This paper presents a fully automated procedure for acquiring and analyzing seismocardiographic (SCG) traces from an Inertial Measurement Unit (IMU) placed over a subject’s sternum. An automated calibration procedure allows for straightforward adaption to different subjects. Calibration is performed once per subject, exploiting ECG (electrocardiogram) markers; relevant patterns and parameters are automatically extracted and used for successive SCG processing, which does not require concurrent ECG information any longer. Annotation of SCG traces is performed in two steps: in the first one, a suitably engineered signal is derived from SCG and used as coarse heartbeat detector; then, annotation can be performed by comparing the prototype extracted at calibration time with segments of SCG data, near to the detected beats. The proposed methodology is validated by direct comparison with ECG, adopted as gold-standard. In particular, three main metrics are taken into account: sensitivity (i.e. percentage of correctly identified heartbeats, compared to ECG), precision (i.e. impact of false positives on truly detected beats) and R2 (i.e. linearity between beat-to-beat measurements as computed by ECG and SCG). Results show satisfactory performance, more than adequate to continuous, long-term monitoring: overall, approximately 90% of heartbeats are correctly detected, on average, with minimal false positives (≈1%). Linearity between ECG and SCG-computed beat-to-beat intervals is extremely high (R2 > 0.95, on average), indicating good agreement between the two measurement methods. These results suggest SCG can be used as a reliable, contactless measure of heart-related parameters.

Fully Automated Annotation of Seismocardiogram for Noninvasive Vital Sign Measurements / Mora, Niccolo; Cocconcelli, Federico; Matrella, Guido; Ciampolini, Paolo. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - 69:4(2020), pp. 1241-1250. [10.1109/TIM.2019.2908511]

Fully Automated Annotation of Seismocardiogram for Noninvasive Vital Sign Measurements

Mora, Niccolo;Cocconcelli, Federico;Matrella, Guido;Ciampolini, Paolo
2020

Abstract

This paper presents a fully automated procedure for acquiring and analyzing seismocardiographic (SCG) traces from an Inertial Measurement Unit (IMU) placed over a subject’s sternum. An automated calibration procedure allows for straightforward adaption to different subjects. Calibration is performed once per subject, exploiting ECG (electrocardiogram) markers; relevant patterns and parameters are automatically extracted and used for successive SCG processing, which does not require concurrent ECG information any longer. Annotation of SCG traces is performed in two steps: in the first one, a suitably engineered signal is derived from SCG and used as coarse heartbeat detector; then, annotation can be performed by comparing the prototype extracted at calibration time with segments of SCG data, near to the detected beats. The proposed methodology is validated by direct comparison with ECG, adopted as gold-standard. In particular, three main metrics are taken into account: sensitivity (i.e. percentage of correctly identified heartbeats, compared to ECG), precision (i.e. impact of false positives on truly detected beats) and R2 (i.e. linearity between beat-to-beat measurements as computed by ECG and SCG). Results show satisfactory performance, more than adequate to continuous, long-term monitoring: overall, approximately 90% of heartbeats are correctly detected, on average, with minimal false positives (≈1%). Linearity between ECG and SCG-computed beat-to-beat intervals is extremely high (R2 > 0.95, on average), indicating good agreement between the two measurement methods. These results suggest SCG can be used as a reliable, contactless measure of heart-related parameters.
Fully Automated Annotation of Seismocardiogram for Noninvasive Vital Sign Measurements / Mora, Niccolo; Cocconcelli, Federico; Matrella, Guido; Ciampolini, Paolo. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - 69:4(2020), pp. 1241-1250. [10.1109/TIM.2019.2908511]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2871185
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