TY - GEN
T1 - IC-SAFE:Intelligent Connected Sensing Approaches for the Elderly
AU - Summers, Alexa
AU - Choi, Sarah
AU - Gummadavelly, Manasa Leela
AU - Choi, Baek Young
AU - Song, Sejun
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Senior citizens, young children, and people with age-related diseases, often find it hard to express themselves. They are not fully aware of their need for help, or how to ask for assistance. This lack of awareness decreases the quality of life, and even endangers those individuals.IC-SAFE (Intelligent Connected Sensing Approaches for the Elderly) tracks the safety of the elderly by using various connected smart wearable sensors. IC-SAFE collects motion data, including walking gaits, arm and leg tremors, and long lounging positions, from many lightweight body sensors to identify the safety status (both physical and emotional) of dementia patients. Feasibility tests have been performed using IMU (Inertial Measurement Unit) sensors in various positions and data from these experiments has been gathered. We have proposed efficient real-time algorithms using analytical learning methods and identified several safety target scenarios by analyzing the corresponding gait data.
AB - Senior citizens, young children, and people with age-related diseases, often find it hard to express themselves. They are not fully aware of their need for help, or how to ask for assistance. This lack of awareness decreases the quality of life, and even endangers those individuals.IC-SAFE (Intelligent Connected Sensing Approaches for the Elderly) tracks the safety of the elderly by using various connected smart wearable sensors. IC-SAFE collects motion data, including walking gaits, arm and leg tremors, and long lounging positions, from many lightweight body sensors to identify the safety status (both physical and emotional) of dementia patients. Feasibility tests have been performed using IMU (Inertial Measurement Unit) sensors in various positions and data from these experiments has been gathered. We have proposed efficient real-time algorithms using analytical learning methods and identified several safety target scenarios by analyzing the corresponding gait data.
UR - http://www.scopus.com/inward/record.url?scp=85137263213&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85137263213&partnerID=8YFLogxK
U2 - 10.1109/ICC45855.2022.9838309
DO - 10.1109/ICC45855.2022.9838309
M3 - Conference contribution
AN - SCOPUS:85137263213
T3 - IEEE International Conference on Communications
SP - 4661
EP - 4666
BT - ICC 2022 - IEEE International Conference on Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Communications, ICC 2022
Y2 - 16 May 2022 through 20 May 2022
ER -