An apparatus for monitoring cardiac stroke volume in a patient, the apparatus comprising: (a) a plurality of Integrated Cardio Respiratory acoustic sensors configured to be positioned on the chest of the patient; (b) a processor coupled to the plurality of ICR acoustic sensors; and (c) a non-transitory memory storing instructions executable by the processor; (d) wherein said instructions, when executed by the processor, perform steps comprising: (i) receiving a phonocardiogram acoustic signal from the plurality of ICR acoustic sensors; (ii) segmenting the PCG acoustic signal to locate one or more cardiac events in the PCG acoustic signal; (iii) extracting one or more of temporal and amplitude characteristics from the PCG acoustic signal; (iv) classifying the extracted characteristics into one or more subgroups; (v) computing the SV of the patient based on the classified characteristics comprising: 1) computing ejection fraction values based on extracted characteristics; 2) assigning a subject into a subgroup based on computed EF values: 3) computing a carrier signal via phonocardiogram Carrier Signal Analysis, which comprises AM-FM decomposition of S1 and S2 events within the PCG signal to yield a carrier signal with unit amplitude; 4) for each subgroup, computing a PCSA feature (RPCSA) that is a ratio between the energy content contained in a high-frequency band of the carrier signal relative to that contained in a low-frequency band; and 5) within each subgroup, applying a second order quadratic transform to PCSA feature (RPCSA) to compute an SV estimate; and (vi) outputting the computed SV of the patient. (a) a plurality of Integrated Cardio Respiratory acoustic sensors configured to be positioned on the chest of the patient; (b) a processor coupled to the plurality of ICR acoustic sensors; and (c) a non-transitory memory storing instructions executable by the processor; (d) wherein said instructions, when executed by the processor, perform steps comprising: (i) receiving a phonocardiogram acoustic signal from the plurality of ICR acoustic sensors; (ii) segmenting the PCG acoustic signal to locate one or more cardiac events in the PCG acoustic signal; (iii) extracting one or more of temporal and amplitude characteristics from the PCG acoustic signal; (iv) classifying the extracted characteristics into one or more subgroups; (v) computing the SV of the patient based on the classified characteristics comprising: 1) computing ejection fraction values based on extracted characteristics; 2) assigning a subject into a subgroup based on computed EF values: 3) computing a carrier signal via phonocardiogram Carrier Signal Analysis, which comprises AM-FM decomposition of S1 and S2 events within the PCG signal to yield a carrier signal with unit amplitude; 4) for each subgroup, computing a PCSA feature (RPCSA) that is a ratio between the energy content contained in a high-frequency band of the carrier signal relative to that contained in a low-frequency band; and 5) within each subgroup, applying a second order quadratic transform to PCSA feature (RPCSA) to compute an SV estimate; and (vi) outputting the computed SV of the patient. (i) receiving a phonocardiogram acoustic signal from the plurality of ICR acoustic sensors; (ii) segmenting the PCG acoustic signal to locate one or more cardiac events in the PCG acoustic signal; (iii) extracting one or more of temporal and amplitude characteristics from the PCG acoustic signal; (iv) classifying the extracted characteristics into one or more subgroups; (v) computing the SV of the patient based on the classified characteristics comprising: 1) computing ejection fraction values based on extracted characteristics; 2) assigning a subject into a subgroup based on computed EF values: 3) computing a carrier signal via phonocardiogram Carrier Signal Analysis, which comprises AM-FM decomposition of S1 and S2 events within the PCG signal to yield a carrier signal with unit amplitude; 4) for each subgroup, computing a PCSA feature (RPCSA) that is a ratio between the energy content contained in a high-frequency band of the carrier signal relative to that contained in a low-frequency band; and 5) within each subgroup, applying a second order quadratic transform to PCSA feature (RPCSA) to compute an SV estimate; and 1) computing ejection fraction values based on extracted characteristics; 2) assigning a subject into a subgroup based on computed EF values: 3) computing a carrier signal via phonocardiogram Carrier Signal Analysis, which comprises AM-FM decomposition of S1 and S2 events within the PCG signal to yield a carrier signal with unit amplitude; 4) for each subgroup, computing a PCSA feature (RPCSA) that is a ratio between the energy content contained in a high-frequency band of the carrier signal relative to that contained in a low-frequency band; and 5) within each subgroup, applying a second order quadratic transform to PCSA feature (RPCSA) to compute an SV estimate; and (vi) outputting the computed SV of the patient.