TY - JOUR
T1 - Beyond fitness tracking
T2 - The use of consumer-grade wearable data from normal volunteers in cardiovascular and lipidomics research
AU - Lim, Weng Khong
AU - Davila, Sonia
AU - Teo, Jing Xian
AU - Yang, Chengxi
AU - Pua, Chee Jian
AU - Blöcker, Christopher
AU - Lim, Jing Quan
AU - Ching, Jianhong
AU - Yap, Jonathan Jiunn Liang
AU - Tan, Swee Yaw
AU - Sahlén, Anders
AU - Chin, Calvin Woon Loong
AU - Teh, Bin Tean
AU - Rozen, Steven G.
AU - Cook, Stuart Alexander
AU - Yeo, Khung Keong
AU - Tan, Patrick
N1 - Publisher Copyright:
© 2018 Lim et al.
PY - 2018/2/27
Y1 - 2018/2/27
N2 - The use of consumer-grade wearables for purposes beyond fitness tracking has not been comprehensively explored. We generated and analyzed multidimensional data from 233 normal volunteers, integrating wearable data, lifestyle questionnaires, cardiac imaging, sphingolipid profiling, and multiple clinical-grade cardiovascular and metabolic disease markers. We show that subjects can be stratified into distinct clusters based on daily activity patterns and that these clusters are marked by distinct demographic and behavioral patterns. While resting heart rates (RHRs) performed better than step counts in being associated with cardiovascular and metabolic disease markers, step counts identified relationships between physical activity and cardiac remodeling, suggesting that wearable data may play a role in reducing overdiagnosis of cardiac hypertrophy or dilatation in active individuals. Wearable-derived activity levels can be used to identify known and novel activity-modulated sphingolipids that are in turn associated with insulin sensitivity. Our findings demonstrate the potential for wearables in biomedical research and personalized health.
AB - The use of consumer-grade wearables for purposes beyond fitness tracking has not been comprehensively explored. We generated and analyzed multidimensional data from 233 normal volunteers, integrating wearable data, lifestyle questionnaires, cardiac imaging, sphingolipid profiling, and multiple clinical-grade cardiovascular and metabolic disease markers. We show that subjects can be stratified into distinct clusters based on daily activity patterns and that these clusters are marked by distinct demographic and behavioral patterns. While resting heart rates (RHRs) performed better than step counts in being associated with cardiovascular and metabolic disease markers, step counts identified relationships between physical activity and cardiac remodeling, suggesting that wearable data may play a role in reducing overdiagnosis of cardiac hypertrophy or dilatation in active individuals. Wearable-derived activity levels can be used to identify known and novel activity-modulated sphingolipids that are in turn associated with insulin sensitivity. Our findings demonstrate the potential for wearables in biomedical research and personalized health.
UR - https://www.scopus.com/pages/publications/85043683008
U2 - 10.1371/journal.pbio.2004285
DO - 10.1371/journal.pbio.2004285
M3 - 文章
C2 - 29485983
AN - SCOPUS:85043683008
SN - 1544-9173
VL - 16
JO - PLoS Biology
JF - PLoS Biology
IS - 2
M1 - e2004285
ER -