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Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement.

ABSTRACT: Persevering with home rehabilitation exercise is a struggle for millions of people in the US each year. A key factor that may influence motivation to engage with rehabilitation exercise is the challenge level of the assigned exercises, but this hypothesis is currently supported only by subjective, self-report. Here, we studied the relationship between challenge level and perseverance using long-term, self-determined exercise patterns of a large number of individuals (N = 2,581) engaging in home rehabilitation with a sensor-based exercise system without formal supervision. FitMi is comprised of two puck-like sensors and a library of 40 gamified exercises for the hands, arms, trunk, and legs that are designed for people recovering from a stroke. We found that individuals showed the greatest perseverance with the system over a 2-month period if they had (1) a moderate level of motor impairment and (2) high but not perfect success during the 1st week at completing the exercise game. Further, a steady usage pattern (vs. accelerating or decelerating use) was associated with more overall exercise, and declines in exercise amount over time were associated with exponentially declining session initiation probability rather than decreasing amounts of exercise once a session was initiated. These findings confirm that an optimized challenge level and regular initiation of exercise sessions predict achievement of a greater amount of overall rehabilitation exercise in a group of users of commercial home rehabilitation technology and suggest how home rehabilitation programs and exercise technologies can be optimized to promote perseverance.

SUBMITTER: Ramos Munoz EJ

PROVIDER: S-EPMC9252527 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTechnology is being increasingly investigated as an option to allow stroke survivors to exploit their full potential for recovery by facilitating home-based upper limb practice. This review seeks to explore the factors that influence perseverance with technology-facilitated home-based upper limb practice after stroke.MethodsA systematic mixed studies review with sequential exploratory synthesis was undertaken. Studies investigating adult stroke survivors with upper limb disability undertaking technology-facilitated home-based upper limb practice administered ≥ 3 times/week over a period of ≥ 4 weeks were included. Qualitative outcomes were stroke survivors' and family members' perceptions of their experience utilising technology to facilitate home-based upper limb practice. Quantitative outcomes were adherence and dropouts, as surrogate measures of perseverance. The Mixed Methods Appraisal Tool was used to assess quality of included studies.ResultsForty-two studies were included. Six studies were qualitative and of high quality; 28 studies were quantitative and eight were mixed methods studies, all moderate to low quality. A conceptual framework of perseverance with three stages was formed: (1) getting in the game; (2) sticking with it, and; (3) continuing or moving on. Conditions perceived to influence perseverance, and factors mediating these conditions were identified at each stage. Adherence with prescribed dose ranged from 13 to 140%. Participants were found to be less likely to adhere when prescribed sessions were more frequent (6-7 days/week) or of longer duration (≥ 12 weeks).ConclusionFrom the mixed methods findings, we propose a framework for perseverance with technology-facilitated home-based upper limb practice. The framework offers opportunities for clinicians and researchers to design strategies targeting factors that influence perseverance with practice, in both the clinical prescription of practice and technology design. To confirm the clinical utility of this framework, further research is required to explore perseverance and the factors influencing perseverance. Registration: PROSPERO CRD42017072799- https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=72799.

Project description:We are developing a system for long term Semi-Automated Rehabilitation At the Home (SARAH) that relies on low-cost and unobtrusive video-based sensing. We present a cyber-human methodology used by the SARAH system for automated assessment of upper extremity stroke rehabilitation at the home. We propose a hierarchical model for automatically segmenting stroke survivor's movements and generating training task performance assessment scores during rehabilitation. The hierarchical model fuses expert therapist knowledge-based approaches with data-driven techniques. The expert knowledge is more observable in the higher layers of the hierarchy (task and segment) and therefore more accessible to algorithms incorporating high level constraints relating to activity structure (i.e., type and order of segments per task). We utilize an HMM and a Decision Tree model to connect these high level priors to data driven analysis. The lower layers (RGB images and raw kinematics) need to be addressed primarily through data driven techniques. We use a transformer based architecture operating on low-level action features (tracking of individual body joints and objects) and a Multi-Stage Temporal Convolutional Network(MS-TCN) operating on raw RGB images. We develop a sequence combining these complimentary algorithms effectively, thus encoding the information from different layers of the movement hierarchy. Through this combination, we produce a robust segmentation and task assessment results on noisy, variable and limited data, which is characteristic of low cost video capture of rehabilitation at the home. Our proposed approach achieves 85% accuracy in per-frame labeling, 99% accuracy in segment classification and 93% accuracy in task completion assessment. Although the methodology proposed in this paper applies to upper extremity rehabilitation using the SARAH system, it can potentially be used, with minor alterations, to assist automation in many other movement rehabilitation contexts (i.e., lower extremity training for neurological accidents).

Project description:BackgroundConstraint-Induced Movement therapy (CI therapy) is shown to reduce disability, increase use of the more affected arm/hand, and promote brain plasticity for individuals with upper extremity hemiparesis post-stroke. Randomized controlled trials consistently demonstrate that CI therapy is superior to other rehabilitation paradigms, yet it is available to only a small minority of the estimated 1.2 million chronic stroke survivors with upper extremity disability. The current study aims to establish the comparative effectiveness of a novel, patient-centered approach to rehabilitation utilizing newly developed, inexpensive, and commercially available gaming technology to disseminate CI therapy to underserved individuals. Video game delivery of CI therapy will be compared against traditional clinic-based CI therapy and standard upper extremity rehabilitation. Additionally, individual factors that differentially influence response to one treatment versus another will be examined.MethodsThis protocol outlines a multi-site, randomized controlled trial with parallel group design. Two hundred twenty four adults with chronic hemiparesis post-stroke will be recruited at four sites. Participants are randomized to one of four study groups: (1) traditional clinic-based CI therapy, (2) therapist-as-consultant video game CI therapy, (3) therapist-as-consultant video game CI therapy with additional therapist contact via telerehabilitation/video consultation, and (4) standard upper extremity rehabilitation. After 6-month follow-up, individuals assigned to the standard upper extremity rehabilitation condition crossover to stand-alone video game CI therapy preceded by a therapist consultation. All interventions are delivered over a period of three weeks. Primary outcome measures include motor improvement as measured by the Wolf Motor Function Test (WMFT), quality of arm use for daily activities as measured by Motor Activity Log (MAL), and quality of life as measured by the Quality of Life in Neurological Disorders (NeuroQOL).DiscussionThis multi-site RCT is designed to determine comparative effectiveness of in-home technology-based delivery of CI therapy versus standard upper extremity rehabilitation and in-clinic CI therapy. The study design also enables evaluation of the effect of therapist contact time on treatment outcomes within a therapist-as-consultant model of gaming and technology-based rehabilitation.Trial registrationClinicaltrials.gov, NCT02631850 .

Project description:BackgroundDespite the proven benefits of exercise rehabilitation for numerous health conditions, musculoskeletal injuries and recovery from surgery, patient adherence to such programs is reported to often be less than 35%. Increasing patient engagement therefore has the potential to improve patient health outcomes, benefiting the patient, their carers and the services that support them. The aims of this review were to identify the factors that contribute to 'patient' engagement in prescribed exercise rehabilitation using the COM-B (capability, opportunity, motivation-behaviour) framework of behavioural analysis.MethodsFive electronic databases (PubMed, Embase, Cochrane, Web of Science, and ClinicalTrials.gov) were searched. 'COM-B' was the key word searched for specifically within titles and abstracts, combined with either 'physical activity' OR 'exercise' included using the 'AND' operation. Records were then filtered and excluded following full-text screening based on the predetermined eligibility criteria.ResultsTwenty studies were included in the review. The main COM-B themes highlighted for improving patient engagement were: capability-improving patient knowledge and cognitive skills for behavioural regulation, such as 'action planning' and 'action control', which could also benefit time-management; opportunity-a balanced life situation that enabled time to be devoted to the exercise program, social support, easily accessible and affordable resources and services; and motivation-increasing patient levels of self-efficacy and autonomous motivation, which were noted to be influenced by levels of perceived 'capability', additionally 'motivation' was noted to be influenced by patients perceiving the benefits of the exercise, and adherence to the program was promoted by 'goal-setting'. Other issues in the 'capability' domain included a fear and/or dislike of exercise.ConclusionPatient engagement behavior has been shown to be influenced by both external (opportunity) and intrapersonal variables (capability and motivation). Those prescribing exercises within a rehabilitation program need to discuss these factors with their patients and co-design the exercise rehabilitation program in partnership with the patient, since this is likely to improve patient engagement, and thereby result in superior health outcomes. Furthermore, these factors need to be a consideration in clinical trials, if the findings from such trials are to translate into mainstream healthcare settings.

Project description:BackgroundDue to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.ObjectiveIn this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.MethodsThe scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.ResultsA total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.ConclusionsMultiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

Project description:Aim Although cardiac rehabilitation improves physical fitness after a cardiac event, many eligible patients do not participate in cardiac rehabilitation and the beneficial effects of cardiac rehabilitation are often not maintained over time. Home-based training with telemonitoring guidance could improve participation rates and enhance long-term effectiveness. Methods and results We randomised 90 low-to-moderate cardiac risk patients entering cardiac rehabilitation to three months of either home-based training with telemonitoring guidance or centre-based training. Although training adherence was similar between groups, satisfaction was higher in the home-based group ( p?=?0.02). Physical fitness improved at discharge ( p?<?0.01) and at one-year follow-up ( p?<?0.01) in both groups, without differences between groups (home-based p?=?0.31 and centre-based p?=?0.87). Physical activity levels did not change during the one-year study period (centre-based p?=?0.38, home-based p?=?0.80). Healthcare costs were statistically non-significantly lower in the home-based group (€437 per patient, 95% confidence interval -562 to 1436, p?=?0.39). From a societal perspective, a statistically non-significant difference of €3160 per patient in favour of the home-based group was found (95% confidence interval -460 to 6780, p?=?0.09) and the probability that it was more cost-effective varied between 97% and 75% (willingness-to-pay of €0 and €100,000 per quality-adjusted life-years, respectively). Conclusion We found no differences between home-based training with telemonitoring guidance and centre-based training on physical fitness, physical activity level or health-related quality of life. However, home-based training was associated with a higher patient satisfaction and appears to be more cost-effective than centre-based training. We conclude that home-based training with telemonitoring guidance can be used as an alternative to centre-based training for low-to-moderate cardiac risk patients entering cardiac rehabilitation.

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Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement.

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