Arousal level classification of the aging adult from electro-dermal activity: From hardware development to software architecture

作者：Martinez Rodrigo Arturo^*; Zangroniz Roberto; Manuel Pastor Jose; Sokolova Marina V

来源：Pervasive and Mobile Computing, 2017, 34: 46-59.

DOI：10.1016/j.pmcj.2016.04.006

• Wearable
• Electro-dermal activity
• Stress quantification
• Ambient intelligence

The fast aging of the population around the world makes ambient intelligence-based assistive technologies essential for sustainable and efficient health-care systems. Aging adults who decide to live alone at home need constant monitoring to control their health status and quality of life. This work introduces a new wearable device that continuously monitors the emotional state of the elderly. Electro-dermal activity (EDA) is used to classify the aging adults into two groups: sleepiness and stressed. The results report a performance of more than 83% of accuracy by using exclusively time and magnitude features from EDA events.

• 出版日期2017-1