Classification of Atrial Fibrillation and Acute Decompensated Heart Failure Using Smartphone Mechanocardiography: A Multilabel Learning Approach

Abstract

Timely diagnosis of cardiovascular diseases (CVD) is crucial to prevent morbidity and mortality. Atrial fibrillation (AFib) and heart failure (HF) are two prevalent cardiac disorders that are associated with a high risk of morbidity and mortality, especially if they are concurrently present. Current approaches fail to screen many at-risk individuals who would benefit from preventive treatment; while others receive unnecessary interventions. An effective approach to the detection of CVDs is mechanocardiography (MCG) by which translational and rotational precordial chest movements are monitored. In this study, we collected MCG data from a study sample of 300 hospitalized cardiac patients using multidimensional built-in inertial sensors of a smartphone. Our main objective was to detect concurrent AFib and acute decompensated HF (ADHF) using smartphone MCG (or sMCG). To this end, we adopted a supervised machine learning classification using multi-label and hierarchical classification. Logistic regression, random forest, and extreme gradient boosting were used as candidate classifiers. The results of the analysis showed the area under the receiver operating characteristic curve values of 0.98 and 0.85 for AFib and ADHF, respectively. The highest percentages of positive and negative predictive values for AFib were 91.9 and 100; while for ADHF, they were 56.9 and 88.4 for the multi-label classificationand 69.9 and 68.8 for the hierarchical classification,respectively. We conclude that using a single sMCG measurement, AFib can be detected accurately whereas ADHF can be detected with moderate certainty.

Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers

“…That fact confirms the possibility of conducting HRV analysis on seismocardiograms [ 3 , 4 , 13 , 19 , 20 , 36 ] and gyrocardiograms [ 39 ] as well as on electrocardiograms. C. Yang et al [ 23 ], Z. Iftikhar et al [ 32 ] and S. Mehrang et al [ 22 ] use heartbeat detection and heart rate variability to craft features in classification of cardiovascular diseases. However, they did not concentrate on HRV analysis and that fact hampers the comparison of the results of HRV analysis on healthy patients and patients suffering from cardiovascular diseases.…”

“…Technological improvements and miniaturization of accelerometers make seismocardiography a useful non-invasive technique for examining cardiac activity [ 5 , 11 , 12 , 13 , 14 ]. The applications of SCG include heart monitoring during magnetic resonance imaging (MRI) scan [ 15 , 16 ], monitoring response to cardiac interventions [ 5 ] heart rate variability analysis [ 4 , 13 , 17 , 18 , 19 , 20 ], the detection of atrial fibrillation [ 6 , 21 , 22 ], heart failure [ 22 , 23 ] and the diagnosis of myocardial ischemia [ 5 , 24 , 25 , 26 ].…”

“…Gyrocardiograms (GCG signals) were used to improve the reliability of HRV analysis on mechanocardiograms. Iftikhar et al [ 32 ] and Mehrang et al [ 22 ] crafted features based on heart rate variability on mechanocardiograms to classify between healthy subjects and patients suffering from atrial fibrillation, coronary artery disease and acute decompensated heart failure.…”

Gyrocardiography: A Review of the Definition, History, Waveform Description, and Applications

“…They compared the waveforms, spectra, amplitude ranges, bispectra, the length and the area of the cardiac cycle [ 76 ]. In the same year, Mehrang et al [ 77 ] proposed a new classifier of cardiac diseases (atrial fibrillation and acute decompensated heart failure) based on SCG and GCG signals. The classification was based on random forests, extreme gradient boosting (XGB) and logistic regression (LR).…”

“…The GCG along with the SCG and BCG constitute the mechanocardiography (MCG) or vibrational cardiography (VCG). The first term was proposed by [ 24 , 49 , 55 , 58 , 60 , 64 , 65 , 71 , 73 , 77 , 88 ] and the second term was proposed by [ 9 , 73 , 79 , 80 ].…”