Pen-Type Electrodermal Activity Sensing System for Stress Detection Based on Likelihood Ratios.
IEEE Trans Biomed Circuits Syst
; 15(6): 1467-1476, 2021 12.
Article
en En
| MEDLINE
| ID: mdl-34855600
ABSTRACT
Psychological stress experienced during academic testing is a significant performance factor for some students. While a student may be able to recognize and self-report exam stress, unobtrusive tools to track stress in real time and in association with specific test problems are lacking. This effort pursued the design and initial assessment of an electrodermal activity (EDA) sensor mounted to a pen/pencil 'trainer' a holder into which a pen/pencil is inserted that can help a person learn how to properly grip a writing instrument. This small assembly was held in the hand of each subject during early experiments and can be used for follow-on, mock test-taking scenarios. In these experiments, data were acquired with this handheld device for each of 36 subjects (Kansas State University Internal Review Board Protocol #9864) while they viewed approximately 30 minutes of emotion-evoking videos. Data collected by the EDA sensor were analyzed by an EDA signal processing app, which calculated and stored parameters associated with significant phasic EDA peaks while allowing intermediate peak detection processes to be visualized. These peak data were then subjected to a hypothesis driven stress-detection test that employed likelihood ratios to identify 'relaxed' versus 'stressed' events. For these initial testing scenarios, which were free of hand motions, this pen-type EDA sensing system discerned 'relaxed' versus 'stressed' phasic responses with 87.5% accuracy on average, where subject self-assessments of perceived stress levels were used to establish ground truth.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Procesamiento de Señales Asistido por Computador
/
Respuesta Galvánica de la Piel
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
IEEE Trans Biomed Circuits Syst
Año:
2021
Tipo del documento:
Article