Disclosed is an apparatus for recording respiratory rate of a subject. The apparatus comprises a first component to be arranged on the subject and away from nostrils of the subject, the first component comprises a battery, optionally electronics for the sensor, and electronics for transmitting respiration rate data; and a second component for being arranged in an area of the nose of the subject, the second component comprising at least one sensor for recording respiratory rate. Disclosed is also a method for recording respiratory rate of a subject with such an apparatus. The method comprises arranging the second component in an area of the nose of the subject; arranging the first component on the subject and no further than 30 centimeters from the second component; recording respiratory rate data with the second component, and sending the respiratory rate data to the first component; and sending the respiratory rate data from the first component to a monitor or a hub.

An abnormality processing system is provided capable of executing appropriate processing in cases where an abnormality occurs in a worker's living body. A management computer 300, if determining that an abnormality is present in a worker's living body, transmits an abnormality signal to an administrator terminal 100, a work device 200, a worker camera 20 and a surveillance camera 50. When receiving the abnormality signal, the administrator terminal 100 displays an image showing that an abnormality has occurred. When receiving the abnormality signal, the work device 200 stops operation. When receiving the abnormality signal, the worker camera 20 and the surveillance camera 50 transmit to the management computer 300 imaging data containing at least data of images before and after a timing at which the abnormality has occurred in the worker's living body.

Techniques and technologies for determining and enhancing productivity are described. In at least some embodiments, a system for includes a processing component operatively coupled to a memory; a productivity analyzer at least partially disposed in the memory, the productivity analyzer including one or more instructions that when executed by the processing component perform operations including: receive productivity data associated with usage of one or more productivity tools by at least one user during a time period; receive biometric data associated with one or more biometric aspects of the at least one user during the time period; analyze one or more aspects of the productivity data and the biometric data; and determine based on the analysis at least one productivity-related operation intended to enhance at least one productivity metric of the at least one user.

Biometric identification methods and apparatuses (including devices and systems) for uniquely identifying one an individual based on wearable garments including a plurality of sensors, including but not limited to sensors having multiple sensing modalities (e.g., movement, respiratory movements, heart rate, ECG, EEG, etc.).

Provided is an electronic device to monitor a user's biological measurements, where a sensor is configured to acquire a first signal from a user, and a diagnostic processor is configured to pre-process the first signal to generate a second signal, segment the second signal to form signal segments, determine at least one event location for each of the signal segments, match adjacent signal segments for feature alignment, and provide a third signal using results of the feature alignment.

A functional device is disclosed that can collect and process data/information/parameter values from one or more sensors and compares the same with one or more predefined/threshold value to suggest one or more actions and/or generate alerts/messages/suggestions to be performed by one or a combination of remote system, wearer, home automation network, healthcare provider, doctor, caretaker, among other stakeholders. Communication between the functional device, home automation server and a computational server that stores the data is also disclosed.

A computer implemented method for providing pain management using a wearable device determines a predictive model estimating an intensity level of pain as a function of at least one physiological parameter of a user of the wearable device and at least one activity of the user. The activity of the user includes one or combination of a type of the activity, a level of the activity, a location of the activity, and a duration of the activity. The method determines measurements of physiological and activity sensors of the wearable device to produce values of the physiological parameter and the activity of the user and predicts the intensity level of the pain based on the predictive model and the values of the physiological parameter and the activity of the user. The method executes actions based on the predicted intensity level of pain.

This document discusses, among other things, apparatus, systems, or methods to efficiently collect heart sound data, including detecting first heart sound information of a heart of a patient using a heart sound sensor in a first, low-power operational mode, and detecting second heart sound information of the heart using the heart sound sensor in a separate second, high-power operational mode. The operational mode of the heart sound sensor can be controlled using physiologic information from the patient, including heart sound information, information about a heart rate of the patient, or other physiologic information from the patient that indicates worsening heart failure.

In the present invention, a system and associated method is provided for monitoring vital parameters of a patient. The monitoring system includes sensors disposed on the patient and operably connected to a monitor. The parameters that are sensed by the sensors are transmitted to the monitor and compared with alarm thresholds stored within the monitor. The alarm thresholds stored within the monitor are modified by inputs supplied to the monitor regarding the particular condition(s) of the patient being monitored to provide more accurate alarm determinations for the patient. The dynamic adjustment of the alarm threshold during monitoring can be based on a set of proactive inputs to prevent and/or limit the occurrence of unnecessary or clinically irrelevant alarm conditions or a set of reactive inputs that follow immediately after an alarm event is detected, to enable medical personnel to appropriately respond to sensed alarm condition(s).

Methods and apparatus provide physiological movement detection, such as gesture, breathing, cardiac and/or gross motion, such as with sound, radio frequency and/or infrared generation, by electronic devices such as vehicular processing devices. The electronic device in a vehicle may, for example, be any of an audio entertainment system, a vehicle navigation system, and a semi-autonomous or autonomous vehicle operations control system. One or more processors of the device, may detect physiological movement by controlling producing sensing signal(s) in a cabin of a vehicle housing the electronic device. The processor(s) control sensing, with a sensor, reflected signal(s) from the cabin. The processor(s) derive a physiological movement signal with the sensing signal and reflected signal and generate an output based on an evaluation of the derived physiological movement signal. The output may control operations or provide an input to any of the entertainment system, navigation system, and vehicle operations control system.