TY - CONF
T1 - Towards Wearable Sensing Enabled Healthcare Framework for Elderly Patients
AU - Sodhro, Ali Hassan
AU - Obaidat, Mohammad S.
AU - Gurtov, Andrei
AU - Zahid, Noman
AU - Pirbhulal, Sandeep
AU - Wang, Lei
AU - Hsiao, Kuei Fang
N1 - Funding Information:
This work is funded by CENIIT project 17.01 Computer and Information Science department, Linkoping University, Linkoping, Sweden, and in part by PIFI 2020 under project number 2020BVC0002,Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences (SIAT,CAS), Shenzhen, and also by PR of China Ministry of Education Distinguished Possessor Grant given to Prof. Obaidat under number: MS2017BJKJ003. Besides,this work is partially supported by Operao Centro-01-0145-FEDER000019C4-Centro de Com-petłncias em Cloud Computing, co-financed by the Programa Operacional Regional do Centro (CENTRO 2020), through the Sistema de Apoio Investigao Cientfica e Tecnolgica Programas Integrados de ICDT
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - The pervasive and smart healthcare is important for elderly patients which has revolutionized the medical world and caught the attention from industry and academia with the help of portable sensor-enabled devices. Tiny size and resource-constrained nature restricts them to perform several tasks at a time. Thus, energy drain, limited battery lifetime, and high packet loss ratio (PLR) are the key challenges to be tackled carefully for ubiquitous healthcare. Energy efficiency, reliability and longer battery cycle are the vital ingredients for wearable devices to empower cost-effective and pervasive medical environment. Thus, this research work has three key contributions. First, a novel transmission power control driven energy efficient algorithm (EEA) is proposed to enhance energy, battery lifetime and reliability while monitoring the health status of elderly patients. Proposed EEA and conventional constant transmission power control (TPC) are evaluated by adopting real-time datasets of static (i.e., wheelchair sitting) and dynamic (i.e., wheelchair moving) body postures of elderly patients. Second, smart healthcare framework is proposed. Third, performance metrics such as, energy drain, battery lifetime and reliability are introduced and calculated by considering average and threshold RSSI and TPC values. Finally, it is observed through experimental analysis that the proposed EEA enhances energy efficiency with acceptable PLR than the constant TPC during data transmission.
AB - The pervasive and smart healthcare is important for elderly patients which has revolutionized the medical world and caught the attention from industry and academia with the help of portable sensor-enabled devices. Tiny size and resource-constrained nature restricts them to perform several tasks at a time. Thus, energy drain, limited battery lifetime, and high packet loss ratio (PLR) are the key challenges to be tackled carefully for ubiquitous healthcare. Energy efficiency, reliability and longer battery cycle are the vital ingredients for wearable devices to empower cost-effective and pervasive medical environment. Thus, this research work has three key contributions. First, a novel transmission power control driven energy efficient algorithm (EEA) is proposed to enhance energy, battery lifetime and reliability while monitoring the health status of elderly patients. Proposed EEA and conventional constant transmission power control (TPC) are evaluated by adopting real-time datasets of static (i.e., wheelchair sitting) and dynamic (i.e., wheelchair moving) body postures of elderly patients. Second, smart healthcare framework is proposed. Third, performance metrics such as, energy drain, battery lifetime and reliability are introduced and calculated by considering average and threshold RSSI and TPC values. Finally, it is observed through experimental analysis that the proposed EEA enhances energy efficiency with acceptable PLR than the constant TPC during data transmission.
KW - constant TPC
KW - Elderly heathcare
KW - Smart
KW - Wearable Sensing Technology
U2 - 10.1109/ICC40277.2020.9149286
DO - 10.1109/ICC40277.2020.9149286
M3 - Paper
AN - SCOPUS:85089417325
T2 - 2020 IEEE International Conference on Communications, ICC 2020
Y2 - 7 June 2020 through 11 June 2020
ER -
