At least one computing device programmed to implement a method of analyzing electromechanical characteristics of a heart of a subject, the method comprising producing at least one inference, wherein producing the at least one inference comprises analyzing, in a plurality of models associated with respective different types of inference, at least: a time series of electrocardiogram measurements of the heart and measured during a first period of time; and a time series of measurements of movement caused by the heart during a second period of time at least overlapping with the first period of time, wherein the measurements of movement comprise measurements of rotational movement caused by the heart around at least one axis of rotation (270, 272, 274); characterized in that producing the at least one inference comprises feature extraction of at least three time segments of, at least, the time series of measurements of movement; and wherein the at least three time segments comprise: a high-energy systole time segment, wherein the high-energy systole time segment is defined as between: a start of systolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of systolic vibration identified in the time series of measurements of movement; a high-energy diastole time segment, wherein the high-energy diastole time segment is defined as between: a start of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of diastolic vibration identified in the time series of measurements of movement; and a low-energy diastole time segment, wherein the low-energy diastole time segment is defined as between: an end of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent "Q" wave of the time series of ECG measurements. a time series of electrocardiogram measurements of the heart and measured during a first period of time; and a time series of measurements of movement caused by the heart during a second period of time at least overlapping with the first period of time, wherein the measurements of movement comprise measurements of rotational movement caused by the heart around at least one axis of rotation (270, 272, 274); characterized in that producing the at least one inference comprises feature extraction of at least three time segments of, at least, the time series of measurements of movement; and wherein the at least three time segments comprise: a high-energy systole time segment, wherein the high-energy systole time segment is defined as between: a start of systolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of systolic vibration identified in the time series of measurements of movement; a high-energy diastole time segment, wherein the high-energy diastole time segment is defined as between: a start of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of diastolic vibration identified in the time series of measurements of movement; and a low-energy diastole time segment, wherein the low-energy diastole time segment is defined as between: an end of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent "Q" wave of the time series of ECG measurements. a high-energy systole time segment, wherein the high-energy systole time segment is defined as between: a start of systolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of systolic vibration identified in the time series of measurements of movement; a start of systolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of systolic vibration identified in the time series of measurements of movement; a high-energy diastole time segment, wherein the high-energy diastole time segment is defined as between: a start of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of diastolic vibration identified in the time series of measurements of movement; and a start of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent end of diastolic vibration identified in the time series of measurements of movement; and a low-energy diastole time segment, wherein the low-energy diastole time segment is defined as between: an end of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent "Q" wave of the time series of ECG measurements. an end of diastolic vibration identified in the time series of measurements of movement; and an immediately subsequent "Q" wave of the time series of ECG measurements.