A Novel Cooperation-Based Network Coding Scheme for Walking Scenarios in WBANs

Zhang, Hongyun; Safaei, Farzad; Tran, Le Chung

doi:10.1155/2017/6267579

Cited by 9 publications

(14 citation statements)

References 27 publications

(38 reference statements)

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“…The correlation coefficient (R) is another statistical analysis that can reflect the correlation between two variables. Correlation coefficient values range between 1 and −1 according to the "Cauchy-Schwarz inequality" [55]. In this paper, it was used to estimate the correlation between AWHMS and BM measurements.…”

Section: Correlation Coefficient Testmentioning

confidence: 99%

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

Fakhrulddin

Gharghan

2019

JSAN

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Falls are a main cause of injury for patients with certain diseases. Patients who wear health monitoring systems can go about daily activities without limitations, thereby enhancing their quality of life. In this paper, patient falls and heart rate were accurately detected and measured using two proposed algorithms. The first algorithm, abnormal heart rate detection (AHRD), improves patient heart rate measurement accuracy and distinguishes between normal and abnormal heart rate functions. The second algorithm, TB-AIC, combines an acceleration threshold and monitoring of patient activity/inactivity functions to accurately detect patient falls. The two algorithms were practically implemented in a proposed autonomous wireless health monitoring system (AWHMS). The AWHMS was implemented based on a GSM module, GPS, microcontroller, heartbeat and accelerometer sensors, and a smartphone. The measurement accuracy of the recorded heart rate was evaluated based on the mean absolute error, Bland–Altman plots, and correlation coefficients. Fourteen types of patient activities were considered (seven types of falling and seven types of daily activities) to determine the fall detection accuracy. The results indicate that the proposed AWHMS succeeded in monitoring the patient’s vital signs, with heart rate measurement and fall detection accuracies of 98.75% and 99.11%, respectively. In addition, the sensitivity and specificity of the fall detection algorithm (both 99.12%) were explored.

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Section: Correlation Coefficient Testmentioning

confidence: 99%

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

Fakhrulddin

Gharghan

2019

JSAN

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“…The main function of these transceivers is to transmit and receive continuous data packets to/from each other and record the received signal strength indicator (RSSI) values into a micro SD card. More detailed description of the hardware can be found in [6][7][8].…”

Section: Measurement Setupsmentioning

confidence: 99%

“…Different from other typical wireless radio channels, a large number of factors may result in the severe attenuation (over 100 dB has been observed) in WBAN channels. These factors include diffraction, reflection, energy absorption and consumption, antenna losses, shadowing by the body tissue, and body posture [2][3][4][5][6][7]. It has been demonstrated by many research works, such as [8,9], that the shadowing effect from the human body is the dominant factor that leads to the severe attenuation.…”

Section: Introductionmentioning

confidence: 99%

Channel autocorrelation-based dynamic slot scheduling for body area networks

Zhang

Safaei

Tran

2018

J Wireless Com Network

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As a promising technology in the context of m-health and e-medical, wireless body area networks (WBANs) have a stringent requirement in terms of transmission reliability. Meanwhile, the wireless channel in WBANs is prone to deep fading due to multiple reasons, such as shadowing by the body, reflection, diffraction, and interference. To meet the challenge in transmission reliability, the dynamic slot scheduling (DSS) methods have attracted considerable interest in recent years. DSS method does not require extra hardware or software overhead on the sensor side. Instead, the hub optimizes the time-division multiple access slots by selecting the best permutation at the beginning of each superframe to improve the transmission reliability. However, most existing DSS works optimize the time slot scheduling based on a two-state ("good" or "bad") Markov channel model, which is insufficient for human daily life scenarios with a variety of irregular activities. In this paper, we first collect the channel gain data in the real human daily scenarios and analyze the autocorrelation of wireless channels based on this real database. Motivated by the significant temporal autocorrelation, we then propose a new DSS method, which applies a temporal autocorrelation model to predict the channel condition for future time slots. The new method is designed to be compatible with IEEE 802.15.6 standard. Compared to the classical Markov model-based methods, simulation results show that the newly proposed DSS method achieves up to 12.9% reduction in terms of packet loss ratios.

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“…Instead of utilizing the distance-based formula to quantify the path loss [2], we adopt channel gain datasets collected from the real daily scenarios. The portable wireless transceivers introduced in [3], [4] are used to collect the channel gain data. We adopt the energy consumption model in network simulator Castalia [5], which is one of the most accurate energy models for WBANs.…”

Section: System Modelmentioning

confidence: 99%

Autocorrelation Based Transmission Power Control in WBANs

Zhang

Safaei

Tran

2018

2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)

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In this paper, we propose an autocorrelation-based transmission power control (A-TPC) method to increase the transmission reliability and reduce the energy consumption. In A-TPC, data packets from multiple sensor nodes are scheduled in the TDMA-fashion. The transmission power level and the slot scheduling are jointly optimized based on a temporal autocorrelation model. The channel datasets collected from real WBAN daily scenarios are imported into our simulation model to evaluate the performance of A-TPC. Simulation results demonstrate that A-TPC significantly improves the transmission reliability and reduces the energy consumption.Abstract-In this paper, we propose an autocorrelation-based transmission power control (A-TPC) method to increase the transmission reliability and reduce the energy consumption. In A-TPC, data packets from multiple sensor nodes are scheduled in the TDMA-fashion. The transmission power level and the slot scheduling are jointly optimized based on a temporal autocorrelation model. The channel datasets collected from real WBAN daily scenarios are imported into our simulation model to evaluate the performance of A-TPC. Simulation results demonstrate that A-TPC significantly improves the transmission reliability and reduces the energy consumption.

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A Novel Cooperation-Based Network Coding Scheme for Walking Scenarios in WBANs

Cited by 9 publications

References 27 publications

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

An Autonomous Wireless Health Monitoring System Based on Heartbeat and Accelerometer Sensors

Channel autocorrelation-based dynamic slot scheduling for body area networks

Autocorrelation Based Transmission Power Control in WBANs

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