Wearable light data logger for studying physiological and psychological effects of light data
Light sensors can provide valuable information about environmental exposure; however, current light sensing packages are limited. This work presents the development of an open-source hardware device capable of logging light measurements. Due to its lightweight, wearable construction, it is well-suit...
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2020-10-01
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doaj-013c9cde96584913943c155f6983d0d92020-12-25T05:11:14ZengElsevierHardwareX2468-06722020-10-018e00157Wearable light data logger for studying physiological and psychological effects of light dataMatthew B. Rhudy0Nathan Greenauer1Catherine Mello2Mechanical Engineering, Division of Engineering, Business, and Computing, The Pennsylvania State University, Berks, Reading, PA 19610, USA; Corresponding author.Applied Psychology, Division of Humanities, Arts, and Social Sciences, The Pennsylvania State University, Berks, Reading, PA 19610, USAApplied Psychology, Division of Humanities, Arts, and Social Sciences, The Pennsylvania State University, Berks, Reading, PA 19610, USA; Rehabilitation and Human Services, Division of Humanities, Arts, and Social Sciences, The Pennsylvania State University, Berks, Reading, PA 19610, USALight sensors can provide valuable information about environmental exposure; however, current light sensing packages are limited. This work presents the development of an open-source hardware device capable of logging light measurements. Due to its lightweight, wearable construction, it is well-suited to human subject research in naturalistic conditions. Its low cost makes it a viable option for population studies. This work offers an example application of objectively determining whether a person is indoors or outdoors based on the light measurements. This application has practical value within disciplines such as environmental and health psychology, which seek to relate psychological outcomes to environmental exposure.http://www.sciencedirect.com/science/article/pii/S2468067220300663ArduinoData loggerLight |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Matthew B. Rhudy Nathan Greenauer Catherine Mello |
spellingShingle |
Matthew B. Rhudy Nathan Greenauer Catherine Mello Wearable light data logger for studying physiological and psychological effects of light data HardwareX Arduino Data logger Light |
author_facet |
Matthew B. Rhudy Nathan Greenauer Catherine Mello |
author_sort |
Matthew B. Rhudy |
title |
Wearable light data logger for studying physiological and psychological effects of light data |
title_short |
Wearable light data logger for studying physiological and psychological effects of light data |
title_full |
Wearable light data logger for studying physiological and psychological effects of light data |
title_fullStr |
Wearable light data logger for studying physiological and psychological effects of light data |
title_full_unstemmed |
Wearable light data logger for studying physiological and psychological effects of light data |
title_sort |
wearable light data logger for studying physiological and psychological effects of light data |
publisher |
Elsevier |
series |
HardwareX |
issn |
2468-0672 |
publishDate |
2020-10-01 |
description |
Light sensors can provide valuable information about environmental exposure; however, current light sensing packages are limited. This work presents the development of an open-source hardware device capable of logging light measurements. Due to its lightweight, wearable construction, it is well-suited to human subject research in naturalistic conditions. Its low cost makes it a viable option for population studies. This work offers an example application of objectively determining whether a person is indoors or outdoors based on the light measurements. This application has practical value within disciplines such as environmental and health psychology, which seek to relate psychological outcomes to environmental exposure. |
topic |
Arduino Data logger Light |
url |
http://www.sciencedirect.com/science/article/pii/S2468067220300663 |
work_keys_str_mv |
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