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Optimal upper extremity motor control and range of motion are necessary to achieve even the basic activities of daily living (ADL) function. Stroke, with resulting hemiparesis, can significantly and negatively impact an individuals ADL function. Functional Independence Measure (FIM) self-care score can provide an assessment of what aspects and to what degree ADL functions are impaired. FIM self-care assessment can also track changes in ADL function during stroke recovery and rehabilitation. Recently, the sensor-acquired 3D motion analysis of stroke patients upper extremity has shown promise as a potential alternative to assess ADL function. This observational study evaluates whether the sensor-acquired upper extremity reachable workspace (RWS) measure correlates with clinician-evaluated FIM self-care score in stroke patients. Seventeen patients with stroke were enrolled in the study. FIM self-care, NeuroQoL upper extremity, and reachable workspace outcome measures (relative surface area, RSA) were collected upon rehabilitation hospital admission, at discharge, and at the 3-month visit. Pearson and Spearmans rank correlation coefficients as well as multiple linear regression analyses were used to determine the relationships between FIM self-care, NeuroQoL, and reachable workspace RSAs. Moderately strong correlation between total reachable workspace RSA and total FIM self-care score at discharge and at 3 months were noted (r = 0.619, r = 0.661, p < 0.05), and similarly strong correlation was also noted with the upper extremity NeuroQoL total score (r = 0.690, r = 0.815, p < 0.05). Multiple linear regression analyses revealed a change in average bilateral total RSA of 0.1 unit from admission to the 3-month follow-up correlated with a respective change in the FIM self-care score of 2.011 points (95%CI: 0.663-3.360). Longitudinal improvement in ADL function during stroke rehabilitation and recovery process is correlated with improvement in reachable workspace.

BackgroundChildren with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. ObjectiveThis study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. MethodsThere were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning–based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. ResultsExisting calorimetry equations using linear regression and nonlinear machine-learning–based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). ConclusionsOur results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning–based nonlinear regression specifically developed for this target population.

BackgroundDespite the recent explosion of the mobile health (mHealth) industry and consumer acquisition of mHealth tools such as wearable sensors and applications (apps), limited information is known about how this technology can sustain health behavior change and be integrated into health care. ObjectiveThe objective of the study was to understand potential users’ views of mHealth technology, the role this technology may have in promoting individual activity goals aimed at improving health, and the value of integrating mHealth technology with traditional health care. MethodsFour focus groups were conducted with adults interested in sharing their views on how mHealth technology could support wellness programs and improve health. Participants (n=30) were enrolled from an employee population at an academic health institution. Qualitative thematic analysis was used to code transcripts and identify overarching themes. ResultsOur findings suggest that tracking health data alone may result in heightened awareness of daily activity, yet may not be sufficient to sustain use of mHealth technology and apps, which often have low reuse rates. Participants suggested that context, meaning, and health care partnerships need to be incorporated to engage and retain users. In addition to these findings, drivers for mHealth technology previously identified in the literature, including integration and control of health data were confirmed in this study. ConclusionsThis study explores ways that mHealth technologies may be used to not only track data, but to encourage sustained engagement to achieve individual health goals. Implications of these findings include recommendations for mHealth technology design and health care partnership models to sustain motivation and engagement, allowing individuals to achieve meaningful behavior change.

Introduction/aimsNeuralgic amyotrophy (NA) is a multifocal neuropathy involving the nerves of the upper extremity, limiting functional capability and reducing range of motion. The reachable workspace (RWS) is a computerized three-dimensinal analysis system that evaluates the relative surface area (RSA) of an individual's arm reachability and has shown utility in several neuromuscular disorders. The aims of this study were to examine the ability of the RWS to quantitatively detect limitations in upper extremity active range of motion in patients with NA, and correlate these with other upper extremity functional outcome measures.MethodsForty-seven patients with NA and 25 healthy age- and sex-matched controls were measured with the RWS. Study participants' RSAs were correlated with scores on the Shoulder Rating Questionnaire (SRQ), the Disabilities of Arm Shoulder and Hand (DASH) questionnaire, and upper extremity strength measurements using hand-held dynamometry.ResultsPatients with NA showed significantly lower values in the affected arm for all quadrants (except for the ipsilateral lower quadrant) and total RSA compared with controls (P

BackgroundOutcome measures for non-ambulant Duchenne muscular dystrophy (DMD) patients are limited, with only the Performance of the Upper Limb (PUL) approved as endpoint for clinical trials.ObjectiveWe assessed four outcome measures based on devices developed for the gaming industry, aiming to overcome disadvantages of observer-dependency and motivation.MethodsTwenty-two non-ambulant DMD patients (range 8.6-24.1 years) and 14 healthy controls (HC; range 9.5-25.4 years) were studied at baseline and 16 patients at 12 months using Leap Motion to quantify wrist/hand active range of motion (aROM) and a Kinect sensor for reached volume with Ability Captured Through Interactive Video Evaluation (ACTIVE), Functional Workspace (FWS) summed distance to seven upper extremity body points, and trunk compensation (KinectTC). PUL 2.0 was performed in patients only. A stepwise approach assessed quality control, construct validity, reliability, concurrent validity, longitudinal change and patient perception.ResultsLeap Motion aROM distinguished patients and HCs for supination, radial deviation and wrist flexion (range p = 0.006 to

The elderly population experiences a decline in upper extremity range of motion (ROM), impairing activities of daily living. The primary mode of quantification is by goniometer measurement. In this cross-sectional observation study, we investigate a sensor-acquired reachable workspace for assessing shoulder ROM decline in an elderly population in comparison to traditional measurements. Sixty-one healthy subjects aged ≥ 65 years were included and compared to a cohort of 39 younger subjects, aged 20 to 64. A sensor acquired reachable workspace using a Kinect motion capture camera measured the maximum reaching ability of both arms while in a seated position, measured in m2 and normalized to arm length to calculate a novel score defined as a relative surface area. This score approximates range of motion in the upper extremity. This measurement was compared to goniometer measurements, including active ROM in shoulder flexion and abduction. Total RSA shows moderate to strong correlation between goniometer in flexion and abduction in the dominant arm (R = 0.790 and R = 0.650, P < .001, respectively) and moderate correlations for the nondominant arm (R = 0.622 and R = 0.615, P < .001). Compared to the younger cohort, the elderly population demonstrated significantly reduced total RSA in the dominant arm (meanelderly = 0.774, SD = 0.09; meanyounger = 0.830, SD = 0.07, P < .001), with significant reductions in the upper lateral quadrant in both arms (dominant: meanelderly = 0.225, SD = 0.04; meanyounger = 0.241, SD = 0.01; P < .001; nondominant: meanelderly = 0.213, SD = 0.03; meanyounger = 0.228, SD = 0.01; P = .004). The test-retest reliability was strong for both dominant and nondominant total RSA (ICC > 0.762). The reachable workspace demonstrates promise as a simple and quick tool for clinicians to assess detailed and quantitative active shoulder ROM decline in the elderly population.

OBJECTIVE: To determine the prevalence of low vitamin D (

BackgroundThis study examines the correlation, and clinical meaningfulness, between reachable workspace outcome and reported activities of daily living (ADL) function of individuals with facioscapulohumeral dystrophy (FSHD).MethodsTwenty-one FSHD subjects with various disease severity (clinical severity scores 1-4) underwent reachable workspace evaluation and completed the Quality of Life in Neurological Disorders (NeuroQoL) upper extremity questionnaire. Spearman and receiver operator curve analyses were performed.ResultsModerate correlation was found between NeuroQoL scores and total (ρ = 0.7609; P

There are a lack of quantitative measures for clinically assessing upper limb function. Conventional biomechanical performance measures are restricted to specialist labs due to hardware cost and complexity, while the resulting measurements require specialists for analysis. Depth cameras are low cost and portable systems that can track surrogate joint positions. However, these motions may not be biologically consistent, which can result in noisy, inaccurate movements. This paper introduces a rigid body modelling method to enforce biological feasibility of the recovered motions. This method is evaluated on an existing depth camera assessment: the reachable workspace (RW) measure for assessing gross shoulder function. As a rigid body model is used, position estimates of new proximal targets can be added, resulting in a proximal function (PF) measure for assessing a subject's ability to touch specific body landmarks. The accuracy, and repeatability of these measures is assessed on ten asymptomatic subjects, with and without rigid body constraints. This analysis is performed both on a low-cost depth camera system and a gold-standard active motion capture system. The addition of rigid body constraints was found to improve accuracy and concordance of the depth camera system, particularly in lateral reaching movements. Both RW and PF measures were found to be feasible candidates for clinical assessment, with future analysis needed to determine their ability to detect changes within specific patient populations.

Facioscapulohumeral Dystrophy (FSHD) results in slowly progressive strength impairment, especially the upper extremities. Recent discoveries regarding pathophysiology have led to exciting novel therapeutic strategies. To further facilitate drug development, improved FSHD outcome measures that are functionally-relevant and sensitive to longitudinal change will be critical. Recently, a motion sensor (Kinect)-based upper extremity outcome called 'reachable workspace' that provides a quantitative reconstruction of an individual's reachability was developed. In this study, changes in reachable workspace were tracked upwards for five-years in 18 FSHD subjects. Results show -1.63 %/year decline in total reachable workspace (p = 0.144); with most notable decline in the above-the-shoulder level quadrants (upper-lateral Q3: -9.5 %/year, p

IntroductionThe Kinect-based reachable workspace relative surface area (RSA) is compared with the performance of upper limb (PUL) assessment in Duchenne muscular dystrophy (DMD).Methods29 individuals with DMD (ages: 7-23; Brooke: 1-5) underwent both Kinect-based reachable workspace RSA and PUL assessments. RSAs were also collected from 24 age-matched controls. Total and quadrant RSAs were compared with the PUL total, shoulder-, middle-, and distal-dimension scores.ResultsThe total reachable workspace RSA correlated well with the total PUL score (Spearman ρ = -0.602; P < 0.001), and with each of the PUL dimensional scores: shoulder (ρ = -0.624; P < 0.001), middle (ρ = -0.564; P = 0.001), and distal (ρ = -0.630; P < 0.001). With quadrant RSA, reachability in a particular quadrant was closely associated with respective PUL dimensional-level function (lateral-upper quadrant for shoulder-, lateral-upper/lower quadrants for middle-, and lateral-lower quadrant for distal-level function).ConclusionsThis study demonstrates concurrent validity of the reachable workspace outcome measure (RSA) with the DMD-specific upper extremity outcome measure (PUL).

As telehealth plays an even greater role in global health care delivery, it will be increasingly important to develop a strong evidence base of successful, innovative telehealth solutions that can lead to scalable and sustainable telehealth programs. This paper has two aims: (1) to describe the challenges of promoting telehealth implementation to advance adoption and (2) to present a global research agenda for personalized telehealth within chronic disease management. Using evidence from the United States and the European Union, this paper provides a global overview of the current state of telehealth services and benefits, presents fundamental principles that must be addressed to advance the status quo, and provides a framework for current and future research initiatives within telehealth for personalized care, treatment, and prevention. A broad, multinational research agenda can provide a uniform framework for identifying and rapidly replicating best practices, while concurrently fostering global collaboration in the development and rigorous testing of new and emerging telehealth technologies. In this paper, the members of the Transatlantic Telehealth Research Network offer a 12-point research agenda for future telehealth applications within chronic disease management.

IntroductionReachable workspace is a measure that provides clinically meaningful information regarding arm function. In this study, a Kinect sensor was used to determine the spectrum of 3-dimensional reachable workspace encountered in a cross-sectional cohort of individuals with amyotrophic lateral sclerosis (ALS).MethodsBilateral 3D reachable workspace was recorded from 10 subjects with ALS and 17 healthy controls. The data were normalized by each individual's arm length to obtain a reachable workspace relative surface area (RSA). Concurrent validity was assessed by correlation with scoring on the ALS Functional Rating Score-revised (ALSFRSr).ResultsThe Kinect-measured reachable workspace RSA differed significantly between the ALS and control subjects (0.579 ± 0.226 vs. 0.786 ± 0.069; P < 0.001). The RSA demonstrated correlation with ALSFRSr upper extremity items (Spearman correlation ρ = 0.569; P = 0.009). With worsening upper extremity function, as categorized by the ALSFRSr, the reachable workspace also decreased progressively.ConclusionsThis study demonstrates the feasibility and potential of using a novel Kinect-based reachable workspace outcome measure in ALS.

IntroductionIt is not known whether a reduction in reachable workspace closely reflects loss of upper extremity strength in facioscapulohumeral muscular dystrophy (FSHD). In this study we aimed to determine the relationship between reachable workspace and quantitative upper extremity strength measures.MethodsMaximal voluntary isometric contraction (MVIC) testing of bilateral elbow flexion and shoulder abduction by hand-held dynamometry was performed on 26 FSHD and 27 control subjects. In addition, Kinect sensor-based 3D reachable workspace relative surface areas (RSAs) were obtained. Loading (500-g weight) effects on reachable workspace were also evaluated.ResultsQuantitative upper extremity strength (MVIC of elbow flexion and shoulder abduction) correlated with Kinect-acquired reachable workspace RSA (R = 0.477 for FSHD, P = 0.0003; R = 0.675 for the combined study cohort, P

Objectives-The aim of this study was to determine the intra- and inter-rater reliability of sonographic measurements of the median nerve cross-sectional area in individuals with carpal tunnel syndrome and healthy control participants.Methods-The median nerve cross-sectional area was evaluated by sonography in 18 participants with carpal tunnel syndrome (18 upper extremities) and 9 control participants (18 upper extremities) at 2 visits 1 week apart. Two examiners, both blinded to the presence or absence of carpal tunnel syndrome, captured independent sonograms of the median nerve at the levels of the carpal tunnel inlet, pronator quadratus, and mid-forearm. The cross-sectional area was later measured by each examiner independently. Each also traced images that were captured by the other examiner.Results-Both the intra- and inter-rater reliability rates were highest for images taken at the carpal tunnel inlet (radiologist, r = 0.86; sonographer, r = 0.87; inter-rater, r = 0.95; all P < .0001), whereas they was lowest for the pronator quadratus (r = 0.49, 0.29, and 0.72, respectively; all P < .0001). At the mid-forearm, the intra-rater reliability was lower for both the radiologist and sonographer, whereas the inter-rater reliability was relatively high (r = 0.54, 0.55, and 0.81; all P < .0001). Tracing of captured images by different examiners showed high concordance for the median cross-sectional area at the carpal tunnel inlet (r = 0.96-0.98; P < .0001).Conclusions-The highest intra- and inter-rater reliability was found at the carpal tunnel inlet. The results also demonstrate that tracing of the median nerve cross-sectional area from captured images by different examiners does not contribute significantly to measurement variability.

IntroductionAn innovative upper extremity 3-dimensional (3D) reachable workspace outcome measure acquired using the Kinect sensor is applied toward Duchenne/Becker muscular dystrophy (DMD/BMD). The validity, sensitivity, and clinical meaningfulness of this novel outcome measure are examined.MethodsUpper extremity function assessment (Brooke scale and NeuroQOL questionnaire) and Kinect-based reachable workspace analyses were conducted in 43 individuals with dystrophinopathy (30 DMD and 13 BMD, aged 7-60 years) and 46 controls (aged 6-68 years).ResultsThe reachable workspace measure reliably captured a wide range of upper extremity impairments encountered in both pediatric and adult, as well as ambulatory and non-ambulatory individuals with dystrophinopathy. Reduced reachable workspaces were noted for the dystrophinopathy cohort compared with controls, and they correlated with Brooke grades. In addition, progressive reduction in reachable workspace correlated directly with worsening ability to perform activities of daily living, as self-reported on the NeuroQOL.ConclusionThis study demonstrates the utility and potential of the novel sensor-acquired reachable workspace outcome measure in dystrophinopathy.

IntroductionA depth-ranging sensor (Kinect) based upper extremity motion analysis system was applied to determine the spectrum of reachable workspace encountered in facioscapulohumeral muscular dystrophy (FSHD).MethodsReachable workspaces were obtained from 22 individuals with FSHD and 24 age- and height-matched healthy controls. To allow comparison, total and quadrant reachable workspace relative surface areas (RSAs) were obtained by normalizing the acquired reachable workspace by each individual's arm length.ResultsSignificantly contracted reachable workspace and reduced RSAs were noted for the FSHD cohort compared with controls (0.473 ± 0.188 vs. 0.747 ± 0.082; P

Energy expenditure (EE) estimation is an important factor in tracking personal activity and preventing chronic diseases, such as obesity and diabetes. Accurate and real-time EE estimation utilizing small wearable sensors is a difficult task, primarily because the most existing schemes work offline or use heuristics. In this paper, we focus on accurate EE estimation for tracking ambulatory activities (walking, standing, climbing upstairs, or downstairs) of a typical smartphone user. We used built-in smartphone sensors (accelerometer and barometer sensor), sampled at low frequency, to accurately estimate EE. Using a barometer sensor, in addition to an accelerometer sensor, greatly increases the accuracy of EE estimation. Using bagged regression trees, a machine learning technique, we developed a generic regression model for EE estimation that yields upto 96% correlation with actual EE. We compare our results against the state-of-the-art calorimetry equations and consumer electronics devices (Fitbit and Nike+ FuelBand). The newly developed EE estimation algorithm demonstrated superior accuracy compared with currently available methods. The results were calibrated against COSMED K4b2 calorimeter readings.

BackgroundThe concept of reachable workspace is closely tied to upper limb joint range of motion and functional capability. Currently, no practical and cost-effective methods are available in clinical and research settings to provide arm-function evaluation using an individual's three-dimensional (3D) reachable workspace. A method to intuitively display and effectively analyze reachable workspace would not only complement traditional upper limb functional assessments, but also provide an innovative approach to quantify and monitor upper limb function.Methodology/principal findingsA simple stereo camera-based reachable workspace acquisition system combined with customized 3D workspace analysis algorithm was developed and compared against a sub-millimeter motion capture system. The stereo camera-based system was robust, with minimal loss of data points, and with the average hand trajectory error of about 40 mm, which resulted to ~5% error of the total arm distance. As a proof-of-concept, a pilot study was undertaken with healthy individuals (n = 20) and a select group of patients with various neuromuscular diseases and varying degrees of shoulder girdle weakness (n = 9). The workspace envelope surface areas generated from the 3D hand trajectory captured by the stereo camera were compared. Normalization of acquired reachable workspace surface areas to the surface area of the unit hemi-sphere allowed comparison between subjects. The healthy group's relative surface areas were 0.618±0.09 and 0.552±0.092 (right and left), while the surface areas for the individuals with neuromuscular diseases ranged from 0.03 and 0.09 (the most severely affected individual) to 0.62 and 0.50 (very mildly affected individual). Neuromuscular patients with severe arm weakness demonstrated movement largely limited to the ipsilateral lower quadrant of their reachable workspace.Conclusions/significanceThe findings indicate that the proposed stereo camera-based reachable workspace analysis system is capable of distinguishing individuals with varying degrees of proximal upper limb functional impairments.