Statistical Analysis of the Consistency of HRV Analysis Using BCG or Pulse Wave Signals

Abstract

Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including Coefficients of Variation (CV), Lin’s Concordance Correlation Coefficient (LCCC), and Bland-Altman analysis (BA ratio), were utilized to analyze the consistency of BCG and ECG signals in HRV analysis. If the methods gave different answers, the worst case was taken as the result. Measures of consistency such as Mean, SDNN, LF gave good agreement (the absolute value of CV difference < 2%, LCCC > 0.99, BA ratio < 0.1) between J-J (BCG) and R-R intervals (ECG). pNN50 showed moderate agreement (the absolute value of CV difference < 5%, LCCC > 0.95, BA ratio < 0.2), while RMSSD, HF, LF/HF indicated poor agreement (the absolute value of CV difference ≥ 5% or LCCC £ 0.95 or BA ratio ≥ 0.2). Additionally, the R-R intervals were compared with P-P intervals extracted from the pulse wave (PW). Except for pNN50, which exhibited poor agreement in this comparison, the performances of the HRV indices estimated from the PW and the BCG signals were similar.

Conception of an AI-based recommender system for labeling ballistocardiographic data

“…While medical conditions [2,7] and information about atypical signals [2] might be included as annotations on the signal as a whole, labels for specific anomalies are often omitted. While Heart rate and heart rate variability can be reliably extracted using signal processing methods [8,9], more complex features and anomalies are more challenging to extract [10]. Furthermore, there is considerable uncertainty regarding the interpretation of BCG waveform, leading to various different interpretations over the years [10].…”

ECG-Free Heartbeat Detection in Seismocardiography and Gyrocardiography Signals Provides Acceptable Heart Rate Variability Indices in Healthy and Pathological Subjects

“…In this regard, continuous, long-term monitoring would benefit from wearable devices, especially in daily life environments, all the more so if one considers that accelerometers and gyroscopes are largely integrated into smartphones nowadays. For these reasons, many studies investigated the suitability of cardio-mechanical signals for HRV analysis, particularly BCG [73][74][75], SCG [36,57,[76][77][78], and GCG [76,79]. Specific peaks or valleys of these signals, which correlate with important cardiac cycle events, were considered as heartbeat fiducial points, e.g., the aortic valve opening (AO) on SCG/GCG signals and the peak of the J wave on BCG signals.…”