Resumé
| Originalsprog | Engelsk |
|---|---|
| Titel | NordiCHI 2018 : Revisiting the Life Cycle - Proceedings of the 10th Nordic Conference on Human-Computer Interaction |
| Antal sider | 14 |
| Forlag | Association for Computing Machinery |
| Publikationsdato | 1 okt. 2018 |
| Sider | 170-183 |
| ISBN (Elektronisk) | 978-1-4503-6437-9 |
| DOI | |
| Status | Udgivet - 1 okt. 2018 |
| Begivenhed | NordiCHI 2018 - Oslo, Norge Varighed: 1 okt. 2018 → 3 okt. 2018 |
Konference
| Konference | NordiCHI 2018 |
|---|---|
| Land | Norge |
| By | Oslo |
| Periode | 01/10/2018 → 03/10/2018 |
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It’s not Complicated : A Study of Non-Specialists Analyzing GSR Sensor Data to Detect UX Related Events. / Bruun, Anders.
NordiCHI 2018: Revisiting the Life Cycle - Proceedings of the 10th Nordic Conference on Human-Computer Interaction. Association for Computing Machinery, 2018. s. 170-183.Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review
TY - GEN
T1 - It’s not Complicated
T2 - A Study of Non-Specialists Analyzing GSR Sensor Data to Detect UX Related Events
AU - Bruun, Anders
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Emotion is a key factor in understanding user experiences (UX) of interactive systems. An emerging trend within HCI is to apply physiological sensors for uncovering emotions. Previous studies rely on various sophisticated analysis techniques and specialized knowledge to interpret sensor data. While commendable for increasing accuracy at fine grained latencies (to detect events within seconds), this can be challenging for UX practitioners without specialized knowledge. This study contributes in two ways. Firstly by understanding the level of sensor accuracy in detecting UX related events. Secondly by applying a basic analysis approach where sensor data is interpreted by 21 non-specialist participants (no previous experience in doing this). Their performance is compared to random guessing. Findings show that sensor data analyzed by non-specialists are significantly more accurate in capturing subjectively reported UX events than random guessing. An accuracy level of 60-80% was obtained at granularities within 3.5-11 seconds of UX related events.
AB - Emotion is a key factor in understanding user experiences (UX) of interactive systems. An emerging trend within HCI is to apply physiological sensors for uncovering emotions. Previous studies rely on various sophisticated analysis techniques and specialized knowledge to interpret sensor data. While commendable for increasing accuracy at fine grained latencies (to detect events within seconds), this can be challenging for UX practitioners without specialized knowledge. This study contributes in two ways. Firstly by understanding the level of sensor accuracy in detecting UX related events. Secondly by applying a basic analysis approach where sensor data is interpreted by 21 non-specialist participants (no previous experience in doing this). Their performance is compared to random guessing. Findings show that sensor data analyzed by non-specialists are significantly more accurate in capturing subjectively reported UX events than random guessing. An accuracy level of 60-80% was obtained at granularities within 3.5-11 seconds of UX related events.
KW - Emotion
KW - GSR
KW - Non-specialists
KW - Orienting responses
KW - Physiological sensors
KW - Sensor Data Analysis
KW - Subjective
UR - http://www.scopus.com/inward/record.url?scp=85056580964&partnerID=8YFLogxK
U2 - 10.1145/3240167.3240183
DO - 10.1145/3240167.3240183
M3 - Article in proceeding
SP - 170
EP - 183
BT - NordiCHI 2018
PB - Association for Computing Machinery
ER -