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Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor–A Preliminary Study
Abstract
The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment.
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
SENSORS
no. 18(10),
pages 1 - 14,
ISSN: 1424-8220 - Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Tomczak M. T., Wójcikowski M., Listewnik P., Pankiewicz B., Majchrowicz D., Szczerska M.: Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor–A Preliminary Study// SENSORS. -Vol. 18(10), iss. 3530 (2018), s.1-14
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/s18103530
- Verified by:
- Gdańsk University of Technology
Referenced datasets
- dataset Short-term measurement of physiological parameters - child (2)
- dataset Long-term measurement of physiological parameters - a teenager (60 minutes) - the 2nd serie
- dataset Long-term measurement of physiological parameters - adult (120 minutes)
- dataset Long-term measurement of physiological parameters - a teenager (105 minutes)
- dataset Long-term measurement of physiological parameters - a teenager (100 minutes)
- dataset Long-term measurement of physiological parameters - an adult (100 minutes)
- dataset Long-term measurement of physiological parameters - an adult (70 minutes)
- dataset Long-term measurement of physiological parameters - a teenager (60 min)
- dataset Long-term measurement of physiological parameters - an adult (60 minutes)
- dataset Long-term measurement of physiological parameters - child (120 min)
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