Publications by authors named "Ayyoob Jafari"

5 Publications

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Prevalence of behavioural risk factors for road-traffic injuries among the Iranian population: findings from STEPs 2016.

Int J Epidemiol 2019 08;48(4):1187-1196

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Background: To achieve Sustainable Development Goal 3.6 in Iran, we need to have a comprehensive understanding of the distribution of risky behaviours regarding road-traffic injuries at national and sub-national levels. Little is known about the road-use vulnerability patterns of road-traffic injuries in Iran. The aim of this study is to describe the prevalence of self-reported human risk factors in road-traffic injuries using the findings from a large-scale cross-sectional study based on the World Health Organization's stepwise approach to surveillance of non-communicable diseases (STEPs).

Methods: A cross-sectional survey study in 2016 assessed the road-use pattern and prevalence of risky behaviours of people more than 18 years old. In this study, we planned to recruit 31 050 individuals as a representative sample at national and provincial levels. In practice, 30 541 individuals (3105 clusters) from urban and rural areas of Iran were selected. Basic socio-demographic data, major behavioural risk factors such as seatbelt and helmet non-compliance, drunk driving and occupant in a car with a drunk driver were assessed through baseline interviews gathered through an Android tablet-based questionnaire.

Results: The overall prevalence of seatbelt and helmet compliance was 75.2% (95% confidence interval: 74.7-75.7) and 13.9% (13.4-14.5), respectively, at the national level. The prevalence of risk-taking behaviours such as drink driving was 0.5% (0.4-0.6) and for being an occupant in a car with a drunk driver was 3.5% (3.2-3.8). At the provincial level, the highest age-standardized prevalence of seatbelt compliance (89.6%) was almost 1.5 times higher than the lowest provincial prevalence (58.5%). In 63% of provinces, the lowest prevalence of seatbelt compliance was observed among people aged 18-24 years old.

Conclusions: In Iran, existing disease-prevention and health-promotion programmes should be expanded to target vulnerable subgroups that have more prevalent human risk factors for road-traffic injuries. Further research is required to investigate the context-specific proximal human risk factors and vulnerability patterns in Iran.
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http://dx.doi.org/10.1093/ije/dyz021DOI Listing
August 2019

An Approach Towards Reducing Road Traffic Injuries and Improving Public Health Through Big Data Telematics: A Randomised Controlled Trial Protocol.

Arch Iran Med 2018 11 1;21(11):495-501. Epub 2018 Nov 1.

Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

Objective: Deaths due to road traffic accidents (RTAs) are a major public health concern around the world. Developing countries are over-represented in these statistics. Punitive measures are traditionally employed to lower RTA related behavioural risk factors. These are, however, resource intensive and require infrastructure development. This is a randomised controlled study to investigate the effect of non-punitive behavioural intervention through peer-comparison feedback based on driver behaviour data gathered by an in-vehicle telematics device.

Design, Setting, And Participants: A randomised controlled trial using repeated measures design conducted in Iran on the drivers of 112 public transport taxis in Tehran province and 1309 inter-city busses operating nationwide. Driving data is captured by an in-vehicle telematics device and sent to a centrally located data centre using a mobile network. The telematics device is installed in all vehicles. Participants are males aged above 20 who have had the device operating in their vehicles for at least 3 months prior to the start of the trial.

Intervention: The study had three stages: 1- Driver performance was monitored for a 4-week period after which they were randomised into intervention and control groups. 2- Their performance was monitored for a 9-week period. At the end of each week, drivers in the intervention group received a scorecard and a note informing them of their weekly behaviour and ranking within their peer group. Drivers in the control group received no feedback via short messaging service (SMS). 3- Drivers did not receive further feedback and their behaviour was monitored for another 4 weeks.

Primary And Secondary Outcome Measure: Primary outcome was changes in weekly driving score in intervention and control groups during stage 2 of intervention. Taxis and busses were analysed separately using generalised estimating equation analysis.

Funding And Ethical Approval: This project was funded by the National Institute for Medical Research Development (Grant No.940576) and approved by its ethics committee (Code: IR.NIMAD.REC.1394.016). This trial was registered at www.irct.ir as IRCT20180708040391N1.
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November 2018

Do the chaotic features of gait change in Parkinson's disease?

J Theor Biol 2012 Aug 12;307:160-7. Epub 2012 May 12.

Electrical Engineering Faculty, Sahand University of Technology, Tabriz, Iran.

Some previous studies have focused on chaotic properties of Parkinson's disease (PD). It seems that considering PD from dynamical systems perspective is a relevant method that may lead to better understanding of the disease. There is some ambiguity about chaotic nature in PD symptoms and normal behaviour. Some studies claim that normal gait has somehow a chaotic behaviour and disturbed gait in PD has decreased chaotic nature. However, it is worth noting that the basis of this idea is the difference of fractal behaviour in gait of normal and PD patients, which is concluded from Long Range Correlation (LRC) indices. Our primary calculations show that a large number of normal persons and patients have similar LRC. It seems that chaotic studies on PD need a different view. Because of short time recording of symptoms, accurate calculation of chaotic features is tough. On the other hand, long time recording of symptoms is experimentally difficult. In this research, we have first designed a physiologically plausible model for normal and PD gait. Then, after validating the model with neural network classifier, we used the model for extracting long time simulation of stride in normal and PD persons. These long time simulations were then used for calculating the chaotic features of gait. According to change of phase space behaviour and alteration of three largest lyapunov exponents, it was observed that simulated normal persons act as chaotic systems in stride production, but simulated PD does not have chaotic dynamics and is stochastic. Based on our results, it may be claimed that normal gait has chaotic nature which is disturbed in PD state. Surely, long time real recordings from gait signal in normal persons and PD patients are necessary to warranty this hypothesis.
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http://dx.doi.org/10.1016/j.jtbi.2012.04.032DOI Listing
August 2012

Modeling the gait of normal and Parkinsonian persons for improving the diagnosis.

Neurosci Lett 2012 Feb 7;509(2):72-5. Epub 2011 Nov 7.

Neuromuscular Systems Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

In this study, we present a model for the gait of normal and Parkinson's disease (PD) persons. Gait is semi-periodic and has fractal properties. Sine circle map (SCM) relation has a sinusoidal term and can show chaotic behaviour. Therefore, we used SCM as a basis for our model structure. Moreover, some similarities exist between the parameters of this relation and basal ganglia (BG) structure. This relation can explain the complex behaviours and the complex structure of BG. The presented model can simulate the BG behaviour globally. A model parameter, Ω, has a key role in the model response. We showed that when Ω is between 0.6 and 0.8, the model simulates the behaviour of normal persons; the amounts greater or less than this range correspond to PD persons. Our statistical tests show that there is a significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons. Additionally, our results showed that Spearman correlation between the Ω and the severity of PD is 0.586. This parameter may be a good index of PD severity.
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http://dx.doi.org/10.1016/j.neulet.2011.10.002DOI Listing
February 2012

Statistical modeling of speech Poincaré sections in combination of frequency analysis to improve speech recognition performance.

Chaos 2010 Sep;20(3):033106

Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.

This paper introduces a combinational feature extraction approach to improve speech recognition systems. The main idea is to simultaneously benefit from some features obtained from Poincaré section applied to speech reconstructed phase space (RPS) and typical Mel frequency cepstral coefficients (MFCCs) which have a proved role in speech recognition field. With an appropriate dimension, the reconstructed phase space of speech signal is assured to be topologically equivalent to the dynamics of the speech production system, and could therefore include information that may be absent in linear analysis approaches. Moreover, complicated systems such as speech production system can present cyclic and oscillatory patterns and Poincaré sections could be used as an effective tool in analysis of such trajectories. In this research, a statistical modeling approach based on Gaussian mixture models (GMMs) is applied to Poincaré sections of speech RPS. A final pruned feature set is obtained by applying an efficient feature selection approach to the combination of the parameters of the GMM model and MFCC-based features. A hidden Markov model-based speech recognition system and TIMIT speech database are used to evaluate the performance of the proposed feature set by conducting isolated and continuous speech recognition experiments. By the proposed feature set, 5.7% absolute isolated phoneme recognition improvement is obtained against only MFCC-based features.
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http://dx.doi.org/10.1063/1.3463722DOI Listing
September 2010