TY - JOUR

T1 - Adaptive Techniques for Extracting Mental Activity Phases from Heart Beat Rate Streams

AU - Dubatovka, Alina

AU - Mikhailova, Elena

AU - Zotov, Mikhail

AU - Novikov, Boris

PY - 2016

Y1 - 2016

N2 - The paper presents algorithms for automatic detection of non-stationary periods of cardiac rhythm during professional activity. While working and subsequent rest operator passes through the phases of mobilization, stabilization, work, recovery and the rest. The amplitude and frequency of non-stationary periods of cardiac rhythm indicates the human resistance to stressful conditions. We introduce and analyze a number of algorithms for non-stationary phase extraction: the different approaches to phase preliminary detection, thresholds extraction and final phases extraction are studied experimentally. Due to very significant differences between streams obtained from different persons and relatively small amount of data common machine learning techniques do not work well with our data. Thus, we had to develop adaptive algorithms based on domain-specific high-level properties of data and adjust parameters based on the preliminary analysis of the stream, making the algorithms adaptive and thus able to capture indi

AB - The paper presents algorithms for automatic detection of non-stationary periods of cardiac rhythm during professional activity. While working and subsequent rest operator passes through the phases of mobilization, stabilization, work, recovery and the rest. The amplitude and frequency of non-stationary periods of cardiac rhythm indicates the human resistance to stressful conditions. We introduce and analyze a number of algorithms for non-stationary phase extraction: the different approaches to phase preliminary detection, thresholds extraction and final phases extraction are studied experimentally. Due to very significant differences between streams obtained from different persons and relatively small amount of data common machine learning techniques do not work well with our data. Thus, we had to develop adaptive algorithms based on domain-specific high-level properties of data and adjust parameters based on the preliminary analysis of the stream, making the algorithms adaptive and thus able to capture indi

KW - small data

KW - adaptive algorithm

KW - non-stationary data stream

KW - signal processing

KW - mental activity phases

KW - phase separation

U2 - 10.3233/978-1-61499-714-6-197

DO - 10.3233/978-1-61499-714-6-197

M3 - Article

VL - 291

SP - 197

EP - 210

JO - Frontiers in Artificial Intelligence and Applications

JF - Frontiers in Artificial Intelligence and Applications

SN - 0922-6389

ER -