A system for detecting an anomalous event in a person includes a body in contact with a skin surface of a person; a heat source for heating the skin surface to a target temperature; a skin temperature sensor for measuring a temperature of the skin surface in contact with the heat source; a blood volume sensor for measuring a blood volume of the skin surface; and a hardware processor communicatively coupled to the heat source, the blood volume sensor, the skin temperature sensor, and an environmental temperature sensor. The hardware processor is configured to receive a baseline blood volume signal, output a heating signal to the heat source to initiate a heating cycle, receive a second blood volume signal from the blood volume sensor, compare the second blood volume signal to the baseline blood volume signal, and determine whether an anomalous biologic event has occurred.

An exit prediction system for a support apparatus receives data inputs from one or more force sensors without zeroing the one or more force sensors. Changes in the data inputs are detected to determine whether the detected changes indicate a movement trend. An exit prediction is determined based at least partially on the movement trend, and without combining the data inputs from the one or more force sensors to determine the occupant's weight. A notification is generated based on the exit prediction.

A cardiopulmonary resuscitation (CPR) device for performing automatic defibrillation and chest compressions on a patient and method for using same. The CPR device having a balloon configured to inflate/deflate, a belt configured to securely strap around a chest of a patient, a pair of electrode pads configured to deliver shock energy from a shock source, and, optionally, a pulse oximeter sensor. The CPR device is in electrical communication with a CPR defibrillator/ECG computer system that is configured to control the CPR device.

A pain-monitoring device and method according to an embodiment of the present disclosure is a pain-monitoring device for obtaining information related to a pain of a user and providing a service of monitoring the pain of the user, includes: an input unit sensing pain-related input of the user; a display unit outputting pain-related information; and a control unit controlling the input unit and the display unit, in which the input unit includes: a touch input unit sensing touch input of the user; and a pressure measurement unit measuring pressure input of the user, and the control unit creates user-input pain information in accordance with the sensed pressure input and touch input.

A patient monitoring system comprises a contactless monitoring unit having a contactless patient monitor and operable to communicate with equipment in a patient room and components of hospital information system. The patient monitoring system implements methods for detecting and optimizing signals from a patient supported on a patient support apparatus. The patient monitoring unit includes a power source and a controller. The contactless patient monitor includes a first detector, an emitter, and a controller. The controller processes signals from the first detector and vary the operation of the emitter to change the environment in the field of the detector such that the signals detected by the first detector are optimized.

A multifunctional personal health monitor with an activity tracker embedded into a pet leash is provided. The energy of a pet pulling the leash cord is converted to an electrical power to run and to analyze operation of multiple biometric sensors embedded into the leash. The physical activities of the pet and its owner may be tracked. The obtain biometric information may be wirelessly transmitted for additional processing or an emergency call can be initiated. The generated by pet movement electrical power may be used to charge various external devices.

A system comprising a remotely programmable micromonitor with a wireless sensing system-on-module (SOM), one or more sensors to detect one or more conditions in a subject by monitoring one or more parameters associated with the conditions by comparing any monitored parameter to a baseline measurement of the monitored parameter from the subject, a plurality of sensors corresponding to a monitored parameter and connected to the micromonitor to convey measurements of all monitored parameters, the sensors including at least one of a non-optical pulse wave sensor or an electrocardiogram (ECG) sensor, a communications module capable of communicating with a wireless technology, wherein the module can send an alert signal to the subject or an attending physician or a remote service center or any other subject, and one or more algorithms for monitoring conditions and/or for predicting conditions, including at least one of a fall detection or fall prediction algorithm.

A mechanism is provided in a data processing system to implement a multi-sensor health monitoring platform. The mechanism applies a machine learning model to predict patient needs and patient activity trends based on physiological features and activity features of the patient. The mechanism applies the machine learning model to predict energy requirements for a plurality of medical sensors based on the predicted patient needs and patient activity trends. The mechanism schedules recharging of the plurality of medical sensors based on the predicted energy requirements and identifying one or more sensors to set to an activate state based on the predicted patient needs and patient activity trends. The mechanism collecting sensor data from the one or more sensors and applies the machine learning model to generate a point-of-care recommendation based on the collected sensor data.

Device and methods for a wearable medical device are disclosed. The device and methods use an on-board mobile system to alert emergency services when the user is in cardiovascular distress. The device takes advantage of newly miniaturized electrocardiograph, pulse oximetry sensors, mutual reinforcement and anomaly detection algorithms. Electrocardiograph waveforms are recorded digitally for physician review with emphasis on critical events. In the occurrence of a immediate critical-need cardiac event, the system will contact emergency services (EMS) for assistance. The system is a biometric monitoring system that implements key concepts of cardiovascular monitoring through pulse oximetry and electrocardiography (ECG). The system implements key concepts of ECGs and active/capacitive electrodes to produce a wireless network of (individually isolated) ECG nodes that can produce a system ranging from 3 to 16 leads.

A user, such as an elderly person, may be assisted by an assistance device in his or her caregiving environment that operates in conjunction with one or more server computers. The assistance device may execute a schedule of assistance actions where each assistance action is associated with a time and is executed at that time to assist the user. An assistance action may present an input request to a user, process a voice input of the user, and analyze the voice input to determine that the voice input corresponds to a negative response event, a positive response event, or a non-response event. Based on the categorization of one or more voice inputs as negative response events, positive response events, or non-response events, it may be determined to notify a caregiver of the user, for example where the user has not responded to a number of assistance actions.