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Measuring Academic Stress ‘In the Wild’ with Wearable Sensors: Removal of Noise from Wearable Sensor Data Using Fir Filters

Harris, B, Dobbins, C, Fairclough, SH and Lisboa, P Measuring Academic Stress ‘In the Wild’ with Wearable Sensors: Removal of Noise from Wearable Sensor Data Using Fir Filters. In: 1st Neuroadaptive Technology Conference 2017 (NAT’17), 19 July 2017 - 21 July 2017, Berlin, Germany. (Accepted)

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Abstract

Psychological concepts, such as anxiety, can be measured ‘in the wild’ using a range of wearable sensors. The measurement of psychophysiological signals in the field naturally includes a number of confounds such as noise, artefacts and baseline wander. Before getting a general idea of what may be possible from working with the data, it is necessary to use data conditioning methods to remove these unwanted influences.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Applied Mathematics (merged with Comp Sci 10 Aug 20)
Computer Science & Mathematics
Natural Sciences & Psychology (closed 31 Aug 19)
Publisher: Elsevier ??
Date Deposited: 17 May 2017 10:45
Last Modified: 13 Apr 2022 15:15
URI: https://researchonline.ljmu.ac.uk/id/eprint/6435
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