A system for treating and/or monitoring a patient includes a patient physiological parameter monitoring patch and a companion device. The patient physiological parameter monitoring patch including an energy harvesting module, an energy storage module, a sensor module and a communication module. The energy harvesting module harvesting energy from one or more ambient sources, the energy being storable in the energy storage module and usable by one or more components of the patient physiological parameter monitoring patch. The sensor module senses one or more physiological parameters of the patient and the communication module can transmit the sensed data. The companion device can receive the sensed physiological parameters and can send the same to a remote device or store the same.

A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network for determining blood pressure may include: receiving a request to determine blood pressure of a first subject from a terminal, obtaining data related to heart activity of the first subject, determining a personalized model for predicting blood pressure with respect to the first subject, determining the blood pressure of the first subject using the personalized model based on the data related to heart activity of the first subject, and sending the blood pressure of the first subject to the terminal in response to the request.

A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network for determining blood pressure may include: receiving a request to determine blood pressure of a first subject from a terminal, obtaining data related to heart activity of the first subject, determining a personalized model for predicting blood pressure with respect to the first subject, determining the blood pressure of the first subject using the personalized model based on the data related to heart activity of the first subject, and sending the blood pressure of the first subject to the terminal in response to the request.

Sensor apparatuses, methods of operating the sensor apparatuses, and systems including the sensor apparatuses are disclosed. Methods of analyzing electromechanical characteristics of a heart are also disclosed.

An information processing device includes a first acquisition unit that acquires biological information on a user, a first judgment execution unit that executes a first judgment on whether a first discomfort condition is satisfied or not based on first discomfort condition information specifying the first discomfort condition and the biological information, a second acquisition unit that acquires a sound signal, an acoustic feature detection unit that detects an acoustic feature based on the sound signal, a second judgment execution unit that executes a second judgment on whether a second discomfort condition is satisfied or not based on second discomfort condition information specifying the second discomfort condition and the acoustic feature, and an output judgment unit that judges whether first masking sound should be outputted or not based on a result of the first judgment and a result of the second judgment.

The process for classifying anesthetic depth includes: collecting of biological signals, conditioning of said signals, monitoring of activity of the central and autonomic systems, measurement of indexes and classification of patterns in anesthetic depth. The activity includes: i) Awake: Vigil—Ak. and recovery of verbal response—Rc. ii) Light Anesthesia: Light induction anesthesia—Li. Light recovery—Lr, Light dose, increase in drugs or patient movement (La), iii) General anesthesia: General anesthesia—Ga, one minute after the start of the surgery, and iv) Deep anesthesia: identification of the EEG burst-suppression pattern (BSP) associated with deep anesthesia.

The process for classifying anesthetic depth includes: collecting of biological signals, conditioning of said signals, monitoring of activity of the central and autonomic systems, measurement of indexes and classification of patterns in anesthetic depth. The activity includes: i) Awake: Vigil—Ak. and recovery of verbal response—Rc. ii) Light Anesthesia: Light induction anesthesia—Li. Light recovery—Lr, Light dose, increase in drugs or patient movement (La), iii) General anesthesia: General anesthesia—Ga, one minute after the start of the surgery, and iv) Deep anesthesia: identification of the EEG burst-suppression pattern (BSP) associated with deep anesthesia.

An electrode multiplexing physiological parameter monitoring ring, comprising a built-in power supply (2), a microprocessor module (1), an electrocardiogram monitoring analog front end (3), a skin conductance monitoring module (4), a first electrode (6), and a second electrode (7). The microprocessor module (1) is connected to the electrocardiogram monitoring analog front end (3) and the skin conductance monitoring module (4). The first electrode (6) and the second electrode (7) are connected to the electrocardiogram monitoring analog front end (3), and the electrocardiogram monitoring analog front end (3) processes electrocardiogram signals collected by the first electrode (6) and the second electrode (7). The first electrode (6) and the second electrode (7) are further connected to the skin conductance monitoring module (4), and the skin conductance monitoring module (4) processes skin impedance signals collected by the first electrode (6) and the second electrode (7). A coupling manner in which the first electrode (6) and the second electrode (7) are coupled to the electrocardiogram monitoring analog front end (3) is direct current coupling or alternating current coupling, and is opposite to a coupling manner in which the first electrode (6) and the second electrode (7) are coupled to the skin conductance monitoring module (4). By means of the electrode multiplexing physiological parameter monitoring ring, electrocardiogram monitoring, heart rate monitoring, and skin conductance monitoring are implemented through only two electrodes, so that the number of electrodes is reduced, and system design is simplified.

An electrode multiplexing physiological parameter monitoring ring, comprising a built-in power supply (2), a microprocessor module (1), an electrocardiogram monitoring analog front end (3), a skin conductance monitoring module (4), a first electrode (6), and a second electrode (7). The microprocessor module (1) is connected to the electrocardiogram monitoring analog front end (3) and the skin conductance monitoring module (4). The first electrode (6) and the second electrode (7) are connected to the electrocardiogram monitoring analog front end (3), and the electrocardiogram monitoring analog front end (3) processes electrocardiogram signals collected by the first electrode (6) and the second electrode (7). The first electrode (6) and the second electrode (7) are further connected to the skin conductance monitoring module (4), and the skin conductance monitoring module (4) processes skin impedance signals collected by the first electrode (6) and the second electrode (7). A coupling manner in which the first electrode (6) and the second electrode (7) are coupled to the electrocardiogram monitoring analog front end (3) is direct current coupling or alternating current coupling, and is opposite to a coupling manner in which the first electrode (6) and the second electrode (7) are coupled to the skin conductance monitoring module (4). By means of the electrode multiplexing physiological parameter monitoring ring, electrocardiogram monitoring, heart rate monitoring, and skin conductance monitoring are implemented through only two electrodes, so that the number of electrodes is reduced, and system design is simplified.

A data generation method by a computer is disclosed. First waveform data including marking information at a first position on a waveform, and acquiring second waveform data are acquired. A transformation function is specified that transforms the first waveform data to reduce the difference between a first value of a time axis for a first characteristic point in the first waveform data and a second value of the time axis for a second characteristic point, in the second waveform data, corresponding to the first characteristic point. Third waveform data are generated, in which the marking information is applied at a second position corresponding to the first position in the first waveform data, the second position being determined by using the transformation function.