JMIR Rehabilitation and Assistive Technologies最新文献

Background: In recent years, there has been an increasing demand for markerless motion capture systems, which are being widely used in biomechanical and clinical research. Furthermore, by using a markerless motion capture system in a laboratory environment that mimics living spaces, the data acquired on various activities of daily living, such as level walking, ramp walking, and stair ascent and descent, should more closely resemble that of real-life activities. However, the absolute reliability of gait parameters in this context is still unclear.

Objective: The aim of this study was to evaluate the reliability of a markerless motion capture system in assessing the ascent and descent of ramps and stairs during walking in a simulated living space.

Methods: A total of 21 healthy participants performed level walking, ramp and stair ascent and descent on two separate days, with at least a 24-hour interval between sessions. Joint angles were measured using 27 synchronized cameras with a markerless motion capture application, Theia3D (Theia Markerless Inc), and analyzed in Visual3d for all planes of motion at the hip-, knee-, and ankle-joints. The absolute reliability of day-to-day reproducibility was assessed using full-curve analysis (root mean square difference [RMSD]) and discrete point analysis of gait events using the standard error of measurement (SEM). SEM was calculated only for level walking and ramp ascent and descent, where gait events were correctly detected.

Results: The SEM values for level walking and ramp ascent and descent were all below the 5-degree threshold. However, while RMSD values were generally below 5°, this threshold was exceeded for knee-joint flexion-extension angles during ramp ascent and stair ascent (5.07° and 5.64°, respectively).

Conclusions: The markerless motion capture system in the living laboratory setting demonstrated a high degree of accuracy for various environments and gait types. The low SEM values obtained indicate good reliability for joint angle measurements across different days. The slightly higher RMSD values for knee-joint angles during ramp and stair ascent may reflect the system's ability to capture the adaptations in joint kinematics in response to changes in gait conditions. These measurements in a living laboratory environment validated the absolute reliability of various gait parameters not only in level walking but also in ramp and stair ascent and descent. The findings suggest potential clinical applications and research opportunities, including the development of assistive devices and robots, using markerless motion capture in more natural living situations, rather than in controlled environments.

Background: Knee osteoarthritis (KOA) requires long-term treatment that faces significant barriers, including inadequate physiotherapy services, especially in Slovenia and comparable European countries. Mobile health apps offer a promising solution to improve accessibility and adherence to KOA treatment.

Objectives: This study aimed to identify expectations of patients with KOA for app-based therapy, determine the functional requirements, and assess the main barriers and benefits of using mobile apps for KOA management. It also examined these factors about demographic data (gender, age, and education level) and motivation to perform knee exercises.

Methods: A mixed methods approach was used, integrating quantitative data from a structured questionnaire and qualitative data from in-depth interviews. The purposive sample comprised 82 patients with symptomatic KOA graded 1-3 on the Kellgren-Lawrence scale, excluding those with cognitive impairments, wheelchair dependency, significant comorbidities, or language barriers.

Results: The analysis revealed that 53.7% (44/82) of patients preferred smartphones, while 40.2% (33/82) favored PCs for remote KOA management, citing accessibility and convenience. Exercise videos received the highest rating (µ=9.45), followed by goal setting and tracking (µ=8.95) and regular e-messages (µ=8.83). Telephone consultations with physiotherapists were also highly valued (µ=8.41). Significant differences were observed in the perceived importance of key disease information (F9=2.077; P=.04) and exercise videos (F9=2.788; P=.05) based on motivation levels but not by gender, age, or education. Perceptions of the appropriate duration of physical activity varied with motivation levels (F9=2.490; P=.02) but not with demographic factors. Men rated ease of use (4.93 vs 4.71; F1=3.961; P=.05) and the clarity of the exercise flow display higher than women. The most significant barrier was inaccurate disease information (µ=3.96), with notable differences across age groups. Younger participants (younger than 40 years) and those aged 51-60 years expressed concerns about time management and information accuracy. Patients highlighted the ability to rewatch exercises as a key app feature, while time efficiency and improved access to physiotherapists were highly valued for convenience. Enhanced communication and accurate information were essential for building trust and ensuring effective treatment.

Conclusions: Mobile health apps for KOA management should be designed with a user-centered approach, prioritizing accessibility, motivation, and effective communication. Key functionalities include high-quality exercise videos, goal setting, symptom tracking, and regular electronic reminders. Mitigating user-reported barriers and integrating age-specific adaptations can enhance adherence and therapeutic outcomes. The findings highlig

Background: In 2023, the National Clinical Guidelines for Stroke revised the recommended daily multidisciplinary therapy dose from 45 minutes per therapy to 3 hours of therapy overall. To monitor the achievement of these guidelines, there is a need for accurate measurement. This study introduces a novel co-designed digital dosage tracking system that uses Near Field Communication technology to log rehabilitation activities and demonstrates its feasibility and accuracy in a clinical setting through comparison with the current clinical method of manual recording.

Objective: This study aimed to assess the validity, feasibility, and usability of a novel co-designed digital tracker using Near Field Communication technology to automatically log rehabilitation dosage in people with stroke history, providing an objective and low-burden solution for clinical environments.

Methods: This pilot mixed methods study included 2 phases. Phase 1 involved a usability trial with 9 participants conducted at a university research center, assessing usability with the System Usability Scale (SUS) and Intrinsic Motivation Inventory (IMI). Phase 2 consisted of a clinical trial in a National Health Service stroke ward with 15 inpatients, comparing the digital tracker with manual therapist recordings for validity and feasibility using paired t tests, Cohen d, and Bland-Altman plots. An acceptable discrepancy range was set at ±5%-10%.

Results: The digital tracker demonstrated high usability with a mean SUS score of 91.43 (SD 9.53) and strong user satisfaction (IMI score 6.29/7, SD 1.50). Clinical trial results showed a strong agreement between the digital and manual methods (t206=-1.60; P=.11; Cohen d=-0.06), with a small mean time discrepancy of 1.23 (SD 11.01) minutes across 207 activities. The Bland-Altman plot indicated good accuracy and consistency between methods, with limits of agreement within the clinically acceptable range.

Conclusions: The co-designed digital tracker has been shown to agree with a manual method for recording rehabilitation dosage. This development presents the opportunity for objective, automated, and low-burden recording of rehabilitation dose to support prescription, monitoring, and research.

Background: Chronic musculoskeletal pain (CMP) impacts around 20% of people globally, resulting in patients living with pain, fatigue, restricted social and employment capacity, and reduced quality of life. Interdisciplinary multimodal pain treatment (IMPT) programs have been shown to provide positive and sustained outcomes where all other interventions have failed. IMPT programs combined with multidimensional machine learning predictive patient profiles aim to improve clinical decision support and personalized patient assessments, potentially leading to better treatment outcomes.

Objective: We aimed to investigate integrating machine learning with IMPT programs and its potential contribution to clinical decision support and treatment outcomes for patients with CMP.

Methods: This prospective pilot study used a machine learning prognostic patient profile of 7 outcome measures across 4 clinically relevant domains, including activity or disability, pain, fatigue, and quality of life. Prognostic profiles were created for new IMPT patients in the Netherlands in November 2023 (N=17). New summary indicators were developed, including defined categories for positive, negative, and mixed prognostic profiles; an accuracy indicator with high, medium, and low levels based on weighted true- or false-positive values; and an indicator for consistently positive or negative outcomes. The consolidated reporting guidelines checklist for prognostic machine learning modeling studies was completed to provide transparency of data quality, model development methodology, and validation.

Results: The machine learning IMPT prognostic patient profiles demonstrated high accuracy and consistency in predicting patient outcomes. The profile, combined with extended new prognostic summary indicators, provided improved identification of patients with predicted positive, negative, and mixed outcomes, supporting more comprehensive assessment. Overall, 82.4% (14/17) of prognostic patient profiles were consistent with clinician assessments. Notably, clinician case notes indicated the stratified prognostic profiles were directly discussed with around half (8/17, 47.1%) of patients. Clinicians found the prognostic patient profiles helpful in 88.2% (15/17) of initial IMPT assessments to support shared clinician and patient decision-making and discussion of individualized treatment planning.

Conclusions: Machine learning prognostic patient profiles showed promising contributions for IMPT clinical decision support and improving treatment outcomes for patients with CMP. Further research is needed to validate these findings in larger, more diverse populations.

Background: The number of patients undergoing open-heart surgery (OHS) is persistently increasing. Additionally, postoperative pulmonary complications have been reported after OHS, and an incentive spirometer has been suggested to prevent postoperative pulmonary complications. However, no commercial incentive spirometer provides the precise inhalation volume. We developed a digital incentive spirometer (DIS) that displays the relevant data.

Objective: In this study, we aimed to explore the beneficial effects of a DIS on respiratory function in patients who underwent OHS.

Methods: A randomized controlled trial was designed with 32 patients scheduled for OHS: 16 individuals each were assigned to the DIS and the flow-oriented incentive spirometer (ie, Triflow incentive spirometer) groups, respectively. The patients were requested to use the DIS and Triflow incentive spirometer 15 times/set, two sets/day, from day 1 to 5 postextubation. All participants underwent lung function and respiratory muscle strength assessments prior to OHS and on day 5 postextubation postoperatively. For comparison between and within the groups, we performed an intention-to-treat analysis with a two-way mixed analysis of variance.

Results: In both the DIS and Triflow incentive spirometer groups, pulmonary function parameters and maximal respiratory pressure were markedly reduced on day 5 postextubation when compared with those prior to OHS (P<.05). There were no significant differences in pulmonary function or respiratory muscle strength between the two groups (P>.05).

Conclusions: Pulmonary function and respiratory muscle strength did not differ significantly between the DIS and Triflow incentive spirometer groups among patients who underwent OHS.

Background: Stroke often leads to long-term effects on daily activities and participation. Consequences impact not only stroke survivors but also their close networks, and capturing their experiences is crucial for the development of effective interventions. F@ce 2.0 is a person-centered, information and communication technology (ICT)-supported stroke rehabilitation intervention currently being evaluated.

Objective: This study aims to describe family members' experiences of the F@ce 2.0 intervention from the perspective of being a caregiver to a stroke survivor.

Methods: Participants were family members (n=7) of stroke survivors participating in the intervention. Semistructured interviews were conducted at 2 time points, postintervention and 6 months postbaseline, resulting in a total of 13 interviews. Data was analyzed using qualitative inductive content analysis.

Results: An overarching theme was developed from 4 categories. The main theme was the potential of F@ce 2.0 as a support for family members of stroke survivors in the sudden change of life. The categories were: dialogue and partnership with the F@ce 2.0 team, resuming daily activities lowers the demand for family support, support and involvement through the ICT component of F@ce 2.0, and engagement in F@ce 2.0, leading to suggestions for development.

Conclusions: This study aligns with previous research delineating the effects of stroke on family members of stroke survivors. Participants highlighted the positive impact of the focus on daily activities within the intervention. Furthermore, the ICT component was perceived as a support in structuring rehabilitation. Participants, however, suggested further development, both in terms of content and technology.

During the COVID-19 pandemic, telerehabilitation was critical to providing ongoing care for people with impairments or disabilities, and it remains frequently used and popular after the pandemic. Telerehabilitation has been shown to be feasible and effective in a variety of conditions, including chronic heart failure and coronary artery disease, stroke, multiple sclerosis, and spinal cord injuries, with adverse events being rare. This editorial identifies important areas and future directions for the field, including implementation considerations in the postpandemic context, issues of access and equity, and emerging innovations and personalized care. The development and implementation of this knowledge will ensure that individuals with disabilities and impairments will continue to receive effective, safe, and person-driven care remotely.

Background: Wheelchairs are assistive mobility devices known to experience frequent part failures and breakdowns within 6 months of regular use. No tools or technologies exist to monitor the wheelchairs' condition or usage and inform stakeholders and users regarding when or how often they need to undergo servicing to avoid critical part failure.

Objective: We aimed to test the association between wheelchair usage and manual wheelchair damage, part failures, and consequences for older wheelchair users and evaluate their preferences for a new wheelchair servicing technology.

Methods: A cross-sectional study was performed with older manual wheelchair users atInstituto Nacional de Geriatría in Mexico. Demographic data, wheelchair information, failure counts, and preferences for new technology (sensor and smartphone app for servicing) were collected using surveys. Road shocks experienced by the wheelchair were collected for a week using a sensor.

Results: Ten participants (mean [SD] age, 78.8 [11.8] y; 8 female and 2 male) participated. Seven experienced an average (SD) of 2.86 (1.36) self-reported part failures. Road shocks correlated with self-reported loose brake failures (r(8)=0.58, P=.09), the damaged condition of tires (r(8)=0.61, P=.1), and the damaged condition of brakes (r(8)=0.58, P=.099). No consequences were reported. Part failures increased as self-maintenance occurrences increased (r(9)=0.67, P=.04). More than 8 participants responded that they would like to monitor the wheelchair's condition using the new technology and purchase it at an average (SD) price of US $28.95 (18.13).

Conclusions: In this study, the association between wheelchair usage and failures showed that data-driven wheelchair inspection schedules should be determined through a collaborative approach involving researchers and stakeholders in wheelchair repair provision and older adult users. Older adults are interested in using new technology to engage in wheelchair servicing.