Kinelab: A flexible software platform
for measuring manual dexterity

A bespoke, tablet-based software platform that presents interactive visual
stimuli and autonomously analyses movement data.

Client: Bradford Institute for Health Research

WINNER of the 2016 Engineering Impact Award
for Innovative Research

Features and Benefits

  • Cross-referencing of user interface fields with database data eliminates the possibility of input errors
  • Built-in statistical analyses enables benchmarking of each pupil’s performance relative to their age range
  • Automatically-generated reports provide immediate diagnostic feedback to teachers, pupils and parents
ReSolve provided a software solution that enabled us to roll out detailed child cognitive assessments on a large scale across multiple sites, authenticating a child’s identity in the field for secure data linkage, while keeping the child’s personal data safe. We have been hugely impressed by their expertise and partnership. Brilliant!

– Professor John Wright, Chief Investigator, Bradford Institute for Health Research

Winner of the Engineering Impact Award for Innovative Research

We are proud to announce that our Kinelab case study won the National Instruments 2016 Engineering Impact Award for Innovative Research in the Northern European Region.  We’re now in the global finals, which take place at NI Week in Austin, Texas in May 2017. You can read the case study submission here.

The Challenge

The Born in Bradford (BiB) project, nested within the UK’s National Health Service (NHS) is one of the world’s largest scientific studies. The project involves tracking the health of 13,500 children from birth to adulthood to understand the childhood influences that shape health and wellbeing. An important part of the study requires the assessment of manual dexterity and cognitive capacity —two critical aspects of a child’s development—to understand how a child’s motor skills affect the ability to carry out essential, everyday tasks (for example, handwriting) and the impact that related deficits have on a child’s social and emotional wellbeing. Previous techniques for measuring cognitive-motor function ranged from basic and time-consuming pen and paper techniques, to the use of accurate but complicated and costly laboratory equipment. The key requirements for Kinelab were to provide an easily configurable, rugged, and portable platform to collect kinematic measurements rapidly during the presentation of interactive visual stimuli to children aged 4-12 years.

Our Approach

Building on an existing software platform, our role in the project was to increase the functionality and robustness of the application to facilitate data collection on an unprecedented scale. Some of the key work areas are outlined next.

Eliminating operator error

To protect the personal data of 13,500 children, the operator does not have direct access to the database. This could be problematic if errors are made when entering data into the user interface. We needed a robust method of cross-checking user interface fields against the database. We solved this by ensuring that all fields populate automatically when a unique pupil number and date of birth match the database. After confirming a child’s details, the operator can start the trial by pressing ‘play.’ This simple yet effective method safeguards against the possibility of entering incorrect data. Since implementing the database cross-referencing functionality there have been no erroneous inputs into the front panel, which has potentially saved hundreds of hours of post-processing time to correct operator errors manually and match data to individual children.

Running external ‘games’ with Kinelab

To complement the comprehensive capabilities of Kinelab, we can now call executables developed in other environments such as Python in Kinelab using the LabVIEW System Exec function. This allows for quick and easy integration of third-party tasks by passing data seamlessly from LabVIEW to the external applications and vice versa to significantly reduce the development time needed to recreate the same games in LabVIEW.

Statistical analyses and report generation

We combine and process the raw metrics obtained from Kinelab to create summary scores for each task. We used the statistical analysis functions in LabVIEW to compare each child’s scores against all other children through a database. Storing raw and processed results makes it possible for researchers to revisit the data and carry out further analyses.

It is imperative that teachers and pupils receive immediate, non-technical feedback to help identify areas for improvement of the pupil’s skills. We use the LabVIEW report generation toolkit to populate a custom Microsoft Excel template automatically; thus, generating a printable feedback PDF report for each child immediately after testing.