iCalm: wearable sensor and network architecture for wirelessly communicating and logging autonomic activity

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Affective Computing

Background:

• Affective sensing in healthcare is hindered by costly, uncomfortable sensors and lack of wireless standards.
• Existing wearable technology often fails to provide continuous, long-term physiological data collection.

Purpose of the Study:

• To develop a novel, low-cost, low-power wireless sensor platform for affective sensing.
• To enable long-term, continuous monitoring of physiological and motion data in various populations.
• To overcome practical limitations in current wearable healthcare technologies.

Main Methods:

• Implementation of a wireless sensor platform using the IEEE 802.15.4 standard.
• Design of compact wearable sensors for electrodermal activity, temperature, motor activity, and photoplethysmography.
• System validation through continuous, long-term data collection from infants, children, and adults.

Main Results:

• Successful development of a low-cost, low-power wireless sensor platform.
• Demonstration of long-term monitoring capabilities for autonomic nervous system and motion data.
• Presentation of data from wearable designs for wrist and foot applications.

Conclusions:

• The developed sensor platform addresses key limitations in affective sensing for healthcare.
• This technology facilitates new applications for continuous physiological and motion monitoring.
• The system offers a practical solution for long-term wearable health data acquisition.