Maksim Alekhin

Application of step-frequency radars in medicine

The paper summarizes results of step-frequency radars application in medicine. Remote and non-contact control of physiological parameters with modern bioradars provides a wide range of possibilities for non-contact remote monitoring of a human psycho-emotional state and physiological condition. The paper provides information about technical characteristics of bioradars designed at Bauman Moscow State Technical University and experiments using them. Results of verification experiment showed that bioradars of BioRASCAN type may be used for simultaneous remote measurements of breathing and heart rate parameters. In addition, bioradar assisted experiments for detecting of different sleep disorders are described. Their results proved that method of bioradiolocation allows correct estimation of obstructive sleep apnea severity compared to the polysomnography method, which satisfies standard medical recommendations.

Comparison of Bioradiolocation and Respiratory Plethysmography Signals in Time and Frequency Domains on the Base of Cross-Correlation and Spectral Analysis

Comparison of bioradiolocation and standard respiratory plethysmography signals during simultaneous registration of different types of the human breathing movements is performed in both time and frequency domains. For all couples of synchronized signals corresponding to bioradiolocation and respiratory plethysmography methods, the cross-correlation and spectral functions are calculated, and estimates of their generalized characteristics are defined. The obtained results consider bioradiolocation to be a reliable remote sensing technique for noncontact monitoring of breathing pattern in medical applications.

A Novel Method for Recognition of Bioradiolocation Signal Breathing Patterns for Noncontact Screening of Sleep Apnea Syndrome

A novel method for recognition of breathing patterns of bioradiolocation signals breathing patterns (BSBP) in the task of noncontact screening of sleep apnea syndrome (SAS) is proposed and implemented on the base of wavelet transform (WT) and neural network (NNW) applications. Selection of the optimal parameters of WT includes determination of the proper level of wavelet decomposition and the best basis for feature extraction using modified entropy criterion. Selection of the optimal properties of NNW includes defining the best number of hidden neurons and learning algorithm for the chosen NNW topology. The effectiveness of the proposed approach is tested on clinically verified database of BRL signals corresponding to the three classes of breathing patterns: obstructive sleep apnea (OSA); central sleep apnea (CSA); normal calm sleeping (NCS) without sleep-disordered breathing (SDB) episodes.

Estimation of respiratory rhythm during night sleep using a bio-radar

An assessment of bio-radiolocation monitoring of respiratory rhythm during sleep is given. Full-night respiratory inductance plethysmography (RIP) and bio-radiolocation (BRL) records were collected simultaneously in a sleep laboratory. Polysomnography data from 5 subjects without sleep breathing disorders were used. A multi-frequency bioradar with step frequency modulation was applied. It has 8 operating frequencies ranging from 3.6 to 4.0 GHz. BRL data are recorded in two quadratures. Respiratory cycles were detected in time domain. Obtained data was used for the evaluation of correlation between BRL and RIP respiration rate estimates. Strong correlation between corresponding time series was revealed. BRL method is reliably implemented for estimation of respiratory rhythm and respiratory rate variability during full night sleep.

Bioradiolocation as a Technique for Remote Monitoring of Vital Signs

8.

Bioradiolocation: Methods and Applications

Remote and non-contact control of physiological parameters with modern radiolocation means application provides a great amount of possibilities for non-contact remote monitoring of human psycho-emotional state and physiological condition. The practical significance of bio-radiolocation monitoring applications is especially urgent for rescue services and law enforcement bodies, as well as for medicine, particularly, in somnology. The paper presents the experimental results of step-frequency modulated bioradar usage for wide range of medical applications.

Организация системного проектирования и технической поддержки оборонных исследовательских программ DARPA

Currently a vast number of scientific publications in Russia and abroad are devoted to the phenomenon of Defense Advanced Research Projects Agency (DARPA). Success factors of the Agency are usually identified as: a recruitment policy of research managers, scientific resources of the Agency’s contractors, unique super-system of the DARPAs external environment and significant costs of R&D initiatives spent by the US Department of Defense. At the same time, systems engineering and technical assistance (SETA) contracting in the implementation of DARPAs high-risk projects have been neglected as a rule by the time. This paper describes the role of SETA-support contractors in ensuring the success of DARPAs ambitious projects and the impact of government contracts technical support on perspective defense R&D programs. The SETA rate in total R&D expenditures of DARPA are evaluated as 7,4-9,9%. Finally, the possibility of implementation of best practices and experiences of SETA system utilization for technological support of perspective high-risk R&D programs for governmental Russian agencies is analyzed.

Selection of Wavelet Transform and Neural Network Parameters for Classification of Breathing Patterns of Bio-radiolocation Signals

A novel method for classification of breathing patterns of bio-radiolocation signals breathing patterns (BSBP) in the task of non-contact screening of sleep apnea syndrome (SAS) is proposed, implemented on the base of wavelet transform (WT) and neural network (NNW) application with automated selection of their optimal parameters. The effectiveness of the proposed approach is tested on clinically verified database of BRL signals corresponding to the three classes of breathing patterns: obstructive sleep apnea (OSA); central sleep apnea (CSA); normal calm sleeping (NCS) without sleep- disordered breathing (SDB) episodes.