Considering Propulsion Pattern in Therapeutic Outcomes for Children Who Use Manual Wheelchairs.

PURPOSE: Children who use manual wheelchairs encounter pain and injury risks to the upper body. Current literature does not describe how propulsion pattern and physiotherapeutic training methodologies impact response to treatment. METHODS: This study assesses the effect of community-based intensive physical and occupational therapy on functional outcomes over a 7-week period in pediatric manual wheelchair users. RESULTS: Key results include significant joint and musculotendon kinematic differences at the shoulder, improved speed and propulsion effectiveness, and changed propulsion pattern. CONCLUSIONS: Statistics also revealed that propulsion pattern was a predictor of response to therapy, as was weekly therapeutic duration, wheelchair-specific focus by the therapists, and stretching.

Assessment of a markerless motion analysis system for manual wheelchair application.

BACKGROUND: Wheelchair biomechanics research advances accessibility and clinical care for manual wheelchair users. Standardized outcome assessments are vital tools for tracking progress, but there is a strong need for more quantitative methods. A system offering kinematic, quantitative detection, with the ease of use of a standardized outcome assessment, would be optimal for repeated, longitudinal assessment of manual wheelchair users' therapeutic progress, but has yet to be offered. RESULTS: This work evaluates a markerless motion analysis system for manual wheelchair mobility in clinical, community, and home settings. This system includes Microsoft® Kinect® 2.0 sensors, OpenSim musculoskeletal modeling, and an automated detection, processing, and training interface. The system is designed to be cost-effective, easily used by caregivers, and capable of detecting key kinematic metrics involved in manual wheelchair propulsion. The primary technical advancements in this research are the software components necessary to detect and process the upper extremity kinematics during manual wheelchair propulsion, along with integration of the components into a complete system. The study defines and evaluates an adaptable systems methodology for processing kinematic data using motion capture technology and open-source musculoskeletal models to assess wheelchair propulsion pattern and biomechanics, and characterizes its accuracy, sensitivity and repeatability. Inter-trial repeatability of spatiotemporal parameters, joint range of motion, and musculotendon excursion were all found to be significantly correlated (p < 0.05). CONCLUSIONS: The system is recommended for use in clinical settings for frequent wheelchair propulsion assessment, provided the limitations in precision are considered. The motion capture-model software bridge methodology could be applied in the future to any motion-capture system or specific application, broadening access to detailed kinematics while reducing assessment time and cost.

Validation of the Patient Global Impression of Improvement for Penile Prosthesis.

BACKGROUND: No consensus on the preferred means of evaluating patients after surgical placement of an inflatable penile prosthesis (IPP) currently exists. Many self-assessment questionnaires are available, but none specifically targets patients with IPPs. The purpose of this study was to assess the construct validity of the Patient Global Impression of Improvement (PGI-I) for evaluating patient satisfaction after placement of an IPP. METHODS: We conducted a multicenter prospective trial and enrolled patients who elected to have a 3-piece IPP surgically implanted. Postoperatively, patients completed the Sexual Health Inventory for Men (SHIM), Erectile Dysfunction Inventory of Treatment Satisfaction (EDITS), and PGI-I at 3, 6, and 12 months. The Pearson correlation coefficient (PCC) was used to compare scores over time. RESULTS: Fifty-six patients were enrolled, and complete data were available for 39 patients. At 3 months, the PGI-I correlated with the EDITS (PCC=0.83, P<0.01) and with the SHIM (PCC=0.73, P<0.01). At 6 months, the PGI-I correlated with the EDITS (PCC=0.74, P<0.01). At 6 months, the PCC between the PGI-I and the SHIM was 0.41 (P<0.05). At 12 months, the PCC between the PGI-I and the EDITS was 0.83 (P<0.01), and the PCC between the PGI-I and the SHIM was 0.61 (P<0.01). CONCLUSIONS: Overall, the PGI-I appears to correlate with both the SHIM and EDITS and is a valid evaluation tool for use with patients after IPP placement.

Patient perception of transvaginal mesh and the media.

OBJECTIVE: To assess the penetration of media-based information on transvaginal mesh (TVM) in our patient population and to determine whether exposure affects patient opinion. Since the 2011 Federal Drug Administration communication on TVM, many advertisements from legal practices have been directed toward patients. MATERIALS AND METHODS: An 18-item survey was administered to female patients at 2 sites from August 2012 to April 2013. Patients presenting with new diagnoses of pelvic organ prolapse or stress urinary incontinence or patients who reported prior mesh surgery were excluded. RESULTS: Ninety-nine questionnaires were completed. Sixty-six of the patients (67%) were aware of TVM; and of these, 38 (58%) cited advertisements as the initial source of information. Only 12% were aware of the Food and Drug Administration's communication. Regarding opinion of TVM, 9% chose "it is a safe product," 9% "safety depends on factors related to patient," 4.5% "not a safe product," 1.5% "safety depends on the doctor," 68% "I don't know," and 4.5% marked 2 selections. Only 12% indicated knowing the difference in the use of TVM for pelvic organ prolapse vs stress urinary incontinence. When asked what influenced their opinion of TVM the most; responses were as follows: advertisement (33.3%), medical professional (22.7%), friends or family who underwent TVM procedure (12.1%), media article (6.1%), and "not sure" (25.8%). CONCLUSION: Advertisements of TVM lawsuits had a high penetration into our patient population but did not produce an overtly negative response in our sample. Clinicians should be aware of the impact of these advertisements on patient opinion and counsel patients accordingly with unbiased and scientifically accurate information.

Functional classification of skeletal muscle networks. II. Applications to pathophysiology.

In our preceding companion paper (Wang Y, Winters J, Subramaniam S. J Appl Physiol. doi: 10.1152/japplphysiol.01514.2011), we used extensive expression profile data on normal human subjects, in combination with legacy knowledge to classify skeletal muscle function into four models, namely excitation-activation, mechanical, metabolic, and signaling-production model families. In this paper, we demonstrate how this classification can be applied to study two well-characterized myopathies: amyotrophic lateral sclerosis (ALS) and Duchenne muscular dystrophy (DMD). Using skeletal muscle profile data from ALS and DMD patients compared with that from normal subjects, normal young in the case of DMD, we delineate molecular mechanisms that are causative and consequential to skeletal muscle dysfunction. In ALS, our analysis establishes the metabolic role and specifically identifies the mechanisms of calcium dysregulation and defects in mitochondrial transport of materials as important for muscle dysfunction. In DMD, we illustrate how impaired mechanical function is strongly coordinated with other three functional networks, resulting in transformation of the skeletal muscle into hybrid forms as a compensatory mechanism. Our functional models also provide, in exquisite detail, the mechanistic role of myriad proteins in these four families in normal and disease function.

Functional classification of skeletal muscle networks. I. Normal physiology.

Extensive measurements of the parts list of human skeletal muscle through transcriptomics and other phenotypic assays offer the opportunity to reconstruct detailed functional models. Through integration of vast amounts of data present in databases and extant knowledge of muscle function combined with robust analyses that include a clustering approach, we present both a protein parts list and network models for skeletal muscle function. The model comprises the four key functional family networks that coexist within a functional space; namely, excitation-activation family (forward pathways that transmit a motoneuronal command signal into the spatial volume of the cell and then use Ca(2+) fluxes to bind Ca(2+) to troponin C sites on F-actin filaments, plus transmembrane pumps that maintain transmission capacity); mechanical transmission family (a sophisticated three-dimensional mechanical apparatus that bidirectionally couples the millions of actin-myosin nanomotors with external axial tensile forces at insertion sites); metabolic and bioenergetics family (pathways that supply energy for the skeletal muscle function under widely varying demands and provide for other cellular processes); and signaling-production family (which represents various sensing, signal transduction, and nuclear infrastructure that controls the turn over and structural integrity and regulates the maintenance, regeneration, and remodeling of the muscle). Within each family, we identify subfamilies that function as a unit through analysis of large-scale transcription profiles of muscle and other tissues. This comprehensive network model provides a framework for exploring functional mechanisms of the skeletal muscle in normal and pathophysiology, as well as for quantitative modeling.

A framework for mapping between "living" muscle model parameters and systems biology data for muscle tissue.

Striated muscle represents a unique type of actuator in that it depends on living tissue. Models of muscle have historically focused on the role of actuator, using properties that do not adapt over time. This paper extends the foundation of Hill-based muscle models by considering muscle as a tissue composed of well-mixed composite materials (at the level of fascicle), and identifies three specific classes of protein families that occupy functional space functional space: excitation → activation; mechanical attachment/transmission, and myo-energy supply. Typically parameters describing nonlinear muscle properties have been estimated either directly or based on anthropometry and fiber composition. Here we develop a framework for augmenting such estimation through mapping to the up/down-regulation of specific proteins and their transcripts. While useful for establishing a framework for "living" muscle models that can evolve, it also provides an attractive approach for helping interpret high-throughput systems biology data, especially muscle tissue biopsies from studies that target interventional tasks and/or myo-disorders.

Modeling the adaptive pathophysiology of essential hypertension.

This paper proposes an adaptive neuro-fuzzy model to study the pathophysiology of essential hypertension. Using diverse inputs such as risk factors, physical relations and medical interventions, and states that include both transient and resting states for key physiological variables (blood pressure, total peripheral resistance), it can roughly predict both real-time and long-term blood pressure change for a robust range of inputs. Although it was tuned using published population data, it can be applied to specific individuals to estimate the risks of hypertension with different life experience.

Multivariate nonlinear regression analysis of trajectory tracking performance using force reflecting joystick in chronic stroke-induced hemiparesis.

Individualizing a neurorehabilitation training protocol requires understanding the performance of subjects with various capabilities under different task settings. We use multivariate regression to evaluate the performance of subjects with stroke-induced hemiparesis in trajectory tracking tasks using a force-reflecting joystick. A nonlinear effect was consistently shown in both dimensions of force field strength and impairment level for selected kinematic performance measures, with greatest sensitivity at lower force fields. This suggests that the form of a force field may play a different "role" for subjects with various impairment levels, and confirms that to achieve optimized therapeutic benefit, it is necessary to personalize interfaces.

Development of a method for evaluating accessibility of medical equipment for patients with disabilities.

OBJECTIVE: The purpose of this study was to develop a method for evaluating accessibility of medical equipment for patients with disabilities. METHODS: The researchers reviewed videotapes of patient-participants with various physical and sensory disabilities using different types of medical equipment. For each of 11 videotapes, four observers independently identified and documented access and safety barriers, such as physical, sensory, cognitive, and environmental barriers. Inter-observer variability for identifying barrier presence was assessed with kappa statistics for pairs of observers. RESULTS: A list of 10 access and safety barriers was developed through an iterative consensus process, which identified design features of medical equipment that presented difficulties for participants with disabilities. The list is useful for identifying and categorizing accessibility problems found in equipment. While reliability of barrier identification was substantial or moderate for some barriers, reconciliation of barrier events identified by multiple video observers is recommended for optimal results.

Evaluation of applied forces and EMG of the young, aged & stroke population in a 3D arm workspace.

The objectives of this study were to evaluate 11 muscle electromyograms (EMGs) while performing force application tasks in a 3D workspace, and to identify challenging regions within the workspace in which subjects had difficultly generating forces in desired directions. Each subject (4 young healthy adults, 4 older with stroke-induced disability, 4 age-matched older) applied forces (8 lbs desired) in 6 directions at 19 locations spatially distributed in the workspace. The normals could meet the force threshold levels except for the 2 female aged participants for the Right force direction. The stroke group had common difficult directions of Up and Right. The muscle activations were dependent upon the applied force direction, with Up force being associated with maximum EMGs. Maximum variation in the EMGs was in the right and far region for the young adults and in far and low region for the older adults. The stroke subjects' shoulder-arm EMGs showed less directional variability in the regions of workspace, and considerable compensatory trunk movement, unlike the normals.

A pilot study evaluating use of a computer-assisted neurorehabilitation platform for upper-extremity stroke assessment.

BACKGROUND: There is a need to develop cost-effective, sensitive stroke assessment instruments. One approach is examining kinematic measures derived from goal-directed tasks, which can potentially be sensitive to the subtle changes in the stroke rehabilitation process. This paper presents the findings from a pilot study that uses a computer-assisted neurorehabilitation platform, interfaced with a conventional force-reflecting joystick, to examine the assessment capability of the system by various types of goal-directed tasks. METHODS: Both stroke subjects with hemiparesis and able-bodied subjects used the force-reflecting joystick to complete a suite of goal-directed tasks under various task settings. Kinematic metrics, developed for specific types of goal-directed tasks, were used to assess various aspects of upper-extremity motor performance across subjects. RESULTS: A number of metrics based on kinematic performance were able to differentiate subjects with different impairment levels, with metrics associated with accuracy, steadiness and speed consistency showing the best capability. Significant differences were also shown on these metrics between various force field settings. CONCLUSION: The results support the potential of using UniTherapy software with a conventional joystick system as an upper-extremity assessment instrument. We demonstrated the ability of using various types of goal-directed tasks to distinguish between subjects with different impairment levels. In addition, we were able to show that different force fields have a significant effect on the performance across subjects with different impairment levels in the trajectory tracking task. These results provide motivation for studies with a larger sample size that can more completely span the impairment space, and can use insights presented here to refine considerations of various task settings so as to generalize and extend our conclusions.

Evaluating automatically generated personalized interfaces on an ergometer for people with diverse abilities.

The MedURC (Medical Universal Remote Console) technology uses a collection of standards to create universal interfaces for various medical equipment, including user information on preferences and capabilities to create a personalized accessible interface. This project significantly extends MedURC by supporting an ad hoc fitness industry communication standard for that makes it possible for MedURC to operate any other supported exercise equipment. A variety of alternative interfaces (default, universally designed, personalized) were evaluated by subjects that included persons with disabilities and older adults, using performance data while executing specific tasks and subject interviews. Results show that subjects prefer and perform better on a personalized interface.

A multisegmental foot model with bone-based referencing: sensitivity to radiographic input parameters.

We present a new kinematic model measuring the three-dimensional orientation of multiple segments of the foot and ankle. The model defines neutral alignments based on the alignments of the underlying bony segments, and indexes the orientation of skin-mounted markers to the bony anatomy using measures from weightbearing x-rays. The sensitivity of the model to these radiographic input parameters was analyzed using data from walking trials. Kinematic output in each plane was found to be most sensitive to perturbations of radiographic measurements in that same plane; however, perturbations in the coronal and transverse planes demonstrated significant carry-over into other planes. The analysis highlights the importance of accurately accounting for the underlying anatomy in measuring intersegmental kinematics.

An interactive framework for personalized computer-assisted neurorehabilitation.

This paper presents the implementation of a framework for computer-assisted neurorehabilitation that intends to address the need for more personalized healthcare technologies. This framework called UniTherapy is applied to home neurorehabilitation for individuals with stroke-induced disability. It supports interactive upper limb assessment and therapy that makes use of mass-marketed force-reflecting joysticks and wheels, as well as some customized therapeutic devices. A novel service-oriented technical infrastructure is presented, which includes a rich menu of performance assessment capabilities and support features that include telerehabilitation links, protocol design, and data analysis tools. Results are presented that demonstrate its potential as a sensor-based assessment tool. User feedback is summarized.

Potential of a suite of robot/computer-assisted motivating systems for personalized, home-based, stroke rehabilitation.

BACKGROUND: There is a need to improve semi-autonomous stroke therapy in home environments often characterized by low supervision of clinical experts and low extrinsic motivation. Our distributed device approach to this problem consists of an integrated suite of low-cost robotic/computer-assistive technologies driven by a novel universal access software framework called UniTherapy. Our design strategy for personalizing the therapy, providing extrinsic motivation and outcome assessment is presented and evaluated. METHODS: Three studies were conducted to evaluate the potential of the suite. A conventional force-reflecting joystick, a modified joystick therapy platform (TheraJoy), and a steering wheel platform (TheraDrive) were tested separately with the UniTherapy software. Stroke subjects with hemiparesis and able-bodied subjects completed tracking activities with the devices in different positions. We quantify motor performance across subject groups and across device platforms and muscle activation across devices at two positions in the arm workspace. RESULTS: Trends in the assessment metrics were consistent across devices with able-bodied and high functioning strokes subjects being significantly more accurate and quicker in their motor performance than low functioning subjects. Muscle activation patterns were different for shoulder and elbow across different devices and locations. CONCLUSION: The Robot/CAMR suite has potential for stroke rehabilitation. By manipulating hardware and software variables, we can create personalized therapy environments that engage patients, address their therapy need, and track their progress. A larger longitudinal study is still needed to evaluate these systems in under-supervised environments such as the home.

Videoconferencing and telehealth technologies can provide a reliable approach to remote assessment and teaching without compromising quality.

Cardiovascular disease remains a significant chronic healthcare problem in this country, with considerable associated economic and quality-of-life challenges. Along with these challenges, there is high demand for healthcare provider time, particularly in the areas of management of complex healthcare needs and patient education. At the same time, a critical nursing shortage exists. Telehealth technologies provide opportunities to meet the rapidly growing needs of consumers and healthcare practitioners. Many in need of services have limited access to high-end technologies. An argument has been made that the lowest level of technology needed to carry out a task should be used, if it is capable of providing the necessary services. Videoconferencing capabilities allow healthcare practitioners to engage in virtual face-to-face encounters with patients or other healthcare providers. A variety of levels of sophistication in these videoconferencing systems are available. In an effort to evaluate the effectiveness and consumer satisfaction with videoconferencing, 3 pilot studies were conducted to compare face-to-face, low-bandwidth, and high-bandwidth approaches to performing common assessments and patient education activities. In one study, a variety of experienced healthcare practitioners performed functional assessments of stroke subjects using a collection of validated scales by varying approaches (face-to-face, low-bandwidth, and high-bandwidth videoconferencing) in a randomized order. In a second study, undergraduate nursing students performed similar performance measures and taught an unfamiliar individual how to program and use an intravenous pump device, take a tympanic temperature, or to draw up insulin in a syringe. In the third study, advanced practice nursing students assessed vital signs and performed cardiopulmonary assessments on community-dwelling subjects using low-bandwidth and face-to-face approaches. Healthcare practitioners and students generally preferred high-bandwidth approaches over low-bandwidth alternatives when videoconferencing was performed; however, most participants and practitioners were satisfied with the encounters, regardless of the level of technology used.

A dynamic neuro-fuzzy model providing bio-state estimation and prognosis prediction for wearable intelligent assistants.

BACKGROUND: Intelligent management of wearable applications in rehabilitation requires an understanding of the current context, which is constantly changing over the rehabilitation process because of changes in the person's status and environment. This paper presents a dynamic recurrent neuro-fuzzy system that implements expert-and evidence-based reasoning. It is intended to provide context-awareness for wearable intelligent agents/assistants (WIAs). METHODS: The model structure includes the following types of signals: inputs, states, outputs and outcomes. Inputs are facts or events which have effects on patients' physiological and rehabilitative states; different classes of inputs (e.g., facts, context, medication, therapy) have different nonlinear mappings to a fuzzy "effect." States are dimensionless linguistic fuzzy variables that change based on causal rules, as implemented by a fuzzy inference system (FIS). The FIS, with rules based on expertise and evidence, essentially defines the nonlinear state equations that are implemented by nuclei of dynamic neurons. Outputs, a function of weighing of states and effective inputs using conventional or fuzzy mapping, can perform actions, predict performance, or assist with decision-making. Outcomes are scalars to be extremized that are a function of outputs and states. RESULTS: The first example demonstrates setup and use for a large-scale stroke neurorehabilitation application (with 16 inputs, 12 states, 5 outputs and 3 outcomes), showing how this modelling tool can successfully capture causal dynamic change in context-relevant states (e.g., impairments, pain) as a function of input event patterns (e.g., medications). The second example demonstrates use of scientific evidence to develop rule-based dynamic models, here for predicting changes in muscle strength with short-term fatigue and long-term strength-training. CONCLUSION: A neuro-fuzzy modelling framework is developed for estimating rehabilitative change that can be applied in any field of rehabilitation if sufficient evidence and/or expert knowledge are available. It is intended to provide context-awareness of changing status through state estimation, which is critical information for WIA's to be effective.

A telehomecare model for optimizing rehabilitation outcomes.

For telehealth to become an accepted component of rehabilitation, a scientific base verifying that telehealth improves outcomes must be developed. A conceptual framework based on theory and empirical findings is necessary for this area of inquiry to flourish. Most academic curricula possess such an educational pillar, which serves to help prepare professionals to practice in the new arena, and scholars to perform quality research. Currently, the authors are involved in developing areas of the biomedical engineering and nursing curricula at Marquette University to address key areas of telerehabilitation. This paper outlines the conceptual framework for these curricular areas. The conceptual framework is derived from three areas that modulate each other, and ultimately impact the outcomes of telerehabilitation. These areas are rehabilitative biosystems, human-technology interfaces, and behavioral compliance. Each can be viewed from the context of an optimization process, and the model can be applied to help identify the weak link for a given telerehabilitative approach under study. Examples of how the model can be used to frame telerehabilitation research are presented, with a special focus on designing home-based solutions for two societal challenges of large scope and great need-stroke and cardiac rehabilitation. The authors conclude that the proposed framework can be used to conceptualize, understand, and optimize the key components of a telerehabilitative process and to analyze alternative approaches for optimizing outcomes.