Repair Rates for Multiple Descriptions on Distributed Storage.

In a traditional distributed storage system, a source can be restored perfectly when a certain subset of servers is contacted. The coding is independent of the contents of the source. This paper considers instead a lossy source coding version of this problem where the more servers that are contacted, the higher the quality of the restored source. An example could be video stored on distributed storage. In information theory, this is called the multiple description problem, where the distortion depends on the number of descriptions received. The problem considered in this paper is how to restore the system operation when one of the servers fail and a new server replaces it, that is, repair. The requirement is that the distortions in the restored system should be no more than in the original system. The question is how many extra bits are needed for repair. We find an achievable rate and show that this is optimal in certain cases. One conclusion is that it is necessary to design the multiple description codes with repair in mind; just using an existing multiple description code results in unnecessary high repair rates.

Data Discovery and Anomaly Detection Using Atypicality for Real-Valued Data.

The aim of using atypicality is to extract small, rare, unusual and interesting pieces out of big data. This complements statistics about typical data to give insight into data. In order to find such "interesting" parts of data, universal approaches are required, since it is not known in advance what we are looking for. We therefore base the atypicality criterion on codelength. In a prior paper we developed the methodology for discrete-valued data, and the current paper extends this to real-valued data. This is done by using minimum description length (MDL). We develop the information-theoretic methodology for a number of "universal" signal processing models, and finally apply them to recorded hydrophone data and heart rate variability (HRV) signal.

Cardiopulmonary signal sensing from subject wearing body armor.

Continuous wave (CW) Doppler motion sensing radar can detect human physiological signal such as respiration or heart signals at a distance and through barriers. It has been shown that heart rate can be extracted with good accuracy for normally clothed subjects. Such technique could potentially be used to search for survivors in battlefield triage applications. To assess the feasibility of such applications, we investigated Doppler radar of cardiopulmonary signal sensing from subjects wearing body armor vests. This paper presents measurement results of heart signals obtained using CW Doppler radar from a subject wearing body armor vest. Since armor plate reflects most of the RF signal, received signal after reflected from a subject is phase modulated with motion of an armor plate induced by chest motion, rather than directly with chest motion due to cardiopulmonary motion. Two different cases, including supine and seated positions, are chosen for this study, and good sensitivity was obtained in both cases. To the best of author's knowledge, this is the first published result of cardiopulmonary signal detection from a subject wearing a body armor vest.

Feasibility of heart rate variability measurement from quadrature Doppler radar using arctangent demodulation with DC offset compensation.

This paper describes the experimental results of the beat-to-beat interval measurement from a quadrature Doppler radar system utilizing arctangent demodulation with DC offset compensation techniques. The comparison in SDNN and in RMSDD of both signals demonstrates the potential of using quadrature Doppler radar for HRV analysis.

Noise considerations for remote detection of life signs with microwave Doppler radar.

This paper describes and quantifies three main sources of baseband noise affecting physiological signals in a direct conversion microwave Doppler radar for life signs detection. They are thermal noise, residual phase noise, and Flicker noise. In order to increase the SNR of physiological signals at baseband, the noise floor, in which the Flicker noise is the most dominant factor, needs to be minimized. This paper shows that with the consideration of the noise factor in our Doppler radar, Flicker noise canceling techniques may drastically reduce the power requirement for heart rate signal detection by as much as a factor of 100.

Non-contact cardiopulmonary sensing with a baby monitor.

Cardiopulmonary signals can be detected at a distance using simple Doppler radars operating in CW mode. Tests with and without audio modulation show the feasibility of measurements with this hardware, providing a maximum measured difference to the reference of just 1.6bpm for heart rate. Tests show good correspondence of heart/respiration rate with the reference data.