Logo image
Forehead BCG Signal Analysis: Characterization and Robust Detection of Heartbeats Using Cosine Similarity and Energy-Based Approach
Conference paper

Forehead BCG Signal Analysis: Characterization and Robust Detection of Heartbeats Using Cosine Similarity and Energy-Based Approach

Chih-Man Chang, Rongching Dai and Kea-Tiong Tang
BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings
2023

Abstract

accelerometer Ballistocardiogram(BCG) beat-to-beat CosineSimilarity heart rate Signal Processing Biomedical Engineering Electrical and Electronic Engineering Neurology (clinical) Neurology
This work presents a ballistocardiogram (BCG) based beat-to-beat heart rate (HR) measurement algorithm for a portable that on the forehead. To address the diversity of BCG signals, we propose a beat-to-beat detection algorithm that can adapt to the varying shapes of BCG signals among different users. This algorithm utilizes similarity in shape, energy, and variations in interbeat intervals (IBI) to locate the heartbeat points. The algorithm has been verified on 10 subjects, where BCG and ECG signals were simultaneously recorded. By referencing the ECG signal, we have achieved a mean absolute relative error of 3.843% for beat-to-beat interval estimation. Moreover, on average, 99.442% of the beat-to-beat intervals are accurately detected.

Metrics

1 Record Views

Details

Logo image