Abstract: A method utilizing computer processing for detecting, within a cardiac cycle, the earliest onset of global, Q-onset, ventricular depolarization in the presence of an operating pacemaker. The method, in general terms, features (a) gathering a plurality of ECG-obtained QRS heart-cycles waveforms, (b) identifying and categorizing of evidences and specific timings therein of intrinsic Q-onset and pacemaker spike events, (c) looking in a single, selected QRS waveform, between specific, defined first and second time marks, for the most significant slope change appearing in that waveform, and (d) designating to be the correct Q-onset that event which immediately precedes that slope change.

Abstract: A vector method for monitoring a subject's sleep-disordered breathing utilizing a single, anatomy-attached (anatomically outside or implanted inside), three-orthogonal-axis accelerometer(s), including the steps of (1) collecting from a sleeping subject three-orthogonal-axis data relating to at least one of sound data, subject posture, subject activity, snoring, and respiration, and (2) following such collecting, processing and analyzing collected data to detect associated, disordered breathing including assessing the presence of at least one of (a) sleep-disordered breathing generally, (b) sleep apnea specifically, and (c) differentiation between central and obstructive sleep apnea. Further involved is the acquiring of ECG data, and that the mentioned processing and analyzing include recognition of such acquired ECG data.

Abstract: A vector method for monitoring a subject's hemodynamic condition including (a) utilizing at least one, external or internal, anatomy-attached, three-axis accelerometer, collecting from the subject, during a selected cardiac cycle, related, three-orthogonal-axes accelerometer signal data, (b) following such collecting, processing collected signal data to obtain associated, signal vector, magnitude and directionality information, and (c) analyzing such obtained vector information for assessment of the subject's heart hemodynamic condition. ECG and signal time-frequency data is also collected and used in certain manners and implementations of the invention.

Abstract: Combining, to a singularity, from a plurality of anatomical sites, and over a plurality of heart cycles a collection of selected heart-functionality parameter measurements, such as EMAT, LVST, PADT, and AAFT measurements, including (a) collecting ECG and heart-sound data from plural anatomical sites, (b) computer processing such data to acquire plural, per-site, per-heart-cycle, nominal values for the selected parameter, (c) utilizing arithmetic mean and selected variance calculations related to such nominal values processing, and determined weight coefficients, computing weighted nominal values, (d) computing a weighted, nominal-value average of all of the nominal values by summing all of the weighted values and dividing that sum by the sum of all of the weight coefficients, and (e) presenting the computed weighted average as the combined, singularity value of the selected heart-functionality parameter.

Abstract: A vector method for monitoring a subject's hemodynamic condition including (a) utilizing at least one, external or internal, anatomy-attached, three-axis accelerometer, collecting from the subject, during a selected cardiac cycle, related, three-orthogonal-axes accelerometer signal data, (b) following such collecting, processing collected signal data to obtain associated, signal vector, magnitude and directionality information, and (c) analyzing such obtained vector information for assessment of the subject's heart hemodynamic condition. ECG and signal time-frequency data is also collected and used in certain manners and implementations of the invention.

Abstract: A vector method for monitoring a subject's sleep-disordered breathing utilizing a single, anatomy-attached (anatomically outside or implanted inside), three-orthogonal-axis accelerometer(s), including the steps of (1) collecting from a sleeping subject three-orthogonal-axis data relating to at least one of sound data, subject posture, subject activity, snoring, and respiration, and (2) following such collecting, processing and analyzing collected data to detect associated, disordered breathing including assessing the presence of at least one of (a) sleep-disordered breathing generally, (b) sleep apnea specifically, and (c) differentiation between central and obstructive sleep apnea. Further involved is the acquiring of ECG data, and that the mentioned processing and analyzing include recognition of such acquired ECG data.

Abstract: A method utilizing computer processing for detecting, within a cardiac cycle, the earliest onset of global, Q-onset, ventricular depolarization in the presence of an operating pacemaker. The method, in general terms, features (a) gathering a plurality of ECG-obtained QRS heart-cycles waveforms, (b) identifying and categorizing of evidences and specific timings therein of intrinsic Q-onset and pacemaker spike events, (c) looking in a single, selected QRS waveform, between specific, defined first and second time marks, for the most significant slope change appearing in that waveform, and (d) designating to be the correct Q-onset that event which immediately precedes that slope change.

Abstract: Combining, to a singularity, from a plurality of anatomical sites, and over a plurality of heart cycles a collection of selected heart-functionality parameter measurements, such as EMAT, LVST, PADT, and AAFT measurements, including (a) collecting ECG and heart-sound data from plural anatomical sites, (b) computer processing such data to acquire plural, per-site, per-heart-cycle, nominal values for the selected parameter, (c) utilizing arithmetic mean and selected variance calculations related to such nominal values processing, and determined weight coefficients, computing weighted nominal values, (d) computing a weighted, nominal-value average of all of the nominal values by summing all of the weighted values and dividing that sum by the sum of all of the weight coefficients, and (e) presenting the computed weighted average as the combined, singularity value of the selected heart-functionality parameter.

Abstract: A method and system for diagnosing left ventricular hypertrophy (“LVH”) based on ECG data. An LVH system provides an indication of the likelihood that a patient has LVH based on an analysis of the patient's ECG data. The LVH system estimates the left ventricular mass index (“LVMI”) for the patient based on gender-specific formulae that use time-voltage data derived from the ECG data. After the LVH system calculates the estimated LVMI for the patient, it then classifies the estimated LVMI to indicate the likelihood that the patient has LVH. The LVH system may then select various statements of condition and rationale based on the patient's classification.