images. The pre-processing phase utilizes the MediaPipe library to generate landmark hand images, remove the background, and then extract the region of interest (ROI) of the hand gestures, significantly improving gesture recognition accuracy compared to previous methods that relied solely on hand images. Experimental results demonstrate impressive performance, achieving 99.3% gesture recognition accuracy and 93.8% overall movement accuracy in diverse indoor and outdoor environments. Furthermore, this paper presents a control circuit system that can be easily installed on any existing electric wheelchair. This approach offers a cost-effective, real-time solution that enhances the autonomy of individuals with severe disabilities in daily activities, laying the foundation for the development of affordable smart wheelchairs. Full article

Background. Sports for people with disabilities were developed to be the final stage and continuation of rehabilitation, and their main purpose was for therapeutic value. The purpose of this study was to assess the physical activity and selected health behaviors of people with disabilities involved in wheelchair fencing. Materials and Methods. The study included 89 people with disabilities. The first group (n = 42) consisted of parafencers participating in the Kiliński’s Sabre Wheelchair Fencing World Cup. The control group was 47 people with disabilities who were non-athletes. The main research tools were the Health Behaviors Inventory (HBI) and the International Physical Activity Questionnaire (IPAQ). Results. The athletes’ health behaviors, assessed using the HBI, showed significant differences between the two study groups. Wheelchair fencers were more attentive to eating habits, preventive behaviors, and health practices and had more favorable mental attitudes. In the fencers’ overall physical activity over the past seven days, differences were observed between those who trained competitively and non-athletes. The differences were statistically significant. Conclusions. Fencers were characterized by significantly higher levels of health behavior. This may indicate the intellectualization of the training process and the transfer of the desired behavior to everyday life. Full article

As society develops, the aging population issue is becoming more serious and gaining global attention. Meanwhile, the building industry worldwide is focusing on making buildings more convenient for the elderly. This study focuses on a health care building, analyzing its aging-friendly design. It examines issues related to walking situations and activity spaces and proposes optimization strategies based on relevant codes and actual needs. Through optimization and transformation, the walking distance to the nearest exit for the elderly in the building has been reduced by 36.8%, the walking distance to activity space for the elderly has been reduced by 8.4%, and the average public activity space of each elderly person has been increased by about 23.5%. In addition, the handrails of the accessible stairway have been changed to double handrails, which is more suitable for the different needs of the elderly, and the space of the wheelchair-accessible elevator has been expanded, which is more convenient for the elderly’s activities in elevators. This paper explores the feasibility and design direction of the aging-friendly architecture, and it aims to provide a valuable reference for the renovation of aging buildings. Full article

With the aging of the population and the increase in the number of people with disabilities, intelligent wheelchairs are essential in improving travel autonomy and quality of life. In this paper, we propose an autonomous outdoor navigation framework for intelligent wheelchairs based on hierarchical cost maps to address the challenges of wheelchair navigation in complex and dynamic outdoor environments. First, the framework integrates multi-sensors such as RTK high-precision GPS, IMU, and 3D LIDAR; fuses RTK, IMU, and odometer data to realize high-precision positioning; and performs path planning and obstacle avoidance through dynamic hierarchical cost maps. Secondly, the drivable area layer is integrated into the traditional hierarchical cost map, in which the drivable area detection algorithm utilizes local plane fitting and elevation difference analysis to achieve efficient ground point cloud segmentation and real-time updating, which ensures the real-time safety of navigation. The experiments are validated in real outdoor scenes and simulation environments, and the results show that the speed of drivable region detection is about 30 ms, the positioning accuracy of wheelchair outdoor navigation is less than 10 cm, and the distance of active obstacle avoidance is 1 m. This study provides an effective solution for the autonomous navigation of the intelligent wheelchair in a complex outdoor environment, and it has a high robustness and application potential. Full article

Background: Appropriate wheelchair and seating systems are key to allow for the participation of people with Duchenne Muscular Dystrophy. There is little research that focuses on their long-term seating issues and what topics they want studied. Methods: This mixed-method study with adults with Duchenne used an Internet-based survey about wheelchair mobility and discomfort, followed by in-depth interviews. Unanticipated remarks in the interviews led to a second survey regarding the effects of cold weather on wheelchair driving. Descriptive and qualitative analyses were performed. Results: Thirty-seven individuals completed the original survey: 78% used a powered wheelchair, 58% were uncomfortable in their wheelchair, and 94% felt the need to change their seating position. In-depth interviews (N = 9) revealed three themes: seating and pain management, caregiver cooperation, and temperature sensitivity. Almost all (8/9) interviewees explained that cold was a barrier to their participation. In the second survey (N = 13), 11 reported that cold affected their driving, with 10 remarking that it prevented them from participating in daily life activities and 11 stating that the effects of cold on wheelchair driving should be studied. Conclusions: It is essential to ask end-users to identify key issues to ensure the relevance of research to people with disabilities. Full article

Electroencephalography (EEG) is a non-invasive technique with high temporal resolution and cost-effective, portable, and easy-to-use features. Motor imagery EEG (MI-EEG) data classification is one of the key applications within brain–computer interface (BCI) systems, utilizing EEG signals from motor imagery tasks. BCI is very useful for people with severe mobility issues like quadriplegics, spinal cord injury patients, stroke patients, etc., giving them the freedom to a certain extent to perform activities without the need for a caretaker, like driving a wheelchair. However, motion artifacts can significantly affect the quality of EEG recordings. The conventional EEG enhancement algorithms are effective in removing ocular and muscle artifacts for a stationary subject but not as effective when the subject is in motion, e.g., a wheelchair user. In this research study, we propose an empirical error model-based artifact removal approach for the cross-subject classification of motor imagery (MI) EEG data using a modified CNN-based deep learning algorithm, designed to assist wheelchair users with severe mobility issues. The classification method applies to real tasks with measured EEG data, focusing on accurately interpreting motor imagery signals for practical application. The empirical error model evolved from the inertial sensor-based acceleration data of the subject in motion, the weight of the wheelchair, the weight of the subject, and the surface friction of the terrain under the wheelchair. Three different wheelchairs and five different terrains, including road, brick, concrete, carpet, and marble, are used for artifact data recording. After evaluating and benchmarking the proposed CNN and empirical model, the classification accuracy achieved is 94.04% for distinguishing between four specific classes: left, right, front, and back. This accuracy demonstrates the model’s effectiveness compared to other state-of-the-art techniques. The comparative results show that the proposed approach is a potentially effective way to raise the decoding efficiency of motor imagery BCI. Full article