© 2023 Parkinson’s Foundation (Australia)
How KeySense Works
There has been a need for more accurate and objective
diagnoses of Parkinson’s Disease (PD), particularly in its
early stages where the observable symptoms may be
subtle and imprecise.
In order to be effective, such a new assessment technique
needs to -
•
Be significantly more accurate than current non-
specialist clinician diagnoses.
•
Provide an objective, quantifiable and repeatable diag-
nostic test for PD.
•
Be able to diagnose PD where there are just mild symp-
toms present.
•
Be able to detect it significantly earlier in the disease
progression.
•
Not require specialised equipment, training or referral.
•
Take place in the patient’s home or office environment
as they type normally on a computer.
•
Also be capable of providing ongoing monitoring of
medication, treatments & disease progression.
KeySense Methodology
This involves the use of typing – by analyzing the rhythm
and cadence of keystrokes as someone types on a
keyboard.
There is a wealth of information embedded in those
keystroke. Way back in the mid-19th century, when the
telegraph was in wide use, telegraph operators could iden-
tify other operators based on their rhythm as they tapped
on the telegraph key. Much later, during World War II, a
methodology known as the ‘Fist of the Sender’ was used to
identify the sender of the telegraph by using the rhythm,
pace and cadence of their Morse code. Even without
decoding the messages, this allowed German troop move-
ments to be monitored by the Allied Powers, as particular
telegraph operators were attached to a specific army unit.
These days, as someone types on a computer keyboard,
the characteristics of their finger movement can be
measured down to millisecond accuracy.
KeySense Development
•
It has been based on 4 years of peer-reviewed scientific
research, with nearly 500 worldwide participants and
9,000 typing samples.
•
Capture & recording of keystroke characteristics as
someone types normally on a computer keyboard.
•
Detection of 4 separate types of PD feature, especially
two of the cardinal features for clinical diagnosis -
bradykinesia & tremor.
•
Use of sophisticated artificial intelligence (AI) machine
learning models.
As implemented, the technique provides objective, quan-
tifiable, repeatable measurements and results.
The Outcome
Provides a tool for both detection & ongoing monitoring of
disease status and progression. The patient can take the
assessment reports to their medical practitioner (GP) or
specialist.
KeySense has a high and repeatable accuracy, with an 86%
detection rate for even early, mild symptoms of
Parkinson’s, and just 5% false positives. This compares with
GP accuracies of less than 75% across all disease severities,
and much lower than that for early, mild cases.
The User Assessment Process
The user types 350 words of text (two thirds of a page) on
their own computer and KeySense records a myriad of
timings about their finger movement.
This data is then fed through a series of machine learning
models which identify the probabilities of specific move-
ment features being within – or outside – normal expected
ranges. Specifically, KeySense measures inconsistency,
drop-off and sidedness of movement and tremor, as well
as combining these into an overall score.
The results are accompanied by descriptive details which
are also emailed to the user.
Privacy and Anonymity
The KeySense assessment does not need any personal
details to be provided and the participants remain anony-
mous at all times.
GET STARTED NOW
See
whether
the
way
you
type
shows
any
indications
of
early
Parkinson’s
Disease.
Less
than
a
page
is
needed
for
immediate
analysis,
based
on
characteris
-
tics and rhythms in your typing.
YOU NEED TO BE USING A DEVICE WITH A PHYSICAL
KEYBOARD THOUGH. SO GO TO A LAPTOP OR
DESKTOP COMPUTER & RE-VISIT
WWW.PARKINSONS-RESEARCH.ORG