Evaluating the lower-body electromyogram signal acquired from the feet as a noise reference for standing ballistocardiogram measurements.
The ballistocardiogram (BCG) is a measure of the reaction force of the body to cardiac ejection of blood. A variety of systems can be used for BCG detection, including beds, tables, chairs, and weighing scales. Weighing scales, in particular, have several practical advantages over the alternatives: low cost, small size, unobtrusiveness, and familiarity to the user; one disadvantage is that the subject must stand during the recording, rather than sit or lay supine, resulting in a higher susceptibility to motion artifacts in the measured signal. This paper evaluates the electromyogram (EMG) signal acquired from the feet of the subject during BCG recording as a noise reference for standing BCG measurements. As a subject moves while standing on the scale, muscle contractions in the feet are detected by the EMG signal, and used to flag segments of the BCG signal that are corrupted by elevated noise. For the purposes of evaluating this method, estimates of the BCG noise-to-signal ratio (NSR) were independently calculated with an ensemble average method, using the R-wave of a simultaneously-acquired chest ECG as a timing reference. The linear correlation between EMG power alone and BCG NSR from 14 subjects was found to be moderate ( r = 0.58, F-statistic p -value 0.05); combined with body-mass index (BMI), multiple linear regression yielded a stronger correlation ( r = 0.73, F -statistic p-value = 0.01). Additionally, an example usage of the lower-leg EMG for improving BCG measurement robustness is provided.
Inan
Omer T
OT
Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
Kovacs
Gregory T A
GT
Giovangrandi
Laurent
L
D000328:Adult; D016477:Artifacts; D001450:Ballistocardiography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D005260:Female; D005528:Foot / Q000502:physiology; D006801:Humans; D016014:Linear Models; D008297:Male; D009068:Movement; D011187:Posture; D012815:Signal Processing, Computer-Assisted