System architecture for low-power ubiquitously connected remote health monitoring applications with smart transmission mechanism
TL;DR: A novel smart transmission technique with seamless handoff mechanism to achieve ubiquitous connectivity using multiple on-chip radios targeting remote health monitoring applications and concludes that they require only 2082 CMOS transistors for real-time implementation.
Abstract: We present a novel smart transmission technique with seamless handoff mechanism to achieve ubiquitous connectivity using multiple on-chip radios targeting remote health monitoring applications. For the first time to the best of our knowledge, a system architecture for low-power ubiquitously connected multiparametric remote health monitoring system is proposed in this paper. The architecture proposed uses a generic adaptive rule engine for classifying the collected multiparametric data from patient and smartly transmit the data when only needed. The on-chip seamless handoff mechanism proposed aids for the ubiquitous connectivity with a very good energy savings by intelligent controlling of the multiple on-chip radios. The performance analysis of the proposed on-chip seamless handoff mechanism along with adaptive rule engine-based smart transmission mechanism achieves on an average of 50.39% of energy saving and 51.01% reduction in duty cycle of transmitter taken over 20 users compared with the continuous transmission. From the hardware complexity analysis made on the proposed seamless handoff controller and adaptive rule engine concludes that they require only 2082 CMOS transistors for real-time implementation.
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TL;DR: This paper proposes an approach required to make smart villages and towns with respect to the healthcare domain with due consideration and technical backing of survey research including questionnaire-based evaluation and regressive analysis of issues in present technologies.
Abstract: Smart health monitoring system technologies pertaining to the biomedical domain has evinced intense interest, which in turn has led the emphasis on unconventional applications of engineering and internetwork transmission in the field. Throughout the next series of textual and contextual matter, we will be reviewing and exhibiting, such initiatives and established methods which are being used to achieve health monitoring systems approaching toward making smart remote villages and cities. It also collates for the reader the issues and challenges prevalent in the present technical advancements and for societal validation, a survey analysis has also been briefed in this paper to show the demand and requisites of the real world in health monitoring system. Today there is a need for an integrated solution which can diagnose the early cyanotic congenital diseases in newly born babies to monitoring of various geriatric problems in elderly people. The future avenues of maximum life expectancy and uber-prompt medical treatment depend upon it. This paper proposes an approach required to make smart villages and towns with respect to the healthcare domain. This proposal has been made with due consideration and technical backing of survey research including questionnaire-based evaluation and regressive analysis of issues in present technologies.
49 citations
Cites background from "System architecture for low-power u..."
...Ubiquitous/Pervasive computing [11]–[15], [19]–[21], [25], [27], [28], [31], [34], [35], [37], [38] elaborates the concept of spontaneous access to data collected from the patient....
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...[21] proposed a system architecture for low power universally connected remote health monitoring system which includes mote development with handoff controller....
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01 Oct 2017
TL;DR: A novel system architecture to utilize brain signals for controlling Internet of Things enabled environments and aids in translating brain signals to commands that interact with or control the environment using IoT actuation networks thus executing user desired actions.
Abstract: Brain Computer Interface (BCI) has recently gained much popularity due to plethora of its applications. In this paper, we propose a novel system architecture to utilize brain signals for controlling Internet of Things enabled environments. The proposed architecture aids in translating brain signals to commands that interact with or control the environment using IoT actuation networks thus executing user desired actions. It comprises of novel, low complex and low power intelligent signal processing architecture for detection of voluntary eye blinks by isolating involuntary eye blinks and IoT enabled wireless actuation network for controlling the environment using commands generated from EEG signal. For the real time performance analysis of the proposed architecture, we developed a wearable device which acquires dual channel EEG using electrodes at Fp1 and Fp2 locations. From the acquired EEG data, the device detects the voluntary eye blinks of the patient and use this information in controlling the environment such as switching HVAC system, lighting or electric fan etc. Performance analysis shows that the proposed intelligent signal processing architecture detects the voluntary eye blinks with 95.2% accuracy when tested on 10 subjects with a low power consumption of 165 mW.
14 citations
Cites background from "System architecture for low-power u..."
...Authors in [8] proposed a multiple on-chip radio architecture for smarter health care applications and also proposed a Seamless Handoff Controller (SHC) based smart and intelligent controlling of radio switching to improve the performance of node....
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TL;DR: This paper will give you a comparative study on health detection and monitoring of the patient.
Abstract: IOT devices is used in many fields which make the user’s daily life more comfortable. These smart sensors devices is used to collect heartbeat which is used to assess the health condition of the patient. Communicating the collected information to the doctor, making exact decision on the data collected and notifying the patient is the challenging task in the IOT. This paper will give you a comparative study on health detection and monitoring of the patient.
12 citations
TL;DR: The simulation results show that the received throughput of IEEE 802.15.4 WPANs can be improved by exploiting the proposed link adaptation strategies instead of auto-rate fallback, the conventional WPAN strategy.
Abstract: This paper proposes two link adaptation strategies for IEEE 802.15.4 wireless personal area networks (WPANs), using a multi-rate signaling set. In the proposed link adaptation strategies, the most adequate modulation and coding scheme (MCS) satisfying the target bit error rate (BER) of the end device is selected based on the signal-to-interference-plus-noise ratio (SINR) of either a beacon or an acknowledgement (ACK) frame. The beacon-based link adaptation scheme has low complexity and overhead, given that it performs link adaptation only once per superframe. In contrast, the ACK-based strategy performs link adaptation at every ACK frame, and therefore provides a faster and more effective link adaptation, but at the expense of a larger overhead. The specific protocol design for the proposed link adaptation strategies is developed by constructing the signal flow based on the service primitives between the protocol stack layers. The network simulator OPNET is used to implement an accurate IEEE 802.15.4 WPAN protocol stack and the simulation environment required for performance evaluation. The simulation results show that the received throughput of IEEE 802.15.4 WPANs can be improved by exploiting the proposed link adaptation strategies instead of auto-rate fallback, the conventional WPAN strategy.
8 citations
Cites background from "System architecture for low-power u..."
...Recently, this standard has been widely applied as a radio access technology to smart home network systems [2]– [5], in healthcare applications [6]–[9], and to support various services based on the Internet of Things (IoT) [10]–[13]....
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TL;DR: In this paper, the authors present a hardware-software design and implementation of an open, integrated, and scalable healthcare platform oriented to multiple point-care scenarios for healthcare promotion and cardiovascular disease prevention.
Abstract: This article presents the hardware-software design and implementation of an open, integrated, and scalable healthcare platform oriented to multiple point-care scenarios for healthcare promotion and cardiovascular disease prevention. The platform has the capability to provide continuous monitoring, extended device integration, strategies based on artificial intelligence for the information analysis and cybersecurity support, delivering a secure end-to-end hardware-software solution. This platform is used to perform the remote patient health monitoring and supervision by doctors, triage procedures in hospitals, or self-care monitoring using personal devices such as tablets and cellphones. The proposed hardware architecture facilitates the integration of biomedical data acquired from different health-point cares, collecting relevant information for the detection of cardiovascular risk through deep-learning algorithms. All these characteristics make our development a strong tool to perform epidemiological profiling and future implementation of strategies for comprehensive cardiovascular risk intervention. The components of the platform are described, and their main functionalities are highlighted.
7 citations
References
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01 Jan 2012
TL;DR: This leading book on wireless communications offers a wealth of practical information on the implementation realities of wireless communications, from cellular system design to networking, plus world-wide standards, including ETACS, GSM, and PDC.
Abstract: For cellular radio engineers and technicians. The leading book on wireless communications offers a wealth of practical information on the implementation realities of wireless communications. This book also contains up-to-date information on the major wireless communications standards from around the world. Covers every fundamental aspect of wireless communications, from cellular system design to networking, plus world-wide standards, including ETACS, GSM, and PDC. Theodore Rappaport is Series Editor for the Prentice Hall Communication, Engineering, and Emerging Technologies Series.
1,813 citations
"System architecture for low-power u..." refers background or methods in this paper
...1) Attenuation Factor Model: Many indoor path loss models have been proposed such as Log-distance model, Ericsson multiple breakpoint model and Attenuation factor model (AF) [27] etc....
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...The standard values for the two parameters in different scenarios are given in [27]....
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...The red dashed circle indicates the estimated range of ZigBee coverage using the ‘Attenuation Factor Model’ [25]–[27]....
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TL;DR: An algorithm based on wavelet transforms (WT's) has been developed for detecting ECG characteristic points and the relation between the characteristic points of ECG signal and those of modulus maximum pairs of its WT's is illustrated.
Abstract: An algorithm based on wavelet transforms (WT's) has been developed for detecting ECG characteristic points. With the multiscale feature of WT's, the QRS complex can be distinguished from high P or T waves, noise, baseline drift, and artifacts. The relation between the characteristic points of ECG signal and those of modulus maximum pairs of its WT's is illustrated. By using this method, the detection rate of QRS complexes is above 99.8% for the MIT/BIH database and the P and T waves can also be detected, even with serious base line drift and noise. >
1,637 citations
"System architecture for low-power u..." refers background or methods in this paper
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03 Nov 2010
TL;DR: This work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity, then designs BuzzBuzz to mitigate WiFi interference through header and payload redundancy, which improves the ZigBee network delivery rate and reduces ZigBee retransmissions.
Abstract: Frequency overlap across wireless networks with different radio technologies can cause severe interference and reduce communication reliability. The circumstances are particularly unfavorable for ZigBee networks that share the 2.4 GHz ISM band with WiFi senders capable of 10 to 100 times higher transmission power. Our work first examines the interference patterns between ZigBee and WiFi networks at the bit-level granularity. Under certain conditions, ZigBee activities can trigger a nearby WiFi transmitter to back off, in which case the header is often the only part of the Zig-Bee packet being corrupted. We call this the symmetric interference regions, in comparison to the asymmetric regions where the ZigBee signal is too weak to be detected by WiFi senders, but WiFi activity can uniformly corrupt any bit in a ZigBee packet. With these observations, we design BuzzBuzz to mitigate WiFi interference through header and payload redundancy. Multi-Headers provides header redundancy giving ZigBee nodes multiple opportunities to detect incoming packets. Then, TinyRS, a full-featured Reed Solomon library for resource-constrained devices, helps decoding polluted packet payload. On a medium-sized testbed, BuzzBuzz improves the ZigBee network delivery rate by 70%. Furthermore, BuzzBuzz reduces ZigBee retransmissions by a factor of three, which increases the WiFi throughput by 10%.
401 citations
"System architecture for low-power u..." refers background in this paper
...In [19], authors discussed synchronous and asynchronous interference regions...
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TL;DR: A frequency agility-based interference avoidance algorithm that can detect interference and adaptively switch nodes to “safe” channel to dynamically avoid WLAN interference with small latency and small energy consumption is proposed.
Abstract: Smart grid is an intelligent power generation, distribution, and control system. ZigBee, as a wireless mesh networking scheme low in cost, power, data rate, and complexity, is ideal for smart grid applications, e.g., real-time system monitoring, load control, and building automation. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In this paper, we aim to develop practical ZigBee deployment guideline under the interference of WLAN. We identify the “Safe Distance” and “Safe Offset Frequency” using a comprehensive approach including theoretical analysis, software simulation, and empirical measurement. In addition, we propose a frequency agility-based interference avoidance algorithm. The proposed algorithm can detect interference and adaptively switch nodes to “safe” channel to dynamically avoid WLAN interference with small latency and small energy consumption. Our proposed scheme is implemented with a Meshnetics ZigBit Development Kit and its performance is empirically evaluated in terms of the packet error rate (PER) using a ZigBee and Wi-Fi coexistence test bed. It is shown that the empirical results agree with our analytical results. The measurements demonstrate that our design guideline can efficiently mitigate the effect of WiFi interference and enhance the performance of ZigBee networks.
335 citations
"System architecture for low-power u..." refers background in this paper
...deploy ZigBee devices to avoid static and dynamic interferences from WiFi for smart home applications are presented in [20]....
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25 Jun 2008
TL;DR: The experiment described in this paper indicates that RSSI is, in fact, a poor distance estimator when using wireless sensor networks in buildings.
Abstract: In todaypsilas modern wireless ZigBee-based modules, there are two well-known values for link quality estimation: RSSI (received signal strength indicator) and LQI (link quality indicator). In respect to wireless channel models, received power should be a function of distance. From this aspect, we believed that RSSI can be used for evaluating distances between nodes. The experiment described in this paper indicates that RSSI is, in fact, a poor distance estimator when using wireless sensor networks in buildings. Reflection, scattering and other physical properties have an extreme impact on RSSI measurement and so we can conclude: RSSI is a bad distance estimator.
293 citations
"System architecture for low-power u..." refers methods in this paper
...RSSI indicates the power in the received signal and a procedure to measure the RSSI has been depicted in [23]....
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