THINKPEN – A SMART PEN FOR HANDWRITING ANALYSIS
Handwriting analysis is an important tool for the diagnosis and monitoring of the progression of pathologies or alterations affecting the nervous system in both children and the elderly. THInkPen is a sensorized pen that allows for a non-invasive procedure and an ecological monitoring of data relating to handwriting and hand tremors. The device is connected to a telemedicine platform, which allows for the remote monitoring of patients.
The act of writing requires the coordination of both cognitive and motor functions. For this reason, its analysis has become an important tool for diagnosing and monitoring the progress of neurodegenerative diseases, altered developmental states in children, and age-related conditions. However, the current systems used in this field have some technical disadvantages: they are complex, require the support of qualified personnel during testing procedures, and can often lead to distorted results due to their reliance on smart pen-tablet systems, which can have both positive and negative effects on the user. THInkPen solves these issues by inserting sensors into an instrument used for everyday writing, making it impossible for the user to notice that they are being tested, and thus guaranteeing total ecological monitoring.
THInkPen is instrumented with inertial IMU sensors (accelerometers, gyroscopes, magnetometers and force sensor) to measure the acceleration and the amplitude of the hand movement whilst writing and the pressure exerted on the pen tip on the paper. These measurements allow the calculation of clinical index to diagnose and monitor neurodegenerative pathologies.
- Autonomous and non-supervised monitoring of handwriting;
- Monitoring and early diagnosis of Parkinson’s disease;
- Monitoring of dysgraphia in children;
- Diagnosis and progress monitoring of dementia.
- Ecological monitoring of handwriting;
- Easy to use;
- Can be used without the support of qualified personnel;
- Ecological capture: no on/off button, automatic data logging.