Digital Pen is Better Dementia-Prediction Tool than a Doctor

Digital Pen Technology – Dementia Prediction Tool

A digital pen technology, which is a new dementia prediction tool, can diagnose conditions earlier and with great accuracy. The invention is based on a method of screening for cognitive damage, known as clock-drawing test. Individuals are made to draw a clock which shows the time as 11.10 and then copy a pre-drawn clock showing the same time.

The test reveals how they perform when it comes to verbal and understanding, memory as well as spatial knowledge, which is used to ascertain conditions like Parkinson and Alzheimer. The team behind the study of the latest digital pen, desire to find a way to automate the test, to speed up the diagnoses but also to remove doctor subjectivity and possibly help with earlier diagnoses by utilising more detailed data indicators.

With the use of the Anoto Live Pen, that measures a ballpoint position of a tip, 80 times a second with an inbuilt camera, the team from MITs Computer Science and Artificial Intelligence Laboratory, Lahey Hospital together with many other universities all over the US, were capable of collecting data from around 2,600 tests which had been performed over nine years.

The Digital Clock Drawing Test - dCDT

The data was used by the team to build specialised software to create the digital Clock Drawing Test – dCDT. They observed that it was far more accurate in delivering a diagnosis than the equivalent original,which depends on a doctor’s subjective interpretation of the drawings.

Some of it could be due to the fact that the dCDT takes in more than the finished drawings and provides other indicators which tend to depend on the process of drawing the clock. In this case the team noticed that those with memory impairments took more time thinking on the drawing prior to drawing than those without the disorder.

Those affected with Parkinson also took longer to draw clocks which were usually on the smaller side. According toMIT’s Cynthia Rudin, who commented on MIT News, states that `they have improved the analysis in order that it is automated and objective and with the right equipment, they can get results wherever needed, quickly and with higher accuracy’.

Save Manual Hours Spent in Diagnosing

They are expecting that the test will save on the manual hours spent in diagnosing or possibly misdiagnosing, a disorder which is of vital importance, taking into consideration the duration of time it can take in diagnosing neurological conditions like Alzheimer’s with anumber of various tests and processes.

Since the procedures utilised in the dCDT tends to be trained on more data, the team is also hoping that it will be able to pick up on new indicators they are discovering faster like the case of hesitation and the drawing technique enabling an even earlier diagnoses, established on thousands of test results that have been carried over the years.

The team writes that `while the models will need additional testing for validation, they offer the opportunity of considerable improvement in detecting intellectual impairment earlier than presently possible, a development with considerable possible impact in practice.