TY - GEN
T1 - AutoSense
T2 - 9th ACM Conference on Embedded Networked Sensor Systems, SenSys 2011
AU - Ertin, Emre
AU - Stohs, Nathan
AU - Kumar, Santosh
AU - Raij, Andrew
AU - Al'Absi, Mustafa
AU - Shah, Siddharth
AU - Mitra, Somnath
AU - Kwon, Taewoo
AU - Jeong, Jae Woong
PY - 2011
Y1 - 2011
N2 - The effect of psychosocial stress on health has been a central focus area of public health research. However, progress has been limited due a to lack of wearable sensors that can provide robust measures of stress in the field. In this paper, we present a wireless sensor suite called AutoSense that collects and processes cardiovascular, respiratory, and thermoregularity measurements that can inform about the general stress state of test subjects in their natural environment. AutoSense overcomes several challenges in the design of wearable sensor systems for use in the field. First, it is unobtrusively wearable because it integrates six sensors in a small form factor. Second, it demonstrates a low power design; with a lifetime exceeding ten days while continuously sampling and transmitting sensor measurements. Third, sensor measurements are robust to several sources of errors and confounds inherent in field usage. Fourth, it integrates an ANT radio for low power and integrated quality of service guarantees, even in crowded environments. The AutoSense suite is complemented with a software framework on a smart phone that processes sensor measurements received from AutoSense to infer stress and other rich human behaviors. AutoSense was used in a 20+ subject real-life scientific study on stress in both the lab and field, which resulted in the first model of stress that provides 90% accuracy.
AB - The effect of psychosocial stress on health has been a central focus area of public health research. However, progress has been limited due a to lack of wearable sensors that can provide robust measures of stress in the field. In this paper, we present a wireless sensor suite called AutoSense that collects and processes cardiovascular, respiratory, and thermoregularity measurements that can inform about the general stress state of test subjects in their natural environment. AutoSense overcomes several challenges in the design of wearable sensor systems for use in the field. First, it is unobtrusively wearable because it integrates six sensors in a small form factor. Second, it demonstrates a low power design; with a lifetime exceeding ten days while continuously sampling and transmitting sensor measurements. Third, sensor measurements are robust to several sources of errors and confounds inherent in field usage. Fourth, it integrates an ANT radio for low power and integrated quality of service guarantees, even in crowded environments. The AutoSense suite is complemented with a software framework on a smart phone that processes sensor measurements received from AutoSense to infer stress and other rich human behaviors. AutoSense was used in a 20+ subject real-life scientific study on stress in both the lab and field, which resulted in the first model of stress that provides 90% accuracy.
KW - deployment experiences
KW - mobile health
KW - psychological stress monitoring
KW - wearable physiological sensors
UR - http://www.scopus.com/inward/record.url?scp=83455176188&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=83455176188&partnerID=8YFLogxK
U2 - 10.1145/2070942.2070970
DO - 10.1145/2070942.2070970
M3 - Conference contribution
AN - SCOPUS:83455176188
SN - 9781450307185
T3 - SenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
SP - 274
EP - 287
BT - SenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Y2 - 1 November 2011 through 4 November 2011
ER -