Body Sensors Applied in Pacemakers: A Survey

Shi, Wei; Zhou, MengChu

doi:10.1109/jsen.2011.2177256

Cited by 21 publications

(11 citation statements)

References 40 publications

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“…In this article, three factors of activity levels, emotions, body size, which are measurable by the device-connected sensors, are used to have an exact and simple study of system's software behavior. The best way to identify the level of physical activity is to use an activity sensor which is known as accelerometer [4]. This accelerometer can convert the activity level to signal based on the patient's body movements.…”

Section: A Factors Affecting Heart Ratementioning

confidence: 99%

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Medical software runtime checking using Petri-nets & software agents

Majma

Babamir

2014

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)

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Nowadays, a new generation of Health Information systems (HIS) called e-health is developing. Health-related equipment can be defined as electronic devices that are able to be implanted in the patient's body to help his health state. Insulin pump and pacemaker device are some instances of such equipment. Most of the patients who use these devices do not have much technical knowledge. Therefore, these devices must be self-configuring and self-managing. More significantly, they should be able to tolerate and remove errors. As these equipment are often sensitive and may affect the life of human beings, their software are called vital software programs. Even a small error in these vital software programs may endanger lives of human being. The runtime test of these software programs is necessary. This article aims at presenting a solution to verify the performance of these devices. Pacemaker device as a sample is studied. The proposed strategy suggests the application of reactive model-based software agents which play the role of an oracle in a software test. This agent's knowledgebase is obtained by Petri net drawn based on the proper state of device implementation. Petri net first turns into matrix thanks to linear algebra and then changes to rules which the agent uses to make decisions. Using its intelligence, the agent directs the error, if identified, to the safe mode. The safe mode is meant to be the patient's proper heart rate. Checking at runtime by use of the agent in addition to the assurance of accurate performance of device can make quick decision makings at crisis time possible for those devices related to human health.

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Section: A Factors Affecting Heart Ratementioning

confidence: 99%

“…Recognizing the emotional state of the patient is measurable according to his respiration rate . A sensor called minute ventilation or blended can do this measurement [4]. Body size is calculated by respiration rate (RR) and blood pressure.…”

Section: A Factors Affecting Heart Ratementioning

confidence: 99%

Medical software runtime checking using Petri-nets & software agents

Majma

Babamir

2014

2014 4th International Conference on Computer and Knowledge Engineering (ICCKE)

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“…Therefore, many types of body sensors such as metabolic sensor and dual sensors have been applied in pacemakers to detect physiological changes of the body during possible daily activities. 7 Common design of most dual sensors includes 2 sensors. 7 First, an accelerometer or activity sensor is used to give a rapid response for short time duration of the exercise condition.…”

Section: Introductionmentioning

confidence: 99%

“…7 Common design of most dual sensors includes 2 sensors. 7 First, an accelerometer or activity sensor is used to give a rapid response for short time duration of the exercise condition. Second, the time interval between 2 waves, ie, Q and T, in electrocardiogram is detected by a Q-T sensor, which is proportional to the metabolic demand to measure the actual value of heart rates.…”

Section: Introductionmentioning

confidence: 99%

Robust RBF neural network–based backstepping controller for implantable cardiac pacemakers

Karar

2018

Adaptive Control & Signal

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Implantable cardiac pacemaker is a standard medical device to treat heart rhythm disorders. In this paper, a new adaptive backstepping controller is developed to enhance the performance of dual-sensor pacemakers for regulating the heart rate based on radial basis function neural networks. The robust design of adaptive backstepping controller using Lyapunov functions allows to guarantee the stability and performance of the rate-adaptive pacing system for accurately accomplishing the heart rate regulation at different preset or desired values. The developed control system has been successfully validated using 12 cases of the preset heart rates for 4 patients during 3 body activities, namely, at rest, walking, and jogging. The resulting root mean square error and maximum error are less than 0.9 and 1.7%, respectively. Moreover, the comparative results of this study showed that the performance of developed backstepping controller is superior to other pacemaker controllers in the previous studies. Therefore, it is potentially valid to be applied in dual-sensor cardiac pacemakers for the clinical use. KEYWORDSbackstepping control, dual-sensor pacemaker, intelligent control, Lyapunov stability analysis, neural networks, radial basis function

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“…In fact, the patient can perform activities of daily living while physiological data are continuously monitored by medical centers. A WBAN is composed of several biosensors implanted or deployed on the body to measure medical parameters, such as body temperature, arterial pressure, and EEG Signal [3][4][5][6][7][8]. Once the aforementioned parameters are collected, they are transmitted to the base station where further analyses are taking place by the specialists.…”

Section: Introductionmentioning

confidence: 99%

Equalized Energy Consumption in Wireless Body Area Networks for a Prolonged Network Lifetime

Azhari

Moussaid

Toumanari

et al. 2017

Wireless Communications and Mobile Computing

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The phenomenal advances in electronics contributed to a widespread use of distributed sensors in wireless communications. A set of biosensors can be deployed or implanted in the human body to form a Wireless Body Area Network (WBAN), where various WBAN PHY layers are utilized. The WBAN allows the measurement of physiological data, which is forwarded by the gateway to the base station for analysis purposes. The main issue in conceiving a WBAN communication mechanism is to manage the residual energy of sensors. The mobile agent system has been widely applied for surveillance applications in Wireless Sensor Networks (WSNs). It consists in dispatching one or more mobile agents simultaneously to collect data, while following a predetermined optimum itinerary. The continuous use of the optimal itinerary leads to a rapid depletion of sensor nodes batteries, which minimizes the network lifetime. This paper presents a new algorithm to equalize the energy consumption among sensor motes. The algorithm exploits all the available paths towards the destination and classifies them with respect to the end-to-end delay and the overall energy consumption. The proposed algorithm performs better compared to the optimal routing path. It increases the network lifetime to the maximum by postponing routing of data via the most-recently used path, and it also maintains data delivery within the delay interval threshold.

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Body Sensors Applied in Pacemakers: A Survey

Cited by 21 publications

References 40 publications

Medical software runtime checking using Petri-nets & software agents

Medical software runtime checking using Petri-nets & software agents

Robust RBF neural network–based backstepping controller for implantable cardiac pacemakers

Equalized Energy Consumption in Wireless Body Area Networks for a Prolonged Network Lifetime

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Body Sensors Applied in Pacemakers: A Survey

Cited by 21 publications

References 40 publications

Medical software runtime checking using Petri-nets &amp; software agents

Medical software runtime checking using Petri-nets &amp; software agents

Robust RBF neural network–based backstepping controller for implantable cardiac pacemakers

Equalized Energy Consumption in Wireless Body Area Networks for a Prolonged Network Lifetime

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Product

Resources

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Medical software runtime checking using Petri-nets & software agents

Medical software runtime checking using Petri-nets & software agents