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Detecting stress patterns based on physiological measurements in real-life scenarios using existing wearables

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Detecting stress patterns based on physiological measurements in real-life scenarios using existing wearables

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Samenvatting

During the last decades there has been an uprising in stress related health problems. To counter this growing problem, a system is proposed to detect stress events at an individual level. These events can then be used as feedback in efforts to prevent chronic stress symptoms from developing.
To detect stress, test subjects are monitored using the Huawei Watch 2’s PPG signal. This signal was used in combination with a peak detection algorithm to determine heart rate and HRV parameters. A group of (lecturing) staff is monitored during a controlled test sequence using STROOP and MAT(H) tests.
The heart rate and RMSSD/SDNN features show most separation power between rest and stress phases. Test subjects did not respond to proposed test sequence as expected. Therefore classification based on gathered datasets could not accurately be determined with sufficient statistical backing.
Afterwards the test subjects were monitored for at least five days. Data gathered from this field test does show possible stress events and stress trend lines. Further studies should look into improvements to test setup, test sequence and test subject selection.

Toon meer
OrganisatieHanzehogeschool Groningen
OpleidingMaster Sensor Technology
AfdelingInstituut voor Engineering
Jaar2019
TypeMaster
TaalEngels

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