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A Smart Ink Pen for the Ecological Assessment of Age-Related Changes in Writing and Tremor Features
- Publication Year :
- 2020
-
Abstract
- We present the development of a novel smart ink pen instrumented with force and motion sensors designed for the quantitative and ecological assessment of daily-life handwriting. This work aims at testing the pen’s sensors and algorithms and the use of the smartpen to detect age-related changes in writing and tremor parameters during daily-life handwriting. A comparison against reference instruments was carried out to validate the pen tip force during static and dynamic conditions, the pen’s tilt angle, and the algorithm for the segmentation of the force signal into strokes. The smartpen was tested on 43 healthy adults divided into three age groups (young, middle-old, and old) during unconstrained handwriting on paper. The validation of the pen’s sensors and algorithms reported excellent results. A solid test–retest reliability was found in the writing and tremor indicators extracted from both young and old adults. As for the age-related analysis, the older age groups were characterized by an increase of temporal writing measures, a more uniform writing pressure, and more repetitive and predictable tremor oscillation components. The greatest accomplishment of our smart ink pen is the ability to combine the advantages of the digitizing tablet technology with the natural “feel,” the ease of use, and the ecological validity of the traditional pen-and-paper approach. The proposed solution represents an important step toward a simple, ecologically valid, reliable quantitative assessment of daily-life handwriting. Our smartpen is particularly suitable for daily-life telemonitoring applications in a number of important health-related fields.
- Subjects :
- Inkwell
Computer science
business.industry
020208 electrical & electronic engineering
Work (physics)
Usability
02 engineering and technology
Handwriting
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
business
Instrumentation
Reliability (statistics)
Graphics tablet
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....c24debef056fa492c271f958dbd79106