mSpider

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively

About the technology

Data collection of physical data from study participants is time consuming and expensive. State of the art is moving towards the use of data from consumer-based equipment. However, since there are many vendors with separate method for extracting data, there is a need for a system that can handle this data collection in a more automatic way. mSpider is a tool where health researchers can register participants, after which the system will automatically handle the data extraction.

mSpider is compatible with the major consumer-based activity trackers such as Fitbit, Garmin etc and other smart equipment. The system can upload both historic and future data. Although mSpider has been developed as a research tool in mind, its application areas also include remote patient monitoring in terms of long-term physical activity.

Value proposition

  • Sensor agnostic, supports all major devices
  • Fully automatic
  • Ready to use, does not require any programming resources
  • Prototype tested and used in several
    research projects

Resources and partners

  • Department of Computer Science, UiT.
  • RESTART, a NFR (336341) funded RCT
  • mSpider is currently used as research
    infrastructure at UiT
Image: mSpider is compatible with the major consumer-based activity trackers such as Fitbit, Garmin etc and other smart equipment. The system can upload both historic and future data.

Opportunities for Collaboration

We are currently looking for industry partners or potential users who finds interest in our technology. We are open for working together on the development of mSpider to accommodate your needs.

Partners

Universitetet i Tromsø

Contact information

Foto: Marius Fiskum

Ingrid Skjæveland

Forretningsutvikler | Tech Transfer

ingrid@norinnova.no
Tlf. 991 57 143

Les om andre prosjekter:

mSpider

•
16. november 2023

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively About the technology Data collection of physical data …

Thyroid Assist

•
8. november 2023

– A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy About the technology Levothyroxine is a necessary synthetic …

, ,

FiRsT – Optical microscope calibration targets

•
8. november 2023

About the technology New and advanced label-free and super resolution microscopes and nanoscopes have emerged, and their characterization is becoming more demanding. …

,

Nanospacer

•
30. oktober 2023

– Bringing nanofluidic technology to the people About the technology The Nanospacer is a specially designed microscope coverslip that allows nanoscale particle …

, , ,

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

,

Novel platform for live-imaging of cells in action

•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,

Thyroid Assist

- A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy

About the technology

Levothyroxine is a necessary synthetic hormone after removal of the thyroid gland, or in patients with an underactive tyroid gland. The optimal dosage varies between individuals, making several rounds of dose adjustments required. Due to long half-life of the hormone, it commonly takes 6-12 months for patients to finish their dose adjustment.

We have developed a decision support tool (DST) that calculates a dosage proposal for each individual patient. The invention shortens the time to arrive at the right medical dose for patients after surgery. This is acheived by repeatedly measuring the concentration of hormones in the blood for 2 weeks, and then using these data as input to a model, along with biodata. This new method can replace a long standing clinical practice with long intervals between dosage adjustments. The future goal is to adapt the model so it can also be used for all patients with all kinds of thyroid disorders.

Value proposition

  • 50% reduced time to correct dose
  • Patients quality of life improved
  • Can be performed at GPs office
  • High patient complience
  • Cost effective

Resources and partners

  • Clinically tested in a randomised multicentre study (Brun et al 2021. Intern. Federation for Medical and Biological Engineering Proceedings, Springer. 76:1264-1269)
  • Clinical validation studies ongoing
  • University Hospital of Northern Norway (UNN)
  • SINTEF
  • UiT The Arctic University of Norway
Image: With Thyroid Assist the time needed to achieve correct TSH levels is shortened significantly.

Opportunities for Collaboration

We are currently looking for industry partners or potential users who find interest in our technology. We are open for working together on the development of the DST to accommodate your needs.

Partners

Universitetet i Tromsø

Contact information

Foto: Marius Fiskum

Ingrid Skjæveland

Forretningsutvikler | Tech Transfer

ingrid@norinnova.no
Tlf. 991 57 143

Les om andre prosjekter:

mSpider

•
16. november 2023

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively About the technology Data collection of physical data …

Thyroid Assist

•
8. november 2023

– A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy About the technology Levothyroxine is a necessary synthetic …

, ,

FiRsT – Optical microscope calibration targets

•
8. november 2023

About the technology New and advanced label-free and super resolution microscopes and nanoscopes have emerged, and their characterization is becoming more demanding. …

,

Nanospacer

•
30. oktober 2023

– Bringing nanofluidic technology to the people About the technology The Nanospacer is a specially designed microscope coverslip that allows nanoscale particle …

, , ,

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

,

Novel platform for live-imaging of cells in action

•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,

SPICE: Sea sPray ICE prediction model

A tool that predicts ice amount and distribution on marine structures

About the technology

Due to climate changes the Arctic marine territories are opening up for new and widespread industry activities such as aquaculture, new shipping pathways, offshore wind-energy harness and so on. However, icing of marine structures is a big challenge affecting operations. SPICE is a machine learning model that can predict the amount and distribution of ice on different structures including those on marine vessels, due to freezing sea spray in cold conditions. Leveraging novel sea spray flux algorithms and models developed at UiT, SPICE represent a leap forward in state of the art of ice prediction from sea spray.

User of Technology

  • Marine vessel designers
  • Shipping companies
  • Off-shore companies operating in cold climates
  • Certification companies such as the DNV Group AS

Value proposition

  • Fully automated
  • Predicts ice distribution depending on specific structures
  • Predicts both amount and distribution of ice
  • Based on 108k datapoints from more than 30 climate controlled experiments ensures high accuracy
  • Validated in lab scale

Resources and partners

  • Department of Building, Energy and Material Technology , UiT
  • Demo of tool available
Image: Icing of marine structures is a big challenge due to freezing sea spray in cold conditions.

Collaboration partners

Universitetet i Tromsø

Opportunities for Collaboration

We are currently looking for industry partners who finds interest in our technology. We are open for working together on the development of SPICE to accommodate your needs.

Contact information

Foto: Marius Fiskum

Ingrid Skjæveland

Forretningsutvikler | Tech Transfer

ingrid@norinnova.no
Tlf. 991 57 143

Les om andre prosjekter:

mSpider

•
16. november 2023

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively About the technology Data collection of physical data …

Thyroid Assist

•
8. november 2023

– A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy About the technology Levothyroxine is a necessary synthetic …

, ,

FiRsT – Optical microscope calibration targets

•
8. november 2023

About the technology New and advanced label-free and super resolution microscopes and nanoscopes have emerged, and their characterization is becoming more demanding. …

,

Nanospacer

•
30. oktober 2023

– Bringing nanofluidic technology to the people About the technology The Nanospacer is a specially designed microscope coverslip that allows nanoscale particle …

, , ,

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

,

Novel platform for live-imaging of cells in action

•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,

MUSICAL – Multiple Signal Classification Algorithms

- Multi-option distributed computing solutions for super-resolution imaging

The MUSICAL technology

MUSICAL is an imaging software that makes super-resolution optical microscopy available to specialized labs and clinics as a high-end premium GPU or embedded solution, or to laymans with their own personal microscopy data through an budget-conscious cloud solution.

The technology can be applied to both super-resolution microscopy raw data as well as data generated by conventional low-cost microscopes. The key advantage it provides is not needing any calibration in illumination engineered microscopes or special dyes for achieving super-resolution.

MUSICAL processing method to exploit the high spatial frequencies of illumination pattern to generate super-resolved image. In other words, processing super-resolution images from microscopes at an immense speed.

The MUSICAL solutions

  • Cloud solution (Beta-stage)

Lightweight software for super-resolution imaging tailored to low-cost microscopes.

  • GPU solution (under development)

Plug-and-play dongle providing state-of-the-art imaging with an additional edge in processing time

  • Embedded solution (to be developed)

MUSICAL as a built-in hardware solution with the microscope. Unlocking it’s full imaging capabilities

Opportunities for collaboration

  • Licensees for MUSICAL cloud solution
  • Collaborative R&D with industrial partner for MUSICAL GPU or MUSICAL Embedded solution
  • Patent pending
As compared to diffraction-limited image on the left, MUSICAL reconstructs the cristae (i.e., the empty spaces between the outer and inner membranes of mitochondria) with amazing number of details using only 100 images of diffraction-limited video.

Collaboration partners

Universitetet i Tromsø

Contact information

Foto: Marius Fiskum

Lars Sørensen

Forretningsutvikler | Tech Transfer

lars@norinnova.no
Tlf. 942 45 511

Les om andre prosjekter:

mSpider

•
16. november 2023

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively About the technology Data collection of physical data …

Thyroid Assist

•
8. november 2023

– A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy About the technology Levothyroxine is a necessary synthetic …

, ,

FiRsT – Optical microscope calibration targets

•
8. november 2023

About the technology New and advanced label-free and super resolution microscopes and nanoscopes have emerged, and their characterization is becoming more demanding. …

,

Nanospacer

•
30. oktober 2023

– Bringing nanofluidic technology to the people About the technology The Nanospacer is a specially designed microscope coverslip that allows nanoscale particle …

, , ,

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

,

Novel platform for live-imaging of cells in action

•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,

Novel and easy to use Deep Learning Input Function in dynamic PET scanning

- Deep Learning derived Input Function in dynamic PET

About the technology

With DLIF we present a non-invasive, automatically generated input-function for kinetic modelling in dynamic PET. Our deep learning models are trained end-to-end with dynamic PET images as input and ready-to-use input function as output. The model show very strong correlation and non-significant difference in influx (Ki) for myocardium and tumor derived with AIF and DLIF, respectively.

Value proposition

  • No surgery requirements
  • Compatible with any PET scanner and the most widely used tracers
  • Provides results that are highly accurate with less bias and variation than state of the art

Areas of application

  • Non-invasive input function for dynamic PET where blood sampling is not possible
  • Preclinical or clinical applications
  • Could be integrated into external software independent of PET scanner vendor
  • As a part of the PET scanner-software to deliver the DLIF together with the PET images

Resources and partners

  • The Norwegian Nuclear Medicine Consortium 180°N
  • Tromsø Research Foundation ​
  • Centre for Research-based Innovation (SFI) Visual Intelligence
  • Proof of concept validated for small scale research in mice

Comparison to state of the art technology

Image: Comparison model of DLIF and existing state of the art technology.

Opportunities for Collaboration

We are currently looking for industry partners who finds interest in our technology. We are open for working together on the development of DLIF to accommodate your needs.

Collaboration partners

Universitetet i Tromsø
TFS_FARGE_NOR-HOR

Contact information

Foto: Marius Fiskum

Ingrid Skjæveland

Forretningsutvikler | Tech Transfer

ingrid@norinnova.no
Tlf. 991 57 143

Les om andre prosjekter:

mSpider

•
16. november 2023

Motivating continous Sharing of Physical activity using non-Intrusive Data Extraction methods Retro- and prospectively About the technology Data collection of physical data …

Thyroid Assist

•
8. november 2023

– A novel decision support aid tool (DST) for optimal levothyroxine dosage after thyroidectomy About the technology Levothyroxine is a necessary synthetic …

, ,

FiRsT – Optical microscope calibration targets

•
8. november 2023

About the technology New and advanced label-free and super resolution microscopes and nanoscopes have emerged, and their characterization is becoming more demanding. …

,

Nanospacer

•
30. oktober 2023

– Bringing nanofluidic technology to the people About the technology The Nanospacer is a specially designed microscope coverslip that allows nanoscale particle …

, , ,

SPICE: Sea sPray ICE prediction model

•
11. august 2023

A tool that predicts ice amount and distribution on marine structures About the technology Due to climate changes the Arctic marine territories …

,

Novel platform for live-imaging of cells in action

•
9. august 2023

CYMOPLIVE – Cyto-Motility and Cyto-Plasticity in Vitro Live-Cell Assay About the technology Cymoplive is a platform that allows us to study cells …

, ,