A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

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.

A system includes an electronic circuit, a memory, and a control system. The electronic circuit is coupled to a conduit. The conduit may be configured to deliver pressurized air. A portion of the electronic circuit has a first electrical property that is configured to change based at least in part on movement of the portion of the electronic circuit. The memory stores machine-readable instructions. The control system includes one or more processors configured to execute the machine-readable instructions. Data associated with the first electrical property of the electronic circuit is received. The received data is analyzed. Based at least in part on the analysis, it is determined that the first electrical property of the electronic circuit has changed. Responsive to the determination that the first electrical property of the electronic circuit has changed, it is determined that the conduit is moving or has moved.

There is described support structures for a bed, and various embodiments of a bed for use in a hospital. In an example, a support structure comprises a plurality of sections, each configured to support a respective part of a body, and a plurality of resilient members that extend in a longitudinal direction from an upper end of the support structure to a lower end of the support structure, wherein a shape and/or profile of the support structure is determined by a shape and/or profile of the resilient members.

A system for monitoring medical conditions including pressure ulcers, pressure-induced ischemia and related medical conditions comprises at least one sensor adapted to detect one or more patient characteristic including at least position, orientation, temperature, acceleration, moisture, resistance, stress, heart rate, respiration rate, and blood oxygenation, a host for processing the data received from the sensors together with historical patient data to develop an assessment of patient condition and suggested course of treatment, including either suspending or adjusting turn schedule based on various types of patient movement. Compliance with Head-of-Bed protocols can also be performed based on actual patient position instead of being inferred from bed elevation angle. The sensor can include bi-axial or tri-axial accelerometers, as well as resistive, inductive, capacitive, magnetic and other sensing devices, depending on whether the sensor is located on the patient or the support surface, and for what purpose.

The disclosure relates to a method for acquiring and for altering a configuration of a number of objects in a procedure room for planning and for collision avoidance during a medical procedure, wherein each object is represented by a virtual model, including a physical model of the object and a safety zone around the physical model. The physical model represents the configuration of the object and the safety zone represents a collision-prevention area for a movement of any of the objects during a medical procedure. The virtual models of the objects are placed at a position in a virtual model of the procedure room. Additionally, the configurations of the physical models during the medical procedure are computed and the configuration of the physical model of the corresponding object is altered when a collision during the movement is determined. The disclosure further relates to a device for executing the method.

A medical monitoring system for use in residential facilities, nursing homes, or home environments is disclosed. The system utilizes a variety of modules and wearable medical devices that convey vital patient information to a series of smart hubs which are connected to the cloud. In the event a change in medical status of a patient occurs, the health care workers receive an Alert notifying them of which specific patient needs attention. The system is monitored using a specialized dashboard.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A system for monitoring patients during a consciousness-altering therapeutic treatment session including a data collection module in electronic communication with network servers for storage of data on non-transitory computer readable media for monitoring a patient's well-being during and after the treatment session. A method of using the system in treating a patient, by continuously, continually, or at the healthcare professionals discretion monitoring the well-being of the patient during a consciousness-altering therapeutic treatment session through one or more wearable devices and a patient mobile device in electronic communication with a facilitator mobile device, and continuously monitoring the well-being of the patient after the treatment session with the wearable device.

Presented is a system and method for assessing the functional ability of a person to perform a task. The system comprises: a task identification unit adapted to identify the task to be performed by the person; and a task complexity unit adapted to obtain a task-specific complexity signal representative of a required level of functional ability to perform the identified task. A functional ability unit is adapted to obtain a functional ability signal representative of a determined functional ability of the person. An assessment unit is adapted to determine an ability of the person to perform the identified task based on the task-specific complexity signal and the functional ability signal.