Handwriting is a constant cognitive-motor job that requires high skill and cerebral engagement during development . Handwriting is a simple and familiar pastime for almost all literate individuals, and it has been shown to be a valuable biomarker. Indeed, the coordinated operation of the brain, in conjunction with the neuromuscular and visual systems, is essential for writing performance. This deteriorates in all older persons to some extent, and it deteriorates significantly more when neurological disease is present .
As a result, the examination of this commonplace action has been used to assess various disorders. In neurology, kinematic analysis of handwriting has been employed as a clinical tool that may detect even minor dysfunctions, making it particularly effective in the evaluation of Parkinson's disease (PD) , Dystonia , and Huntington's disease .
Handwriting analysis, due to its fine motor character, has proven to be a particularly valuable method in the examination of tremor . Furthermore, handwriting was examined in order to distinguish between different levels of severity in terms of age-related cognitive deterioration . In light of this, identifying age-related variations in handwriting is critical because it may help distinguish physiological variation caused by aging from aberrant alterations caused by neurological disorders or cognitive loss.
To record the subject's writing outcome, early work used an ink pen and a paper notepad . On the one hand, this method can be regarded useful in the clinical setting because it is simple and does not require the assistance of a technician.The assessment of the paper-and-pen technique, on the other hand, necessitates the expertise of a clinical professional to evaluate the writing outcome without the support of any quantitative data: this approach does not meet the current needs of health systems that rely on telemedicine's achievements to solve problems like limited availability of specialists, reduced time to conduct such tests, and the difficulty for some patients—especially the elderly—to complete such tests. As a result, digitizers and tablets capable of returning the 2-Dtrajectory of the writing trace have largely supplanted the paper-and-pen technique in recent research , , . Data digitization enables for the extraction of quantitative parameters for objectively assessing handwriting and remote monitoring of the user's performance.
However, such an approach is questioned because it forces the user to write on a small surface (usually that of a tablet) that is not the standard writing surface, so undermining the naturalness of the motion . As a result, because the experimental context does not reflect the real-world occurrence, this approach lacks ecological validity . Furthermore, the usage of such technology may not be simple, especially when dealing with elderly users, necessitating the technical assistance of an operator.
We created a revolutionary smart ink pen that allows users to write on a common sheet of paper while capturing motion and force data, combining the ecological validity of the first approach with the quantitative assessment provided by contemporary technologies.The ink pen is equipped with a force sensor that measures the normal force applied to the pen tip while writing, as well as inertial sensors that capture motion and tremor data during the writing job. The pen was meant to automatically collect data when it was used to improve usability. An ad hoc software was built to facilitate telemonitoring by instantly downloading writing data and computing relevant handwriting and tremor indicators. Another aspect of our approach's novelty is the protocol's ecological validity and transparency. Unlike the great majority of research , , , in which handwriting is studied under controlled conditions (with the participant copying or writing previously determined text), we chose to provide tasks that mimicked everyday writing without limiting the writing mode or topic.
In terms of sensors, inertial signals are collected using three-dimensional linear accelerometers and gyroscopes (LSM6DSM iNEMO 6DoF), while the writing force exerted on the tip is measured using a miniaturized load cell (FC8E by Forsentek; 1.6 mm; 50-N capacity) mounted with the lower face pressing on the refill stopper. PCB2 contains a Panasonic Corporation, Osaka, Japan, rechargeable Li-ion p-i-n-type battery with a coaxial power connector accessible from the pen cap and a battery protection circuit. The preamplification circuit for the load cell data is located on PCB3, which has a rounded shape and is inserted in the load cell holder. Because the pen is self-operated via movement detection or BLE connection request, the enduser does not have access to an activation button. Despite this, an LED is visible to display the pen's operating mode and battery level. All of the electronics are housed in a 3-D printed plastic shell that keeps them safe and secure.