A system and method for measuring vital signs and motion from a patient comprising a plurality of sensors, each comprising a processor and analog-to-digital converter configured to generate the physiologic data waveform(s) from the sensor as synchronized, separately resolvable digital data comprising a header indicating the sensor from which the digital data originates, and to transmit the physiologic data waveform(s) to a processing system via a cable comprising a terminal connector that reversibly mates with one of a plurality functionally equivalent of connectors to operably connect the sensor to the processing system. The processing system receive sthe physiologic data waveforms and determines therefrom one or more vital signs for the individual, which are transmitted to a remote vital sign monitor.

A blood pressure measurement system comprising: a heart reference sensor (HRS) including a bladder for mounting proximate the patient's heart level, tubing, and a pressure sensor; a finger cuff attachable to a patient's finger; and a blood pressure measurement controller coupled to the HRS and the finger cuff to perform blood pressure measurement functions. The pressure sensor is located at approximately the same height level of the finger cuff and the tubing extends from the bladder of the HRS to the pressure sensor, the bladder of the HRS including liquid in fluid communication with liquid in the tubing connected to the pressure sensor at the patient's finger level such that gravity generated pressure differences between the patient's heart level and finger level are measurable by the pressure sensor of the HRS to be subtracted from the blood pressure measurement, wherein the tubing is non-plasticized tubing or chemically inert tubing.

Described herein are assistant robots that anticipate needs of one or more people (or animals). The assistant robots may recognize a current activity, knowledge of the person's routines, and contextual information. As such, the assistant robots can provide or offer to provide appropriate robotic assistance. The assistant robots can learn users' habits or be provided with knowledge regarding humans in its environment. The assistant robots develop a schedule and contextual understanding of the persons' behavior and needs. The assistant robots may interact, understand, and communicate with people before, during, or after providing assistance. The robot can combine gesture, clothing, emotional aspect, time, pose recognition, action recognition, and other observational data to understand people's medical condition, current activity, and future intended activities and intents.

Described herein are assistant robots that observe signs of core health, health dangers, and/or signs of medical distress in a home or at work. As such, the assistant robots can take actions to prevent dangerous situations, diagnose health problems, respond to requests for help, and provide regular treatments or analysis of a person's medical state. The assistant robots can learn users' habits or be provided with knowledge regarding humans in its environment. The assistant robots develop a schedule and contextual understanding of the persons' behavior and needs. The assistant robots may interact, understand, and communicate with people before, during, or after providing assistance. The robot can combine gesture, clothing, emotional aspect, time, pose recognition, action recognition, and other observational data to understand people's medical condition, current activity, and future intended activities and intents.

Described herein are assistant robots that observe signs of core health, health dangers, and/or signs of medical distress in a home or at work. As such, the assistant robots can take actions to prevent dangerous situations, diagnose health problems, respond to requests for help, and provide regular treatments or analysis of a person's medical state. The assistant robots can learn users' habits or be provided with knowledge regarding humans in its environment. The assistant robots develop a schedule and contextual understanding of the persons' behavior and needs. The assistant robots may interact, understand, and communicate with people before, during, or after providing assistance. The robot can combine gesture, clothing, emotional aspect, time, pose recognition, action recognition, and other observational data to understand people's medical condition, current activity, and future intended activities and intents.

There is provided a device comprising a blood pressure sensor for sensing blood pressure and a method for controlling the device. An angle of the device with respect to the direction of gravity is determined (202) and a location of one or more features of the user holding the device is identified (204). A height of the blood pressure sensor relative to a heart level of the user is determined based on the determined angle of the device with respect to the direction of gravity and the identified location of the one or more features of the user (206). The device is controlled based on the determined height of the blood pressure sensor relative to the heart level of the user (208).

The invention provides a system and method for measuring vital signs and motion 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 method, and a related device, for obtaining the blood pressure of a person. The method comprising steps of providing a light source (101), and an optical sensor (103) configured to detect light from the light source which has propagated through the wrist of a wearer of the device. The amount of light propagating through the wrist depends on the amount of blood in the wrist. Blood pressure is then observed by monitoring the difference in the amplitude of blood pulsation within the wrist when the wrist is lifted above heart level, and when the wrist is lowered below heart level.

A device for non-invasively measuring at least one parameter of a cardiac blood vessel in a patient comprises at least one light source that directs light at a tissue site on the patient; at least one photodetector adapted to receive light emitted by the light source and generate an output based on the received light, the output of said photodetector being correlated with a parameter of the blood vessel; and at least one probe for facilitating delivery of light from the light source to the tissue site, and receipt of light by the photodetector. The device may include a height sensor to adapt it for use to determine central venous pressure, or the configuration of light source(s) and photodetector(s) may be adapted to permit the device to provide attenuation correction in the determination of venous blood oxygenation.

An embodiment of the invention provides a method of estimating a body temperature of an individual where physiological data is received from at least one sensor 510. Environmental data is received and the physiological data and the environmental data are input into a model. The model generates an estimated body temperature and an estimated physiological condition based on the physiological data and the environmental data. A processor 520 compares the estimated physiological condition to a measured physiological condition in the physiological data. A controller 530 modifies at least one parameter in the model when the difference between the estimated physiological condition and the measured physiological condition is above a threshold.