This technology is an e-health application. The DragONE application is inspired by the global guidelines for the management of asthma, which promote the opportunity to implement a multidimensional assessment of pediatric asthma using innovative systems. DragONE allows to record data on the subjective control of asthma, by using easy-to-understand colors and icons for children (red, yellow or green dragon), to keep track to the patient’s of perceived state.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 1 - 9 of 9
Our innovative proposal involves an educational robotics training program, resulting from an experimental research that combines traditional educational approaches with the utilization of robotics. Specifically, the educational robot Thymio, developed by EPFL, serves as a facilitator in the learning process to enhance School Readiness.
Plants have a huge potential to contribute to the solution of a large number of issues facing the modern world, ranging from a poor crop yields and problems caused by global climate changing. Our team has been on the forefront of the PCR and NGS applications to plant responses to biotic and abiotic stress. As experts in genomics and plant pathology we are able to accelerate the understanding and use of plant genes and resources.
We have identified the presence of the poorly characterized precursor proNGF-A in human tissues, deposited its coding nucleotide sequence (GenBank MH358394) and demonstrated its neuroprotective and neurotrophic activity in vitro and in vivo. We inserted mutations into the native molecule, identified through computational analysis, which allow proNGF-A production by eukaryotic expression systems, through a method currently validated on a laboratory scale.
The prototype uses soil moisture sensors which, through a measurement of dielectric permittivity, estimate the soil moisture based on which irrigation is started through relay-controlled solenoid valve. The system was developed using Open Source technologies. Specifically, for the hardware components, a small sized board computer Raspberry PI 3B + was used together with a 4G LTE Wi-Fi router and a Modbus rs485 / USB converter.
To the enterprises working in the field of nutrition/nutraceutics and drug development/repositioning, we offer the know-how and state-of-the-art instrumentation of our labs to monitor multiple relevant biological parameters at the cellular level: metabolic activity, vitality, health, but also stress and toxicity. The use of advanced imaging techniques based on fluorescent/bioluminescent probes together with the availability of time-lapse acquisitions, guarantee the cutting-edge analysis of different biological parameters over time.
The invention consists in a special regulation method of the horizontal axes of operating and rubbing wheels of a centerless grinding machine coupled with an opportune blade profile, allowing a continuous regulation of blade rest angle (angle between tangent to blade profile at the contact point with the work piece and the horizon, denoted by γ) and workpiece height (denoted by hw), without requiring blade substitution and/or manual regulations.
SITODIET is an innovative software that supports a translational approach to health’s state. It integrates various sources of physiological, behavioral, and psychological data to reduce the risks associated with the onset of lifestyle-related diseases (primary prevention), to support health professionals in early diagnosis (secondary prevention) or to manage the personalized therapy’s patient (tertiary prevention). SITODIETcollects data automatically, through actigraphy tools, as wristband or smartwatch, or manually
This form describes a programmable, autonomous and stand-alone imaging system for the acquisition and processing of images containing subjects whose size is larger than 1cm (e.g. gelatinous zooplankton, fishes, litter, manufacts), form the seafloor or along the water column, in shallow or deep waters. It is capable to recognize and classify the image content through pattern recognition algorithms that combine computer vision and artificial intelligence methodologies.