The present invention relates to an electrocardiogram measurement apparatus (measurement sensor) which can be used in combination with a smartphone by an individual. The electrocardiogram measurement apparatus according to the present invention comprises: two amplifiers for receiving electrocardiogram signals from a first electrode and a second electrode; one electrode driving unit; a third electrode for receiving an output of the electrode driving unit; an A/D converter connected to an output terminal of each of the two amplifiers and converting analog signals into digital signals; a microcontroller for receiving the digital signals from the A/D converter; and a communication means for transmitting the digital signal, wherein: the microcontroller is supplied with power from a battery; the microcontroller controls the A/D converter and the communication means; and each of the two amplifiers amplifies one electrocardiogram signal so as to simultaneously measure two electrocardiogram signals.

The invention provides a system and method for measuring vital signs (e.g. SYS, DIA, SpO2, heart rate, and respiratory rate) and motion (e.g. activity level, posture, degree of motion, and arm height) from a patient. The system features: (i) first and second sensors configured to independently generate time-dependent waveforms indicative of one or more contractile properties of the patient's heart; and (ii) at least three motion-detecting sensors positioned on the forearm, upper arm, and a body location other than the forearm or upper arm of the patient. Each motion-detecting sensor generates at least one time-dependent motion waveform indicative of motion of the location on the patient's body to which it is affixed. A processing component, typically worn on the patient's body and featuring a microprocessor, receives the time-dependent waveforms generated by the different sensors and processes them to determine: (i) a pulse transit time calculated using a time difference between features in two separate time-dependent waveforms, (ii) a blood pressure value calculated from the time difference, and (iii) a motion parameter calculated from at least one motion waveform.

The invention provides a system and method for measuring vital signs (e.g. SYS, DIA, SpO2, heart rate, and respiratory rate) and motion (e.g. activity level, posture, degree of motion, and arm height) from a patient. The system features: (i) first and second sensors configured to independently generate time-dependent waveforms indicative of one or more contractile properties of the patient's heart; and (ii) at least three motion-detecting sensors positioned on the forearm, upper arm, and a body location other than the forearm or upper arm of the patient. Each motion-detecting sensor generates at least one time-dependent motion waveform indicative of motion of the location on the patient's body to which it is affixed. A processing component, typically worn on the patient's body and featuring a microprocessor, receives the time-dependent waveforms generated by the different sensors and processes them to determine: (i) a pulse transit time calculated using a time difference between features in two separate time-dependent waveforms, (ii) a blood pressure value calculated from the time difference, and (iii) a motion parameter calculated from at least one motion waveform.

A seat assembly may include a seat, a first bladder assembly connected to the seat, a second bladder assembly connected to the seat, and/or an electrical control unit (ECU) configured to independently control the first bladder assembly and the second bladder assembly. The ECU may be configured to maintain a level of inflation of the first bladder assembly to provide a hugging effect to a user of the seat while inflating and deflating the second bladder assembly to guide breathing of said user.

A seat assembly may include a seat, a first bladder assembly connected to the seat, a second bladder assembly connected to the seat, and/or an electrical control unit (ECU) configured to independently control the first bladder assembly and the second bladder assembly. The ECU may be configured to maintain a level of inflation of the first bladder assembly to provide a hugging effect to a user of the seat while inflating and deflating the second bladder assembly to guide breathing of said user.

A dynamic wake-up alarm is provided-for, including a clock, a contactless biometric sensor, a processor, memory, and a speaker. The processor may be configured to receive a wake-up rule based on at least two wake-up criteria including a time from the clock and data from the biometric sensor, and evaluate whether the criteria are met to activate an alarm.

A dynamic wake-up alarm is provided-for, including a clock, a contactless biometric sensor, a processor, memory, and a speaker. The processor may be configured to receive a wake-up rule based on at least two wake-up criteria including a time from the clock and data from the biometric sensor, and evaluate whether the criteria are met to activate an alarm.

A system including a sensor interface coupled to a processor. The sensor interface is configured to receive and process an analog electrocardiogram signal of a subject and provide a digitized electrocardiogram signal sampled over a first time period and a second time period that is subsequent to the first time period. The processor is configured to receive the digitized electrocardiogram signal, to analyze a frequency domain transform of the digitized electrocardiogram signal sampled over the first and second time periods and determine first and second metrics indicative of metabolic state of a myocardium of the subject during the first and second time periods, respectively, to compare the first and second metrics to determine whether the metabolic state of the myocardium of the subject is improving, and to indicate administration of an intervention to the subject in response to a determination that the metabolic state is not improving.

A sleep monitor for monitoring baby sleep uses sleep state classification based on heartbeat feature respiration features. The sleep monitor automatically retrains the classification during use of the sleep monitor. Training examples for use in this training process are generated automatically by detecting time instants whereat the baby in the bed is in a wake state, based on signals from the at least one of a sound feature detector a movement feature detector (112) and an open eye detector (114). The retraining may comprise using time sequence from the end of detection of wake states to assign a class to heartbeat feature and/or respiration feature values during that time sequence for the training process. In an embodiment, the retraining comprises clustering detected heartbeat feature and/or respiration feature values detected outside the detected wake states.

A sleep monitor for monitoring baby sleep uses sleep state classification based on heartbeat feature respiration features. The sleep monitor automatically retrains the classification during use of the sleep monitor. Training examples for use in this training process are generated automatically by detecting time instants whereat the baby in the bed is in a wake state, based on signals from the at least one of a sound feature detector a movement feature detector (112) and an open eye detector (114). The retraining may comprise using time sequence from the end of detection of wake states to assign a class to heartbeat feature and/or respiration feature values during that time sequence for the training process. In an embodiment, the retraining comprises clustering detected heartbeat feature and/or respiration feature values detected outside the detected wake states.