IoT ink pen for ecological monitoring of daily life handwriting

The analysis of the writing gesture has been successfully investigated in the diagnosis of age-related diseases, but the current technologies and methods still do not allow the ecological daily monitoring of handwriting, mostly because they rely on standardized writing protocols. In this study, we first designed and validated a novel electronic ink pen, equipped with motion and writing force sensing, for the ecological daily-life monitoring of handwriting in uncontrolled environments. We used the pen to acquire writing activities from healthy adults, from which we computed useful handwriting and tremor indicators. We evaluated the reliability of our measurements by computing the intraclass correlation coefficients (ICC) and the minimal detectable changes (MDC). Moderate to excellent reliability were obtained for all the handwriting indicators computed in two different writing tasks. MDC values can be used as reference to discriminate a real change in the handwriting parameters from a measurement error in longitudinal studies. These results pave the way towards the use of the pen for daily life handwriting monitoring