Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Observing walking behavior of humans using distributed phenomenon detection and tracking mechanisms
AU - Bose, Raja
AU - Helal, Sumi
PY - 2008
Y1 - 2008
N2 - The utility of walking parameters such as stride length, cadence and gait velocity for monitoring motor functions of patients suffering from brain injury, Parkinson's disease and obesity is well established. The application of sensor networks in this context has also been actively researched however; most of the research has focused either on construction of formal models of walking or design of wearable monitors. Unfortunately these approaches are not always practical for real-life monitoring, since they either require users to continuously wear monitoring equipment or rely on mathematical models which can be susceptible to significant prediction errors. In this paper we propose distributed mechanisms which utilize the concept of phenomenon detection and tracking for monitoring walking parameters. Our mechanisms do not require patients to be encumbered with monitoring devices and can track a subject's walk in real-time, in an energy efficient manner without a priori knowledge of a fixed mathematical model, thereby making it suitable for practical deployments. © 2008 IEEE.
AB - The utility of walking parameters such as stride length, cadence and gait velocity for monitoring motor functions of patients suffering from brain injury, Parkinson's disease and obesity is well established. The application of sensor networks in this context has also been actively researched however; most of the research has focused either on construction of formal models of walking or design of wearable monitors. Unfortunately these approaches are not always practical for real-life monitoring, since they either require users to continuously wear monitoring equipment or rely on mathematical models which can be susceptible to significant prediction errors. In this paper we propose distributed mechanisms which utilize the concept of phenomenon detection and tracking for monitoring walking parameters. Our mechanisms do not require patients to be encumbered with monitoring devices and can track a subject's walk in real-time, in an energy efficient manner without a priori knowledge of a fixed mathematical model, thereby making it suitable for practical deployments. © 2008 IEEE.
KW - Applications
KW - Energy efficiency
KW - Functions
KW - Internet
KW - Mathematical techniques
KW - Mechanisms
KW - Network protocols
KW - Sensor networks
KW - A-priori
KW - Brain injury
KW - Detection and tracking
KW - Energy-efficient
KW - Formal modeling
KW - International symposium
KW - Monitoring devices
KW - Parkinson's disease
KW - Prediction errors
KW - Walking behavior
KW - Wear monitoring
KW - Mathematical models
U2 - 10.1109/SAINT.2008.88
DO - 10.1109/SAINT.2008.88
M3 - Conference contribution/Paper
SN - 9780769532974
SP - 405
EP - 408
BT - 2008 International Symposium on Applications and the Internet, SAINT 2008
PB - IEEE
ER -