Estimation of Energy Expenditure in Wheelchair-Bound Spinal Cord Injured Individuals Using Inertial Measurement Units

A healthy lifestyle reduces the risk of cardio-vascular disease. As wheelchair-bound individuals with spinal cord injury (SCI) are challenged in their activities, promoting and coaching an active lifestyle is especially relevant. Although there are many commercial activity trackers available for the able-bodied population, including those providing feedback about energy expenditure (EE), activity trackers for the SCI population are largely lacking, or are limited to a small set of activities performed in controlled settings. The aims of the present study were to develop and validate an algorithm based on inertial measurement unit (IMU) data to continuously monitor EE in wheelchair-bound individuals with a SCI, and to establish reference activity values for a healthy lifestyle in this population. For this purpose, EE was measured in 30 subjects each wearing four IMUs during 12 different physical activities, randomly selected from a list of 24 activities of daily living. The proposed algorithm consists of three parts: resting EE estimation based on multi-linear regression, an activity classification using a k-nearest-neighbors algorithm, and EE estimation based on artificial neural networks (ANNs). The mean absolute estimation error for the ANN-based algorithm was 14.4% compared to indirect calorimeter measurements. Based on reference values from the literature and the data collected within this study, we recommend wheeling 3 km per day for a healthy lifestyle in wheelchair-bound SCI individuals. Combining the proposed algorithm with a recommendation for physical activity provides a powerful tool for the promotion of an active lifestyle in the SCI population, thereby reducing the risk for secondary diseases

Rewiring of the corticospinal tract in the adult rat after unilateral stroke and anti-Nogo-A therapy

The adult CNS has limited potential for functional recovery after structural lesions. Lindau et al. report that a blocking antibody to the neurite-growth inhibitory protein Nogo-A improved functional recovery in a rat sensorimotor cortex stroke model. The functional recovery was accompanied by increased corticospinal innervation from the contralateral corte

RE-CODE DCM (REsearch Objectives and Common Data Elements for Degenerative Cervical Myelopathy): A Consensus Process to Improve Research Efficiency in DCM, Through Establishment of a Standardized Dataset for Clinical Research and the Definition of the Research Priorities.

Study Design: Mixed-method consensus process. Objectives: Degenerative cervical myelopathy (DCM) is a common and disabling condition that arises when mechanical stress damages the spinal cord as a result of degenerative changes in the surrounding spinal structures. RECODE-DCM (REsearch Objectives and Common Data Elements for Degenerative Cervical Myelopathy) aims to improve efficient use of health care resources within the field of DCM by using a multi-stakeholder partnership to define the DCM research priorities, to develop a minimum dataset for DCM clinical studies, and confirm a definition of DCM. Methods: This requires a multi-stakeholder partnership and multiple parallel consensus development processes. It will be conducted via 4 phases, adhering to the guidance set out by the COMET (Core Outcomes in Effectiveness Trials) and JLA (James Lind Alliance) initiatives. Phase 1 will consist of preliminary work to inform online Delphi processes (Phase 2) and a consensus meeting (Phase 3). Following the findings of the consensus meeting, a synthesis of relevant measurement instruments will be compiled and assessed as per the COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) criteria, to allow recommendations to be made on how to measure agreed data points. Phase 4 will monitor and promote the use of eventual recommendations. Conclusions: RECODE-DCM sets out to establish for the first time an index term, minimum dataset, and research priorities together. Our aim is to reduce waste of health care resources in the future by using patient priorities to inform the scope of future DCM research activities. The consistent use of a standard dataset in DCM clinical studies, audit, and clinical surveillance will facilitate pooled analysis of future data and, ultimately, a deeper understanding of DCM.AM is funded by a Clinician Scientist Fellowship (NIHR-CS-2017-17-010) from the UK National Institute for Health Research (NIHR) and supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. Research in the senior author’s laboratory is supported by a core support grant from the Wellcome Trust and MRC to the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute. MRNK is supported by a NIHR Clinician Scientist Award, CS-2015-15-023

Lived Experience-Centred Word Clouds May Improve Research Uncertainty Gathering in Priority Setting Partnerships

INTRODUCTION: AO Spine RECODE-DCM was a multi-stakeholder priority setting partnership (PSP) to define the top ten research priorities for degenerative cervical myelopathy (DCM). Priorities were generated and iteratively refined using a series of surveys administered to surgeons, other healthcare professionals (oHCP) and people with DCM (PwDCM). The aim of this work was to utilise word clouds to enable the perspectives of people with the condition to be heard earlier in the PSP process than is traditionally the case. The objective was to evaluate the added value of word clouds in the process of defining research uncertainties in National Institute for Health Research (NIHR) James Lind Alliance (JLA) Priority Setting Partnerships. METHODS: Patient-generated word clouds were created for the four survey subsections of the AO Spine RECODE-DCM PSP: diagnosis, treatment, long-term management and other issues. These were then evaluated as a nested methodological study. Word-clouds were created and iteratively refined by an online support group of people with DCM, before being curated by the RECODE-DCM management committee and expert healthcare professional representatives. The final word clouds were embedded within the surveys administered at random to 50% of participants. DCM research uncertainties suggested by participants were compared pre- and post-word cloud presentation. RESULTS: A total of 215 (50.9%) participants were randomised to the word cloud stream, including 118 (55%) spinal surgeons, 52 (24%) PwDCM and 45 (21%) oHCP. Participants submitted 434 additional uncertainties after word cloud review: word count was lower and more uniform across each survey subsections compared to pre-word cloud uncertainties. Twenty-three (32%) of the final 74 PSP summary questions did not have a post-word cloud contribution and no summary question was formed exclusively on post-word cloud uncertainties. There were differences in mapping of pre- and post-word cloud uncertainties to summary questions, with greater mapping of post-word cloud uncertainties to the number 1 research question priority: raising awareness. Five of the final summary questions were more likely to map to the research uncertainties suggested by participants after having reviewed the word clouds. CONCLUSIONS: Word clouds may increase the perspective of underrepresented stakeholders in the research question gathering stage of priority setting partnerships. This may help steer the process towards research questions that are of highest priority for people with the condition

How Plastic Is the Brain after a Stroke?

Stroke is a common problem, and with an aging population, it is likely to become more so. Outcomes from stroke are wide ranging from death to complete recovery, but the majority result in severe motor impairments that affect quality of life and become a burden on health care systems, family, and friends. Therapeutically, removal of thromboses can greatly improve outcomes, but for many stroke sufferers, the only currently available therapy is rehabilitative training in which spared brain areas and fiber tracts are strengthened and trained to take over new functions. Experimental data in animals show that this is in part based on changes in the connectivity of the brain and spinal cord and on the growth of new nerve fiber branches, a process called structural plasticity. So, just how plastic is the brain after a stroke? In this review, we explore the factors that affect plasticity after strokes, such as age and the overall size and location of the lesion. We discuss the peri-infarct area as extensive research has shown that processes occurring there are likely to be involved mechanistically in plastic changes in cortical circuitry. Finally, we review promising interventions being tested preclinically and discuss those that have been translated into clinical research

Estimation of energy expenditure in wheelchair-bound spinal cord injured individuals using inertial measurement units

A healthy lifestyle reduces the risk of cardio-vascular disease. As wheelchair-bound individuals with spinal cord injury (SCI) are challenged in their activities, promoting and coaching an active lifestyle is especially relevant. Although there are many commercial activity trackers available for the able-bodied population, including those providing feedback about energy expenditure (EE), activity trackers for the SCI population are largely lacking, or are limited to a small set of activities performed in controlled settings. The aims of the present study were to develop and validate an algorithm based on inertial measurement unit (IMU) data to continuously monitor EE in wheelchair-bound individuals with a SCI, and to establish reference activity values for a healthy lifestyle in this population. For this purpose, EE was measured in 30 subjects each wearing four IMUs during 12 different physical activities, randomly selected from a list of 24 activities of daily living. The proposed algorithm consists of three parts: resting EE estimation based on multi-linear regression, an activity classification using a k-nearest-neighbors algorithm, and EE estimation based on artificial neural networks (ANNs). The mean absolute estimation error for the ANN-based algorithm was 14.4% compared to indirect calorimeter measurements. Based on reference values from the literature and the data collected within this study, we recommend wheeling 3 km per day for a healthy lifestyle in wheelchair-bound SCI individuals. Combining the proposed algorithm with a recommendation for physical activity provides a powerful tool for the promotion of an active lifestyle in the SCI population, thereby reducing the risk for secondary diseases

Reliability of movement workspace measurements in a passive arm orthosis used in spinal cord injury rehabilitation

BACKGROUND: Robotic and non-robotic training devices are increasingly being used in the rehabilitation of upper limb function in subjects with neurological disorders. As well as being used for training such devices can also provide ongoing assessments during the training sessions. Therefore, it is mandatory to understand the reliability and validity of such measurements when used in a clinical setting. The aim of this study was to evaluate the reliability of movement measures as assessed in the Armeo Spring system for the eventual application to the rehabilitation of patients suffering from cervical spinal cord injury (SCI). METHODS: Reliability (intra- and inter-rater reliability) of the movement workspace (representing multiple ranges of movement) and the influence of varying seating conditions (5 different chair conditions) was assessed in twenty control subjects. In eight patients with cervical SCI the test-retest reliability (tested twice on the same day by the same rater) was assessed as well as a correlation of the movement workspace to retrieve self-care items as scored by the spinal cord independence measure (SCIM 3). RESULTS: Analysis of workspace measures in control subjects revealed intra-class correlation coefficients (ICC) ranging from 0.747 to 0.837 for the intra-rater reliability and from 0.661 to 0.855 for the inter-rater reliability. Test-retest analysis in SCI patients showed a similar high reliability with ICC = 0.858. Also the reliability of the movement workspace between different seating conditions was good with ICCs ranging from 0.844 to 0.915. The movement workspace correlated significantly with the SCIM3 self-care items (p < 0.05, rho = 0.72). CONCLUSION: The upper limb movement workspace measures assessed in the Armeo Spring device revealed fair to good clinical reliability. These findings suggest that measures retrieved from such a training device can be used to monitor changes in upper limb function over time. The correlation between the workspace measures and SCIM3 self-care items indicates that such measures might also be valuable to document the progress of clinical rehabilitation, however further detailed studies are required

Reliability of movement workspace measurements in a passive arm orthosis used in spinal cord injury rehabilitation

Abstract Background Robotic and non-robotic training devices are increasingly being used in the rehabilitation of upper limb function in subjects with neurological disorders. As well as being used for training such devices can also provide ongoing assessments during the training sessions. Therefore, it is mandatory to understand the reliability and validity of such measurements when used in a clinical setting. The aim of this study was to evaluate the reliability of movement measures as assessed in the Armeo Spring system for the eventual application to the rehabilitation of patients suffering from cervical spinal cord injury (SCI). Methods Reliability (intra- and inter-rater reliability) of the movement workspace (representing multiple ranges of movement) and the influence of varying seating conditions (5 different chair conditions) was assessed in twenty control subjects. In eight patients with cervical SCI the test-retest reliability (tested twice on the same day by the same rater) was assessed as well as a correlation of the movement workspace to retrieve self-care items as scored by the spinal cord independence measure (SCIM 3). Results Analysis of workspace measures in control subjects revealed intra-class correlation coefficients (ICC) ranging from 0.747 to 0.837 for the intra-rater reliability and from 0.661 to 0.855 for the inter-rater reliability. Test-retest analysis in SCI patients showed a similar high reliability with ICC = 0.858. Also the reliability of the movement workspace between different seating conditions was good with ICCs ranging from 0.844 to 0.915. The movement workspace correlated significantly with the SCIM3 self-care items (p  Conclusion The upper limb movement workspace measures assessed in the Armeo Spring device revealed fair to good clinical reliability. These findings suggest that measures retrieved from such a training device can be used to monitor changes in upper limb function over time. The correlation between the workspace measures and SCIM3 self-care items indicates that such measures might also be valuable to document the progress of clinical rehabilitation, however further detailed studies are required.</p

A novel algorithm for detecting active propulsion in wheelchair users following spinal cord injury

Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as this is one of the most intense upper extremity activities they perform. Current accelerometer-based approaches for describing wheelchair mobility do not distinguish between self- and attendant-propulsion and hence may overestimate total physical activity. The aim of this study was to develop and validate an inertial measurement unit based algorithm to monitor wheel kinematics and the type of wheelchair propulsion (self- or attendant-) within a "real-world" situation. Different sensor set-ups were investigated, ranging from a high precision set-up including four sensor modules with a relatively short measurement duration of 24 h, to a less precise set-up with only one module attached at the wheel exceeding one week of measurement because the gyroscope of the sensor was turned off. The "high-precision" algorithm distinguished self- and attendant-propulsion with accuracy greater than 93% whilst the long-term measurement set-up showed an accuracy of 82%. The estimation accuracy of kinematic parameters was greater than 97% for both set-ups. The possibility of having different sensor set-ups allows the use of the inertial measurement units as high precision tools for researchers as well as unobtrusive and simple tools for manual wheelchair users