Search results for: Autonomic%20computing

Authors: Sharan Badiger, Prema T. Akkasaligar, Deepak Kadeli

Abstract:

Human Immunodeficiency Virus is known to affect almost all organ systems in the body. In addition to central nervous system it also affects the autonomic nervous system. Autonomic nervous dysfunction has been known to severely affect the quality of life in human immunodeficiency virus positive patients. It is known to have caused fatal consequences in late stages of the disease in patients who go in for invasive diagnostic or therapeutic procedures. The aim of this review is to determine the incidence, clinical significance and frequency of cardiac autonomic neuropathy in patients human immunodeficiency virus infection.

Keywords: Autonomic nervous system, autonomic nervous dysfunction, cardiac autonomic dysfunction, human immunodeficiency virus.

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Authors: Dae Won Lee, Ji Hyung Park, Sinae Eom, Syung Hyun Cho, Jong Soo Lee, Han Sung Kim

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The autonomic nervous system has a regulatory structure that helps people adapt to changes in their environment by adjusting or modifying some functions in response to stress, and regulating involuntary function of human organs. The purpose of this study was to investigate the effect of combined stimulation, both far-infrared heating and chiropractic, on the autonomic nervous system activities using thermal image and heart rate variability. Six healthy subjects participated in this test. We compared the before and after autonomic nervous system activities through obtaining thermal image and photoplethysmogram signal. The thermal images showed that the combined stimulation changed subject-s body temperature more highly and widely than before. The result of heart rate variability indicated that LF/HF ratio decreased. We concluded that combined stimulation activates autonomic nervous system, and expected other possibilities of this combined stimulation.

Keywords: Far-infrared heating, Chiropractic, Autonomic nervous system, Heart rate variability

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Authors: Blesson Varghese, Gerard T. McKee

Abstract:

The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on 'Intelligent agents' another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.

Keywords: Autonomic computing, intelligent agents, swarm-array computing.

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Authors: Blesson Varghese, Gerard McKee

Abstract:

The work reported in this paper proposes Swarm-Array computing, a novel technique inspired by swarm robotics, and built on the foundations of autonomic and parallel computing. The approach aims to apply autonomic computing constructs to parallel computing systems and in effect achieve the self-ware objectives that describe self-managing systems. The constitution of swarm-array computing comprising four constituents, namely the computing system, the problem/task, the swarm and the landscape is considered. Approaches that bind these constituents together are proposed. Space applications employing FPGAs are identified as a potential area for applying swarm-array computing for building reliable systems. The feasibility of a proposed approach is validated on the SeSAm multi-agent simulator and landscapes are generated using the MATLAB toolkit.

Keywords: Swarm-Array computing, Autonomic computing, landscapes.

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Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, A. Naseem, N. G. Karthick, T. K. Abdul Jaleel, Paul K.Joseph

Abstract:

It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.

Keywords: Autonomic nervous system, diabetes mellitus, heart rate variability, pattern identification, sample entropy

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Authors: Martin Doran, Roy Sterritt, George Wilkie

Abstract:

NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: Autonomic, self-adaption, self-healing, self-optimization.

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Authors: Martin Doran, Roy Sterritt, George Wilkie

Abstract:

The majority of today’s mobile robots are very dependent on battery power. Mobile robots can operate untethered for a number of hours but eventually they will need to recharge their batteries in-order to continue to function. While computer processing and sensors have become cheaper and more powerful each year, battery development has progress very little. They are slow to re-charge, inefficient and lagging behind in the general progression of robotic development we see today. However, batteries are relatively cheap and when fully charged, can supply high power output necessary for operating heavy mobile robots. As there are no cheap alternatives to batteries, we need to find efficient ways to manage the power that batteries provide during their operational lifetime. This paper proposes the use of autonomic principles of self-adaption to address the behavioral changes a battery experiences as it gets older. In life, as we get older, we cannot perform tasks in the same way as we did in our youth; these tasks generally take longer to perform and require more of our energy to complete. Batteries also suffer from a form of degradation. As a battery gets older, it loses the ability to retain the same charge capacity it would have when brand new. This paper investigates how we can adapt the current state of a battery charge and cycle count, to the requirements of a mobile robot to perform its tasks.

Keywords: Autonomic, self-adaptive, self-optimizing, degradation.

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Authors: P. T. Ahamed Seyd, V. I. Thajudin Ahamed, Jeevamma Jacob, Paul Joseph K

Abstract:

Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Keywords: Autonomic nervous system, diabetes mellitus, frequency domain and time domain analysis, heart rate variability.

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Authors: Sun K. Yoo, Chung K. Lee

Abstract:

Determination of attentional status is important because working performance and an unexpected accident is highly related with the attention. The autonomic nervous and the central nervous systems can reflect the changes in person’s attentional status. Reduced number of suitable pysiological parameters among autonomic and central nervous systems related signal parameters will be critical in optimum design of attentional devices. In this paper, we analyze the EEG (Electroencephalography) and HRV (Heart Rate Variability) signals to demonstrate the effective relation with brain signal and cardiovascular signal during event-related attention, which will be later used in selecting the minimum set of attentional parameters. Time and frequency domain parameters from HRV signal and frequency domain parameters from EEG signal are used as input to the optimum feature parameters selector.

Keywords: EEG, HRV, attentional status.

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Authors: Vladimir I. Ponomarenko, Mikhail D. Prokhorov, Anatoly S. Karavaev

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The interaction between respiration and low-frequency rhythms of the cardiovascular system is studied. The obtained results count in favor of the hypothesis that low-frequency rhythms in blood pressure and R-R intervals are generated in different central neural structures involved in the autonomic control of the cardiovascular systems.

Keywords: Cardiovascular system, R-R intervals, blood pressure, synchronization.

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Authors: Megumi Nishida, Naoya Motegi, Takurou Kikuchi, Tomoko Tokumura

Abstract:

In recent years, the power system has been changed and a flexible power pricing system such as demand response has been sought in Japan. The demand response system works simply in the household sector and the owner as the decision-maker, can benefit from power saving. On the other hand, the execution of demand response in the office building is more complex than in the household because various people such as owners, building administrators and occupants are involved in the decision-making process. While the owners benefit from demand saving, the occupants are exposed to restricted benefits of a demand-saved environment. One of the reasons is that building systems are usually under centralized management and each occupant cannot choose freely whether to participate in demand response or not. In addition, it is unclear whether incentives give occupants the motivation to participate. However, the recent development of IT and building systems enables the personalized control of the office environment where each occupant can control the lighting level or temperature individually. Therefore, it can be possible to have a system which each occupant can make a decision of whether or not to participate in demand response in the office building. This study investigates personal responses to demand response requests, under the condition where each occupant can adjust their brightness individually in their workspace. Once workers participate in the demand response, their desk-lights are automatically turned off. The participation rates in the demand response events are compared among four groups, which are divided by different motivation, the presence, or absence of incentives and the method of participation. The result shows that there are significant differences of participation rates in demand response event between four groups. The method of participation has a large effect on the participation rate. The “Opt-out” groups where the occupants are automatically enrolled in a demand response event if they do not express non-participation have the highest participation rate in the four groups. Incentives also have an effect on the participation rate. This study also reports on the impact of low illumination office environment on the occupants, such as stress or fatigue. The electrocardiogram and the questionnaire are used to investigate the autonomic nervous activity and subjective fatigue symptoms of the occupants. There is no big difference between dim workspace during demand response event and bright workspace in autonomic nervous activity and fatigue.

Keywords: Demand response, illumination, questionnaire, electrocardiograph.

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Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, Paul Joseph K.

Abstract:

Analysis of heart rate variability (HRV) has become a popular non-invasive tool for assessing the activities of autonomic nervous system. Most of the methods were hired from techniques used for time series analysis. Currently used methods are time domain, frequency domain, geometrical and fractal methods. A new technique, which searches for pattern repeatability in a time series, is proposed for quantifying heart rate (HR) time series. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are able to distinguish HR data clearly from noise and electroencephalogram (EEG). The results of analysis using these measures give an insight into the fundamental difference between the composition of HR time series with respect to EEG and noise.

Keywords: Approximate entropy, heart rate variability, noise, pattern repeatability, and sample entropy.

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Authors: Liping Li, Ke Li, Changchun Liu, Chengyu Liu, Yuanyang Li

Abstract:

A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p<0.001). After 7 days and 14 days, 46 subjects from the Young and Old groups were retested twice following the same test protocol. Results showed good-to-excellent interclass correlations (ICC=0.783, 95% confidence interval 0.676-0.864). The Bland-Altman plots were used to reexamine the test-retest reliability. In conclusion, the method proposed could be a valid and reliable method to the short-term HRV assessment.

Keywords: Autonomic nervous system, congestive heart failure, heart rate variability, histogram.

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Authors: T. Pishbin, S.M.P. Firoozabadi, N. Jafarnia Dabanloo, F. Mohammadi, S. Koozehgari

Abstract:

Heart-s electric field can be measured anywhere on the surface of the body (ECG). When individuals touch, one person-s ECG signal can be registered in other person-s EEG and elsewhere on his body. Now, the aim of this study was to test the hypothesis that physical contact (hand-holding) of two persons changes their heart rate variability. Subjects were sixteen healthy female (age: 20- 26) which divided into eight sets. In each sets, we had two friends that they passed intimacy test of J.sternberg. ECG of two subjects (each set) acquired for 5 minutes before hand-holding (as control group) and 5 minutes during they held their hands (as experimental group). Then heart rate variability signals were extracted from subjects' ECG and analyzed in linear feature space (time and frequency domain) and nonlinear feature space. Considering the results, we conclude that physical contact (hand-holding of two friends) increases parasympathetic activity, as indicate by increase SD1, SD1/SD2, HF and MF power (p<0.05) and decreases sympathetic activity, as indicate by decrease LF power (p<0.01) and LF/HF ratio (p<0.05).

Keywords: Autonomic nervous system (ANS), Hand- holding, Heart rate variability (HRV), Power spectral density analysis.

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Authors: Desmond B. Keenan, Paul Grossman

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In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.

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Authors: D.Y. Su, C.C. Liu, C.M. Chiang, W. Wang

Abstract:

This study aims to discuss the effect of illumination and the color temperature of the lighting source under the office lighting environment on human psychological and physiological responses. In this study, 21 healthy participants were selected, and the Ryodoraku measurement system was utilized to measure their skin resistance change.The findings indicated that the effect of the color temperature of the lighting source on human physiological responses is significant within 90 min after turning the lights on; while after 90 min the effect of illumination on human physiological responses is higher than that of the color temperature. Moreover, the cardiovascular, digestive and endocrine systems are prone to be affected by the indoor lighting environment. During the long-term exposure to high intensity of illumination and high color temperature (2000Lux -6500K), the effect on the psychological responses turned moderate after the human visual system adopted to the lighting environment. However, the effect of the Ryodoraku value on human physiological responses was more significant with the increase of perceptive time. The effect of long time exposure to a lighting environment on the physiological responses is greater than its effect on the psychological responses. This conclusion is different from the traditional public viewpoint that the effect on the psychological responses is greater.

Keywords: Autonomic nervous system, Human responses, Office Lighting Environment, Ryodoraku, Meridian

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Authors: Haruo Okabayashi

Abstract:

The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: Embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon.

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: Clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring.

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