Finger Biometrics with Applications in Psychiatry
ISEF · 2021 Biomedical Engineering
Overview
What is the connection between a psychiatric illness and upper limb motility? The present paper aims to identify specific motility of the upper limb in connection with the sphere of psychiatric diseases. Regarding the procedures used, they consisted on the one hand in a theoretical analysis about the anatomy and physiology of the hand and the nervous system, but also in their application in psychiatry - testing and diagnostic methods, interpretation of psychiatric language and behavioral and emotional symptoms. On the other hand, the experimental part of the project is divided into three categories: dynamometer experiments, experiments with piezoelectric sensors and experiments with resolver. The order is not random, but gradual, from the lowest degree of generality to the highest. The study is based on two main books in the field - Diagnostic and Statistical manual of mental disorders, 4th edition (DSM-IV) and Clinical Psychiatry - Kaplan and Sadock (Pocket Manual). The interpretation of the project, in its early stages, consisted in the fact that the nature of mental disorders and uncontrolled hand movements have partially the same nature, but also their direct identification (for example Rett disorder or Parkinson's disease).Subsequently, we tested different characters of these motility such as stability, sensitivity, periodicity incorporated in a series of tests pin games. The conclusions drawn from the research were that people suffering from mental illness can be identified in a simpler and more accurate biometric way, with an important applicability in the field of medicine.
Competition history
- ISEF 2021
Resources
Related projects
ISEF · 2024
Breaking Diagnostic Barriers: Migraines Diagnosis and Handwriting Analysis
ISEF · 2015
The Mapping of Emotional Dimensions: Toward a Neuro-Thermal Biometric System for the Diagnosis of Emotional Flexibility
ISEF · 2019
Development of Software for Mental Illness Diagnostics: Facial Expression Classification through Machine Learning
ISEF · 2018
FacePrint: A Novel, Differential Diagnostic and Monitoring Tool for Parkinson’s Disease, Essential Tremor, and Atypical Parkinsonism Using Facial Behavioral Biomarkers and Dynamic Video Footage Tracking with Machine Learning
Closest projects by meaning, across every fair and year in the corpus.
Source: Regeneron International Science and Engineering Fair