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

Quantifying kinematics of purposeful movements to real, imagined, or absent functional objects: Implications for modelling trajectories for robot-assisted ADL tasks**

BACKGROUND: Robotic therapy is at the forefront of stroke rehabilitation. The Activities of Daily Living Exercise Robot (ADLER) was developed to improve carryover of gains after training by combining the benefits of Activities of Daily Living (ADL) training (motivation and functional task practice with real objects), with the benefits of robot mediated therapy (repeatability and reliability). In combining these two therapy techniques, we seek to develop a new model for trajectory generation that will support functional movements to real objects during robot training. We studied natural movements to real objects and report on how initial reaching movements are affected by real objects and how these movements deviate from the straight line paths predicted by the minimum jerk model, typically used to generate trajectories in robot training environments. We highlight key issues that to be considered in modelling natural trajectories. METHODS: Movement data was collected as eight normal subjects completed ADLs such as drinking and eating. Three conditions were considered: object absent, imagined, and present. This data was compared to predicted trajectories generated from implementing the minimum jerk model. The deviations in both the plane of the table (XY) and the saggital plane of torso (XZ) were examined for both reaches to a cup and to a spoon. Velocity profiles and curvature were also quantified for all trajectories. RESULTS: We hypothesized that movements performed with functional task constraints and objects would deviate from the minimum jerk trajectory model more than those performed under imaginary or object absent conditions. Trajectory deviations from the predicted minimum jerk model for these reaches were shown to depend on three variables: object presence, object orientation, and plane of movement. When subjects completed the cup reach their movements were more curved than for the spoon reach. The object present condition for the cup reach showed more curvature than in the object imagined and absent conditions. Curvature in the XZ plane of movement was greater than curvature in the XY plane for all movements. CONCLUSION: The implemented minimum jerk trajectory model was not adequate for generating functional trajectories for these ADLs. The deviations caused by object affordance and functional task constraints must be accounted for in order to allow subjects to perform functional task training in robotic therapy environments. The major differences that we have highlighted include trajectory dependence on: object presence, object orientation, and the plane of movement. With the ability to practice ADLs on the ADLER environment we hope to provide patients with a therapy paradigm that will produce optimal results and recovery

SPARC: a matricellular regulator of tumorigenesis

Although many clinical studies have found a correlation of SPARC expression with malignant progression and patient survival, the mechanisms for SPARC function in tumorigenesis and metastasis remain elusive. The activity of SPARC is context- and cell-type-dependent, which is highlighted by the fact that SPARC has shown seemingly contradictory effects on tumor progression in both clinical correlative studies and in animal models. The capacity of SPARC to dictate tumorigenic phenotype has been attributed to its effects on the bioavailability and signaling of integrins and growth factors/chemokines. These molecular pathways contribute to many physiological events affecting malignant progression, including extracellular matrix remodeling, angiogenesis, immune modulation and metastasis. Given that SPARC is credited with such varied activities, this review presents a comprehensive account of the divergent effects of SPARC in human cancers and mouse models, as well as a description of the potential mechanisms by which SPARC mediates these effects. We aim to provide insight into how a matricellular protein such as SPARC might generate paradoxical, yet relevant, tumor outcomes in order to unify an apparently incongruent collection of scientific literature

Management of Soil-Borne Diseases of Grain Legumes Through Broad-Spectrum Actinomycetes Having Plant Growth-Promoting and Biocontrol Traits

Chickpea (Cicer arietinum L.) and pigeonpea (Cajanus cajan L.) are the two important grain legumes grown extensively in the semiarid tropics (SAT) of the world, where soils are poor in nutrients and receive inadequate/erratic rainfall. SAT regions are commonly found in Africa, Australia, and South Asia. Chickpea and pigeonpea suffer from about 38 pathogens that cause soil-borne diseases including wilt, collar rot, dry root rot, damping off, stem canker, and Ascochyta/Phytophthora blight, and of which three of them, wilt, collar rot, and dry root rot, are important in SAT regions. Management of these soil-borne diseases are hard, as no one control measure is completely effective. Advanced/delayed sowing date, solarization of soil, and use of fungicides are some of the control measures usually employed for these diseases but with little success. The use of disease-resistant cultivar is the best efficient and economical control measure, but it is not available for most of the soil-borne diseases. Biocontrol of soil-borne plant pathogens has been managed using antagonistic actinobacteria, bacteria, and fungi. Actinobacterial strains of Streptomyces, Amycolatopsis, Micromonospora, Frankia, and Nocardia were reported to exert effective control on soil-borne pathogens and help the host plants to mobilize and acquire macro- and micronutrients. Such novel actinomycetes with wide range of plant growth-promoting (PGP) and antagonistic traits need to be exploited for sustainable agriculture. This chapter gives a comprehensive analysis of important soil-borne diseases of chickpea and pigeonpea and how broad-spectrum actinomycetes, particularly Streptomyces spp., could be exploited for managing them

1996 International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) The Rio File Cache: Surviving Operating System Crashes

Abstract: One of the fundamental limits to high-performance, high-reliability file systems is memory’s vulnerability to system crashes. Because memory is viewed as unsafe, systems periodically write data back to disk. The extra disk traffic lowers performance, and the delay period before data is safe lowers reliability. The goal of the Rio (RAM I/O) file cache is to make ordinary main memory safe for persistent storage by enabling memory to survive operating system crashes. Reliable memory enables a system to achieve the best of both worlds: reliability equivalent to a write-through file cache, where every write is instantly safe, and performance equivalent to a pure write-back cache, with no reliability-induced writes to disk. To achieve reliability, we protect memory during a crash and restore it during a reboot (a “warm ” reboot). Extensive crash tests show that even without protection, warm reboot enables memory to achieve reliability close to that of a write-through file system. Adding protection makes memory even safer than a writethrough file system while adding essentially no overhead. By eliminating reliability-induced disk writes, Rio performs 4-22 times as fast as a write-through file system, 2-14 times as fast as a standard Unix file system, and 1-3 times as fast as an optimized system that risks losing 30 seconds of data and metadata.

The rio file cache: Surviving operating system crashes

Abstract: One of the fundamental limits to high-perfor-mance, high-reliability file systems is memory's vulnerabil-ity to system crashes. Because memory is viewed as unsafe, systems periodically write data back to disk. The extra disk traffic lowers performance, and the delay period before data is safe lowers reliability. The goal of the Rio (RAM I/O) file cache is to make ordinary main memory safe for persistent storage by enabling memory to survive operating system crashes. Reliable memory enables a system to achieve the best of both worlds: reliability equivalent to a write-through file cache, where every write is instantly safe, and perfor-mance equivalent to a pure write-back cache, with no reli-ability-induced writes to disk. To achieve reliability, we protect memory during a crash and restore it during a reboot (a "warm " reboot). Extensive crash tests show that even without protection, warm reboot enables memory to achieve reliability close to that of a write-through file system. Add-ing protection makes memory even safer than a write-through file system while adding essentially no overhead. By eliminating reliability-induced disk writes, Rio performs 4-22 times as fast as a write-through file system, 2-14 times as fast as a standard Unix file system, and 1-3 times as fast as an optimized system that risks losing 30 seconds of data and metadata.