A real time efficient & secure patient monitoring based on Wireless Body Area Networks

2016 ◽  
Author(s):  
Neema Anna Anoop ◽  
T.K. Parani
Keyword(s):  
Real Time ◽  
Patient Monitoring ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Body Area

scholarly journals Fuzzy-Based Dynamic Time Slot Allocation for Wireless Body Area Networks

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2112 ◽  
Author(s):  
Sangeetha Pushpan ◽  
Bhanumathi Velusamy
Keyword(s):  
Real Time ◽  
Energy Efficient ◽  
Patient Monitoring ◽  
Time Slot ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Slot Allocation ◽  
Body Area ◽  
Time Slot Allocation ◽  
Dynamic Time

With the advancement in networking, information and communication technologies, wireless body area networks (WBANs) are becoming more popular in the field of medical and non-medical applications. Real-time patient monitoring applications generate periodic data in a short time period. In the case of life-critical applications, the data may be bursty. Hence the system needs a reliable energy efficient communication technique which has a limited delay. In such cases the fixed time slot assignment in medium access control standards results in low system performance. This paper deals with a dynamic time slot allocation scheme in a fog-assisted network for a real-time remote patient monitoring system. Fog computing is an extended version of the cloud computing paradigm, which is suitable for reliable, delay-sensitive life-critical applications. In addition, to enhance the performance of the network, an energy-efficient minimum cost parent selection algorithm has been proposed for routing data packets. The dynamic time slot allocation uses fuzzy logic with input variables as energy ratio, buffer ratio, and packet arrival rate. Dynamic slot allocation eliminates the time slot wastage, excess delay in the network and attributes a high level of reliability to the network with maximum channel utilization. The efficacy of the proposed scheme is proved in terms of packet delivery ratio, average end to end delay, and average energy consumption when compared with the conventional IEEE 802.15.4 standard and the tele-medicine protocol.

A Statistical-Based Light-Weight Anomaly Detection Framework for Wireless Body Area Networks

2021 ◽  
Author(s):  
Smrithy G S ◽  
Ramadoss Balakrishnan
Keyword(s):  
Anomaly Detection ◽  
Patient Monitoring ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Physiological Parameters ◽  
Light Weight ◽  
Remote Patient Monitoring ◽  
Body Area ◽  
Statistical Measures ◽  
Remote Patient

Abstract In healthcare scenario, the major challenge in anomaly detection for remote patient monitoring is to classify true medical conditions and false alarms. This paper proposes a light-weight anomaly detection (LWAD) framework for detecting anomalies in remote patient monitoring based on wireless body area networks. The proposed framework uses distance correlation for finding correlated (both linear and non-linear) physiological parameters. It also uses a statistical-based improvised dynamic sliding window algorithm for efficient short-range prediction of physiological parameters. Finally, the proposed LWAD framework detects anomalies using anomaly detection framework based on robust statistical techniques. The validation of LWAD framework is performed using three real time datasets with various statistical measures. The proposed LWAD framework outperforms existing methods.

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