System architecture of intelligent personal communication node for body sensor network

Yi, Won-Jae; Niu, Sufeng; Gonnot, Thomas; Saniie, Jafar

doi:10.1109/i2mtc.2013.6555708

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…There are four major components in our system design: wireless sensor nodes, a central node known as the W-iPCN, an Android smartphone, and a central database server. In this paper, we use the notion of the W-iPCN as a central node to communicate with the wireless sensor nodes and the Android smartphone, and integrate all collected sensor data [15]. The customized Android software application can be loaded to any standard Android smartphone to interface with the central W-iPCN via the Bluetooth connection, and to transmit valuable physiological and surrounding environmental information to the central database server via the Internet connection.…”

Section: System Design Overviewmentioning

confidence: 99%

“…Standard smartphones on the market today are equipped with at least quad-core ARM RISC processors with an average clock speed at 2.0 GHz and 2 GB RAM.We have evaluated the feasibility of the smartphone as a data processing device, and it proves that it is possible to perform computationally intense operations on the Android smartphone[15] [31]. Also, it is possible to connect with the wireless sensor nodes to receive real-time sensor data[32].…”

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confidence: 99%

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Patient Centered Real-Time Mobile Health Monitoring System

Yi¹,

Saniie²

2016

ETSN

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In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients' activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients' detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients' health condition. This system also includes the capability for assessing patients' posture and fall detection.

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Section: System Design Overviewmentioning

confidence: 99%

mentioning

confidence: 99%

Patient Centered Real-Time Mobile Health Monitoring System

Yi¹,

Saniie²

2016

ETSN

Self Cite

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“…The absolute phase θ of two modulations are shown in TABLE.IV and TABLE.V. According to (6) and 7, current θ can be decided by the previous one and phase increment. Finally, the modulation process is completed by looking up the two tables.…”

Section: A Modulationmentioning

confidence: 99%

“…It is a communication network which is composed of various network nodes distributed in, on or around human body [1]- [3], including personal terminal, sensors and networking devices. Currently, BAN is mainly used in patient care and physiological parameters measurement [4]- [6]. Through BAN, the measured parameters can be transferred to portable personal electronic devices such as PDA, mobile phones and even remote information center in the hospital for medical care or treatment.…”

Section: Introductionmentioning

confidence: 99%

Design of Modulation and Packet Detection in Body Area Networks

Tang²,

Lin³

et al. 2014

JCP

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In burst communication systems like Body Area Networks (BAN), burst packet should be detected prior to the demodulation of the signal at the receiver. Meanwhile, different modulation and demodulation algorithms may affect the BER performance of the entire system seriously. To satisfy the conditions that BAN nodes or devices have to be small in size and very low in power consumption, algorithm design of modulation and packet detection are very important. Referring to IEEE 802.15.6 BAN standard, theoretical analysis of the modulation and demodulation for π/2-DBPSK and π/4-DQPSK is carried out first. The two modulations are realized by using two different two-step looking up table respectively and then united to be one by combining the two phase increment tables. By use of the special structure of π/2-DBPSK modulated preamble, packet detection algorithm with low complexity is also carefully designed. Simulation results of BER performance are presented at last. In AWGN channel, both modulations achieve good performance, and performance degradation of π/4-DQPSK happens in multipath channel which may not satisfy the requirements. Adaptive modulation is considered to solve this problem by choosing different modulation scheme according to channel quality.

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“…Many sensor reliability issues explored, have been for other impacts of IoT proliferation, such as Satchel et al, who looked at the electromagnetic impacts on implanted medical devices [55]. Yi et al also looked at system architecture of an intelligent personal communication node [56]. There has also been work on power savings for NFC [57], exploring the current consumption of IoT devices [58], as well as power optimizations and battery lifetime issues [59].…”

Section: Securing Sensing and Use Of Near-field Communication (Nfc) mentioning

confidence: 99%

Sensory Substitution: Situational Awareness and Resilience using Available Sensors

Russell¹

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I would like to take this opportunity to thank my amazing and incredible supervisors, Dr. Rafik Goubran and Dr. Felix Kwamena. What an astounding honour it has been for me to have each of these superb advisors. You have unceasingly provided keen and diligent feedback and much appreciated detailed input, from not only your immense knowledge, but also from your quick thinking. Your steadfast support and abiding dedication has been instrumental in the journey through this program. I sincerely extend to you with profound respect, and with heartfelt appreciation, an epic, mammoth, and gigantic thank you. Next, I greatly appreciate and thank each person who has participated on my committees. Thank you to my talented and outstanding colleagues in the lab, and to my friends, and to other great researchers and impressive students with whom I have collaborated throughout campus and all around the world. Also, thank you to all the many admirable professors with whom I have worked or sought advice, especially my former supervisor Dr. Alan Steele, and thank you to those other professionals with whom I have worked. Thank you very much to all of the administrative staff, technical staff, and support staff who have helped me in any way during my time at Carleton. I especially thank my awesome Mom, Norma, for standing with me every step of the way, from well before my first day of Kindergarten through to the preparation of this document, and of course for her love and support in all of my life. Above all, I thank God for everything!! I am ever so grateful.

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System architecture of intelligent personal communication node for body sensor network

Cited by 10 publications

References 10 publications

Patient Centered Real-Time Mobile Health Monitoring System

Patient Centered Real-Time Mobile Health Monitoring System

Design of Modulation and Packet Detection in Body Area Networks

Sensory Substitution: Situational Awareness and Resilience using Available Sensors

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