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1.
Nat Commun ; 13(1): 4465, 2022 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-35915075

RESUMO

Microcatheters have enabled diverse minimally invasive endovascular operations and notable health benefits compared with open surgeries. However, with tortuous routes far from the arterial puncture site, the distal vascular regions remain challenging for safe catheter access. Therefore, we propose a wireless stent-shaped magnetic soft robot to be deployed, actively navigated, used for medical functions, and retrieved in the example M4 segment of the middle cerebral artery. We investigate shape-adaptively controlled locomotion in phantoms emulating the physiological conditions here, where the lumen diameter shrinks from 1.5 mm to 1 mm, the radius of curvature of the tortuous lumen gets as small as 3 mm, the lumen bifurcation angle goes up to 120°, and the pulsatile flow speed reaches up to 26 cm/s. The robot can also withstand the flow when the magnetic actuation is turned off. These locomotion capabilities are confirmed in porcine arteries ex vivo. Furthermore, variants of the robot could release the tissue plasminogen activator on-demand locally for thrombolysis and function as flow diverters, initiating promising therapies towards acute ischemic stroke, aneurysm, arteriovenous malformation, dural arteriovenous fistulas, and brain tumors. These functions should facilitate the robot's usage in new distal endovascular operations.


Assuntos
Aneurisma , AVC Isquêmico , Robótica , Tecnologia sem Fio , Humanos , Robótica/instrumentação , Robótica/métodos , Stents , Ativador de Plasminogênio Tecidual , Resultado do Tratamento
2.
Zhongguo Yi Liao Qi Xie Za Zhi ; 46(4): 373-376, 2022 Jul 30.
Artigo em Chinês | MEDLINE | ID: mdl-35929149

RESUMO

Body temperature is an important physiological parameter of the human body and is used in medicine to reflect the physiological state and health status of the human body. At present, the commonly used clinical thermometers on the market are mainly divided into contact and non-contact types. Most of them are used for rapid body temperature measurement, and it is not easy to monitor body temperature changes in real time. This article introduces a new wearable wireless body temperature monitoring system based on NTC, which senses through NTC. The temperature changes are amplified and filtered, zeroed, and calibrated, and then the temperature data is uploaded to the mobile phone APP via Bluetooth in real time to achieve real-time accurate measurement of body temperature.


Assuntos
Telefone Celular , Dispositivos Eletrônicos Vestíveis , Temperatura Corporal , Humanos , Monitorização Fisiológica , Temperatura , Tecnologia sem Fio
3.
Comput Intell Neurosci ; 2022: 2298139, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35785094

RESUMO

Faced with the AI (artificial intelligence) era, it is both theoretically and practically important to examine the challenges and opportunities that vocational college education in China faces, as well as to actively explore how vocational college education can overcome the challenges and achieve a realistic path. This paper proposes and implements a wireless network-based vocational college talent management system. The main personnel management system primarily completes business operations related to daily personnel file management, while the data mining subsystem mines talent data using the DT (decision tree) classification algorithm to aid talent selection. At the same time, a new topology optimization algorithm based on the principle of minimum rigidity graph is proposed for talent management system wireless network optimization. The maximum-minimum balance criterion and the user-by-user optimization mechanism are designed to obtain the optimal relay selection and subchannel allocation strategy, ensuring the system's reliability and fairness. The optimized algorithm has a user security satisfaction of 0.93 in the range of 250 m, which is higher than other algorithms. It demonstrates that this algorithm's communication link is short, and it has good network connectivity and structural stability.


Assuntos
Inteligência Artificial , Redes de Comunicação de Computadores , Algoritmos , Humanos , Reprodutibilidade dos Testes , Tecnologia sem Fio
4.
Comput Intell Neurosci ; 2022: 1795454, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35785102

RESUMO

With the increasing openness and development of network technology, the network based on the wireless sensor network system has increasingly become an important tool for human social life and production, but it also brings some network security problems. Among them, focus is on network privacy disclosure and foreign intrusion and the research of intrusion detection and privacy protection has increasingly become an important topic of network security. This paper deeply studies the wireless sensor network system based on neural network on the basis of traditional privacy protection and intrusion detection system. Firstly, it applies particle swarm optimization algorithm and constructs a wireless sensor network intrusion detection system based on particle swarm optimization algorithm. The system includes important modules such as data extraction, data analysis, data feedback, and auxiliary decision-making. Compared with other algorithms, particle swarm optimization algorithm does not rely on problem information. It mainly uses real numbers to solve, so the algorithm has strong universality. At the same time, its corresponding principle is simple and easy to implement and less parameters need to be adjusted. Compared with other algorithms, particle swarm optimization algorithm has fast convergence speed and little memory requirement for the computer. At the same time, this paper uses the leap of particle swarm optimization algorithm to make it easier to find the global optimal solution. At the corresponding level of wireless sensor network privacy protection, based on the original data aggregation privacy protection scheme, this paper proposes a privacy protection scheme based on polynomial regression and a user privacy protection scheme based on the same state encryption, which further improves the security of privacy protection and facilitates the management of information. To realize the integrity of user privacy information protection, this paper realizes the decryption of data based on the correlation between binary metadata and compares the corresponding decrypted data with aggregated data, so as to complete the integrity of privacy data protection. The experimental results show that the binary metadata correlation decryption method proposed in this paper and the introduction of the corresponding particle swarm optimization algorithm improve the stability of the system by about 10%, the corresponding system security by a positive proportion, and the integrity of private data by about 10%; therefore, the algorithm proposed in this paper has obvious advantages.


Assuntos
Privacidade , Tecnologia sem Fio , Algoritmos , Segurança Computacional , Humanos , Redes Neurais de Computação
5.
Comput Intell Neurosci ; 2022: 3965416, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35832246

RESUMO

In recent years, with the rapid development of emerging Internet of Things technology and short-range wireless communication technology, smart healthcare monitoring network technology has become a research hotspot. It provides convenience for people and enhances the development of people's own healthcare awareness. This paper aims to study how to make its application in the field of smart healthcare education more applicable through the use of related technologies in the Internet of Things era and few-shot learning. For this reason, this paper proposes to optimize and improve the new sensor technology and the algorithm of few-shot learning, and to adjust some parameters as a whole. At the same time, related experiments and analysis are designed for the improved algorithm to study and understand its performance. The experimental results in this paper show that the improved algorithm improves its application effect by 36.9% and is relatively more applicable than the unimproved algorithm.


Assuntos
Algoritmos , Tecnologia sem Fio , Atenção à Saúde , Humanos , Tecnologia
6.
Comput Math Methods Med ; 2022: 4782850, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35799666

RESUMO

Topological information is provided, and research on the design of routing protocols for UAV self-assembling networks is conducted, in order to enable fleet communication transfer between UAVs and UAVs and enhance their communication transmission rate in the self-assembling network. A new routing protocol is proposed through greedy forwarding and peripheral forwarding of UAV self-assembling network communication data, UAV self-assembling network planarization processing, dynamic adjustment of routing mode based on topological information, and routing protocol decision content generation. The proposed network is described using stochastic geometry theory, with the UAV and building locations modeled as two independently distributed Poisson point processes and the building shape modeled as a rectangular body with height obeying the Rayleigh distribution. An estimated equation for typical user coverage is produced using this model. The simulation results show that the approximate expression matches with the simulation results with reduced computational complexity, which verifies the validity of the approximate analysis. By comparing it with the clustering-based routing protocol, it is concluded that the new routing protocol conditions for UAV self-assembly network can realize the communication transmission between UAVs and drones and further promote their communication transmission rate.


Assuntos
Redes de Comunicação de Computadores , Tecnologia sem Fio , Algoritmos , Simulação por Computador , Humanos
7.
Sensors (Basel) ; 22(13)2022 Jun 22.
Artigo em Inglês | MEDLINE | ID: mdl-35808195

RESUMO

The indoor localization of people is the key to realizing "smart city" applications, such as smart homes, elderly care, and an energy-saving grid. The localization method based on electrostatic information is a passive label-free localization technique with a better balance of localization accuracy, system power consumption, privacy protection, and environmental friendliness. However, the physical information of each actual application scenario is different, resulting in the transfer function from the human electrostatic potential to the sensor signal not being unique, thus limiting the generality of this method. Therefore, this study proposed an indoor localization method based on on-site measured electrostatic signals and symbolic regression machine learning algorithms. A remote, non-contact human electrostatic potential sensor was designed and implemented, and a prototype test system was built. Indoor localization of moving people was achieved in a 5 m × 5 m space with an 80% positioning accuracy and a median error absolute value range of 0.4-0.6 m. This method achieved on-site calibration without requiring physical information about the actual scene. It has the advantages of low computational complexity and only a small amount of training data is required.


Assuntos
Algoritmos , Tecnologia sem Fio , Idoso , Humanos , Aprendizado de Máquina , Movimento , Eletricidade Estática
8.
Sensors (Basel) ; 22(13)2022 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-35808227

RESUMO

Energy and security are major challenges in a wireless sensor network, and they work oppositely. As security complexity increases, battery drain will increase. Due to the limited power in wireless sensor networks, options to rely on the security of ordinary protocols embodied in encryption and key management are futile due to the nature of communication between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network infrastructure and the security challenges it faces. It also discusses the possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains; in addition to the challenges and proposed solutions to improving the ability of sensors to identify threats, attacks, risks, and malicious nodes through their ability to learn and self-development using machine learning algorithms. Furthermore, this paper discusses open issues related to adapting machine learning algorithms to the capabilities of sensors in this type of network.


Assuntos
Redes de Comunicação de Computadores , Tecnologia sem Fio , Algoritmos , Segurança Computacional , Fontes de Energia Elétrica , Aprendizado de Máquina
9.
Sensors (Basel) ; 22(13)2022 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-35808228

RESUMO

Ad hoc vehicular networks have been identified as a suitable technology for intelligent communication amongst smart city stakeholders as the intelligent transportation system has progressed. However, in a highly mobile area, the growing usage of wireless technologies creates a challenging context. To increase communication reliability in this environment, it is necessary to use intelligent tools to solve the routing problem to create a more stable communication system. Reinforcement Learning (RL) is an excellent tool to solve this problem. We propose creating a complex objective space with geo-positioning information of vehicles, propagation signal strength, and environmental path loss with obstacles (city map, with buildings) to train our model and get the best route based on route stability and hop number. The obtained results show significant improvement in the routes' strength compared with traditional communication protocols and even with other RL tools when only one parameter is used for decision making.


Assuntos
Inteligência Artificial , Redes de Comunicação de Computadores , Reprodutibilidade dos Testes , Tecnologia sem Fio
10.
Sensors (Basel) ; 22(13)2022 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-35808252

RESUMO

Energy harvesting is an effective technique for prolonging the lifetime of Internet of Things devices and Wireless Sensor Networks. In applications such as environmental sensing, which demands a deploy-and-forget architecture, energy harvesting is an unavoidable technology. Thermal energy is one of the most widely used sources for energy harvesting. A thermal energy harvester can convert a thermal gradient into electrical energy. Thus, the temperature difference between the soil and air could act as a vital source of energy for an environmental sensing device. In this paper, we present a proof-of-concept design of an environmental sensing node that harvests energy from soil temperature and uses the DASH7 communication protocol for connectivity. We evaluate the soil temperature and air temperature based on the data collected from two locations: one in Belgium and the other in Iceland. Using these datasets, we calculate the amount of energy that is producible from both of these sites. We further design power management and monitoring circuit and use a supercapacitor as the energy storage element, hence making it battery-less. Finally, we deploy the proof-of-concept prototype in the field and evaluate its performance. We demonstrate that the system can harvest, on average, 178.74 mJ and is enough to perform at least 5 DASH7 transmissions and 100 sensing tasks per day.


Assuntos
Solo , Tecnologia sem Fio , Fontes de Energia Elétrica , Fenômenos Físicos , Temperatura
11.
Sensors (Basel) ; 22(13)2022 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-35808320

RESUMO

Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There is therefore the need to find methodologies to identify if, when, and how long the person is in the company of other people (possibly, also considering the number). The challenge is to address this task in poorly sensorized apartments, with non-intrusive sensors that are typically wireless and can only provide local and simple information. The proposed method addresses technological issues, such as PIR (Passive InfraRed) blind times, topological issues, such as sensor interference due to the inability to separate detection areas, and algorithmic issues. The house is modeled as a graph to constrain transitions between adjacent rooms. Each room is associated with a set of values, for each identified person. These values decay over time and represent the probability that each person is still in the room. Because the used sensors cannot determine the number of people, the approach is based on a multi-branch inference that, over time, differentiates the movements in the apartment and estimates the number of people. The proposed algorithm has been validated with real data obtaining an accuracy of 86.8%.


Assuntos
Vida Independente , Qualidade de Vida , Idoso , Envelhecimento , Humanos , Tecnologia , Tecnologia sem Fio
12.
Sensors (Basel) ; 22(13)2022 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-35808430

RESUMO

Wireless networks have drastically influenced our lifestyle, changing our workplaces and society. Among the variety of wireless technology, Wi-Fi surely plays a leading role, especially in local area networks. The spread of mobiles and tablets, and more recently, the advent of Internet of Things, have resulted in a multitude of Wi-Fi-enabled devices continuously sending data to the Internet and between each other. At the same time, Machine Learning has proven to be one of the most effective and versatile tools for the analysis of fast streaming data. This systematic review aims at studying the interaction between these technologies and how it has developed throughout their lifetimes. We used Scopus, Web of Science, and IEEE Xplore databases to retrieve paper abstracts and leveraged a topic modeling technique, namely, BERTopic, to analyze the resulting document corpus. After these steps, we inspected the obtained clusters and computed statistics to characterize and interpret the topics they refer to. Our results include both the applications of Wi-Fi sensing and the variety of Machine Learning algorithms used to tackle them. We also report how the Wi-Fi advances have affected sensing applications and the choice of the most suitable Machine Learning models.


Assuntos
Redes Locais , Aprendizado de Máquina , Algoritmos , Bases de Dados Factuais , Tecnologia sem Fio
13.
Sensors (Basel) ; 22(13)2022 Jul 02.
Artigo em Inglês | MEDLINE | ID: mdl-35808505

RESUMO

The spectrum allocation in any auctioned wireless service primarily depends upon the necessity and the usage of licensed primary users (PUs) of a certain band of frequencies. These frequencies are utilized by the PUs as per their needs and requirements. When the allocated spectrum is not being utilized in the full efficient manner, the unused spectrum is treated by the PUs as white space without believing much in the concept of spectrum scarcity. There are techniques invented and incorporated by many researchers, such as cognitive radio technology, which involves software-defined radio with reconfigurable antennas tuned to particular frequencies at different times. Cognitive radio (CR) technology realizes the logic of the utility factor of the PUs and the requirements of the secondary users (SU) who are in queue to utilize the unused spectrum, which is the white space. The CR technology is enriched with different frequency allocation engines and with different strategies in different parts of the world, complying with the regulatory standards of the FCC and ITU. Based on the frequency allocation made globally, the existing CR technology understands the nuances of static and dynamic spectrum allocation and also embraces the intelligence in time allocation by scheduling the SUs whenever the PUs are not using the spectrum, and when the PUs pitch in the SUs have to leave the band without time. This paper identifies a few of the research gaps existing in the earlier literature. The behavioral aspects of the PUs and SUs have been analyzed for a period of 90 days with some specific spectrum ranges of usage in India. The communal habits of utilizing the spectrum, not utilizing the spectrum as white space, different time zones, the requisites of the SUs, the necessity of the applications, and the improvement of the utility factor of the entire spectrum have been considered along with static and dynamic spectrum usage, the development of the spectrum policy engine aligned with cooperative and opportunistic spectrum sensing, and access techniques indulging in artificial intelligence (AI). This will lead to fine-tuning the PU and SU channel mapping without being hindered by predefined policies. We identify the cognitive radio transmitter and receiver parameters, and resort to the same in a proposed channel adaption algorithm. We also analyze the white spaces offered by spectrum ranges of VHF, GSM-900, and GSM-1800 by a real-time survey with a spectrum analyzer. The identified parameters and white spaces are mapped with the help of a swotting algorithm. A sample policy has been stated for ISM band 2.4 GHz where such policies can be excited in a policy server. The policy engine is suggested to be configured over the 5G CORE spectrum management function.


Assuntos
Redes de Comunicação de Computadores , Tecnologia sem Fio , Inteligência Artificial , Cognição , Humanos , Políticas , Supuração , Tecnologia
14.
Comput Intell Neurosci ; 2022: 2783944, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35814585

RESUMO

Keeping in view the overwhelming characteristics of the wireless sensor networks, these networks are constantly being utilized in numerous domains such as industry, healthcare, and music. Aiming at the problem that there is a single-point and multipoint control in the music performance management system, this paper adopts the wireless sensor network multipoint control technology to realize the control of the music performance management system. The system uses TI's CC2430 chip to design the hardware circuit, uses the TinyOS operating system as the software platform of the system, and designs the components of the base station and sensor nodes to achieve data acquisition and transceiver functions. The experimental test shows that the system can realize the multipoint control of the music performance system and has good performance.


Assuntos
Redes de Comunicação de Computadores , Música , Software , Tecnologia , Tecnologia sem Fio
15.
Comput Intell Neurosci ; 2022: 8552142, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35800681

RESUMO

Finding the location of sensors in wireless sensor networks (WSNs) is a major test, particularly in a wide region. A salient clustering approach is laid out to achieve better performance in such a network using an evolutional algorithm. This paper developed a clustered network called neighborhood grid cluster which has a node assuming the part of a cluster center focused in every grid. Grid-based clustering is less difficult and possesses a lot of benefits compared to other clustering techniques. Besides, we proposed a localization algorithm that centers around assessing the target area by considering the least estimated distance embedded with the genetic algorithm. Performance standards incorporate the energy representation, connectivity stratagem, and distance measure as fitness functions that assess our localization problem to demonstrate its viability. Simulation results confirm that our approach further improves localization accuracy, energy utilization, node lifetime, and localization coverage.


Assuntos
Redes de Comunicação de Computadores , Tecnologia sem Fio , Algoritmos , Análise por Conglomerados , Simulação por Computador
16.
Nano Lett ; 22(14): 5944-5953, 2022 07 27.
Artigo em Inglês | MEDLINE | ID: mdl-35816764

RESUMO

A combined treatment using medication and electrostimulation increases its effectiveness in comparison with one treatment alone. However, the organic integration of two strategies in one miniaturized system for practical usage has seldom been reported. This article reports an implantable electronic medicine based on bioresorbable microneedle devices that is activated wirelessly for electrostimulation and sustainable delivery of anti-inflammatory drugs. The electronic medicine is composed of a radio frequency wireless power transmission system and a drug-loaded microneedle structure, all fabricated with bioresorbable materials. In a rat skeletal muscle injury model, periodic electrostimulation regulates cell behaviors and tissue regeneration while the anti-inflammatory drugs prevent inflammation, which ultimately enhance the skeletal muscle regeneration. Finally, the electronic medicine is fully bioresorbable, excluding the second surgery for device removal.


Assuntos
Implantes Absorvíveis , Terapia por Estimulação Elétrica , Animais , Sistemas de Liberação de Medicamentos , Eletrônica Médica , Ondas de Rádio , Ratos , Tecnologia sem Fio
17.
Sensors (Basel) ; 22(15)2022 Jul 25.
Artigo em Inglês | MEDLINE | ID: mdl-35898044

RESUMO

Recent advances in sensor technology are expected to lead to a greater use of wireless sensor networks (WSNs) in industry, logistics, healthcare, etc. On the other hand, advances in artificial intelligence (AI), machine learning (ML), and deep learning (DL) are becoming dominant solutions for processing large amounts of data from edge-synthesized heterogeneous sensors and drawing accurate conclusions with better understanding of the situation. Integration of the two areas WSN and AI has resulted in more accurate measurements, context-aware analysis and prediction useful for smart sensing applications. In this paper, a comprehensive overview of the latest developments in context-aware intelligent systems using sensor technology is provided. In addition, it also discusses the areas in which they are used, related challenges, motivations for adopting AI solutions, focusing on edge computing, i.e., sensor and AI techniques, along with analysis of existing research gaps. Another contribution of this study is the use of a semantic-aware approach to extract survey-relevant subjects. The latter specifically identifies eleven main research topics supported by the articles included in the work. These are analyzed from various angles to answer five main research questions. Finally, potential future research directions are also discussed.


Assuntos
Redes de Comunicação de Computadores , Tecnologia sem Fio , Inteligência Artificial , Humanos
18.
Sensors (Basel) ; 22(15)2022 Jul 25.
Artigo em Inglês | MEDLINE | ID: mdl-35898045

RESUMO

The Internet of Things (IoT) is one of the most important emerging technologies, spanning a myriad of possible applications, especially with the increasing number and variety of connected devices. Several network simulation tools have been developed with widely varying focuses and used in many research fields. Thus, it is critical to simulate the work of such systems and applications before actual deployment. This paper explores the landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest. Using a systematic approach, we present a chronological survey of available IoT and WSNs simulation tools. With this, we categorized and content-analyzed published scientific papers in the IoT and WSNs simulation tools research domain by highlighting the simulation tools, study type, scope of study and performance measures of the studies. Next, we present an overview of LoRa/LoRaWAN technology by considering its architecture, transmission parameters, device classes and available simulation tools. Furthermore, we discussed three popular open-source simulation tools/frameworks, namely, NS-3, OMNeT++ (FLoRa) and LoRaSim, for the simulation of LoRa/LoRaWAN networks. Finally, we evaluate their performance in terms of Packet Delivery Ratio (PDR), CPU utilization, memory usage, execution time and the number of collisions.


Assuntos
Internet das Coisas , Dispositivos Eletrônicos Vestíveis , Redes de Comunicação de Computadores , Tecnologia sem Fio
19.
Sensors (Basel) ; 22(15)2022 Jul 26.
Artigo em Inglês | MEDLINE | ID: mdl-35898075

RESUMO

Wireless power transfer provides a most convenient solution to charge devices remotely and without contacts. R&D has advanced the capabilities, variety, and maturity of solutions greatly in recent years. This survey provides a comprehensive overview of the state of the art on different technological concepts, including electromagnetic coupled and uncoupled systems and acoustic technologies. Solutions to transfer mW to MW of power, over distances ranging from millimeters to kilometers, and exploiting wave concepts from kHz to THz, are covered. It is an attractive charging option for many existing applications and moreover opens new opportunities. Various technologies are proposed to provide wireless power to these devices. The main challenges reside in the efficiency and range of the transfer. We highlight innovation in beamforming and UV-assisted approaches. Of particular interest for designers is the discussion of implementation and operational aspects, standards, and safety relating to regulations. A high-level catalog of potential applications maps these to adequate technological options for wireless power transfer.


Assuntos
Fenômenos Eletromagnéticos , Tecnologia sem Fio
20.
Sensors (Basel) ; 22(14)2022 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-35890750

RESUMO

The paper analyses the autonomy of a wireless body sensor that continuously measures the potential difference between two proximal electrodes on the skin, primarily used for measuring an electrocardiogram (ECG) when worn on the torso. The sensor is powered by a small rechargeable battery and is designed for extremely low power use. However, the autonomy of the sensor, regarding its power consumption, depends significantly on the measurement quality selection, which directly influences the amount of data transferred. Therefore, we perform an in-depth analysis of the power consumption sources, particularly those connected with the Bluetooth Low Energy (BLE) communication protocol, in order to model and then tune the autonomy of the wireless low-power body sensor for long-term ECG monitoring. Based on the findings, we propose two analytical models for power consumption: one for power consumption estimation in idle mode and the other one for power estimation in active mode. The proposed models are validated with the measured power consumption of the ECG sensor at different ECG sensor settings, such as sampling rate and transmit power. The proposed models show a good fit to the measured power consumption at different ECG sensor sampling rates. This allows for power consumption analysis and sensor autonomy predictions for different sensor settings. Moreover, the results show that the transmit power has a negligible effect on the sensor autonomy in the case of streaming data with high sampling rates. The most energy can be saved by lowering the sampling rate with suitable connection interval and by packing as much data as possible in a single BLE packet.


Assuntos
Eletrocardiografia , Tecnologia sem Fio , Fontes de Energia Elétrica , Eletrodos
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