There is set forth herein a system including a camera device. In one embodiment the system is operative to perform image processing for detection of an event involving a human subject. There is set forth herein in one embodiment, a camera equipped system employed for fall detection.

Disclosed is a capacitive sensor (100) for locating the presence of an individual and/or of an object, the sensor (100) including:—a first layer (C1) including at least one first electrode (E1i, i∈[1,N]) extending in a first direction (d1);—a second layer (C2) having at least one second electrode (E2j, j∈[1,M]) extending in a second direction (d2); in which the first direction (d1) is different from the second direction (d2), and in which the first layer (C1) is electrically insulated from the second layer (C2).

A load cell apparatus for use with a bed includes a housing having a top portion and a bottom portion, and a load cell device held by the bottom portion of the housing. The load cell device is structured to generate a signal having a magnitude that is proportional to a first force being applied to the load cell device. The load cell apparatus also includes a button member held by the housing in a manner wherein the button member is structured to engage the load cell device and apply the first force to the load cell device in response to a second force being applied to the top portion of the housing. Also, various systems for monitoring parameters such as weight, sleep quality, fall risk, and/or pressure sore risk that may incorporate such a load cell apparatus.

The present disclosure generally relates to user interfaces for health applications. In some embodiments, exemplary user interfaces for managing health and safety features on an electronic device are described. In some embodiments, exemplary user interfaces for managing the setup of a health feature on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described. In some embodiments, exemplary user interfaces for managing a biometric measurement taken using an electronic device are described. In some embodiments, exemplary user interfaces for providing results for captured health information on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described.

A fall detection system includes a wearing apparatus for wearing by a user and a processor connected to the wearing apparatus. The wearing apparatus is set with an inertial sensor for detecting user motion data. The processor is connected with the inertial sensor of the wearing apparatus. When the user's fall state is recognized, further obtaining the motion data of the user at the time of the stand by the inertial sensor and comparing the motion data according to a normal posture condition and/or an abnormal posture condition in a database to determine damage severity of the user.

An embodiment of the invention provides a method and system including a sensor on a vehicle and a processor connected to the sensor. The processor determines a probability of falling based on input from the sensor, whether the probability of falling exceeds a threshold, and a state of an operator of the vehicle. An actuator connected to the processor receives a signal from the processor when the probability of falling exceeds the threshold and when the state of the operator includes an impaired state. Stabilizer wheels are connected to the actuator, where the signal includes a command to deploy the stabilizer wheels.

A motion-sensing floor mat, an assembly of such floor mats, and a monitoring system with such floor mats are provided; wherein the floor mat can be joined with another such floor mat and electrically connected to a monitoring device to form the monitoring system; the monitoring device stores a queue list and a topology matrix and uses a topological algorithm to store the identification tag of each such floor mat detected into the queue list in order, to gradually establish the topology matrix for the floor mats detected; and to thereby obtain the relative positions of the floor mats detected. When any of the floor mats is subjected to pressure (e.g., when someone falls on the floor mat accidentally) and generates a sensing signal, the monitoring device can pinpoint the position of that floor mat (i.e., the location of the fall) rapidly according to the topology matrix.

A system includes a sensor configured to generate data associated with movements of a resident for a period of time, a memory storing machine-readable instructions, and a control system arranged to provide control signals to one or more electronic devices. The control system also includes one or more processors configured to execute the machine-readable instructions to analyze the generated data associated with the movement of the resident, determine, based at least in part on the analysis, a likelihood for a fall event to occur for the resident within a predetermined amount of time, and responsive to the determination of the likelihood for the fall event satisfying a threshold, cause an operation of the one or more electronic devices to be modified.

Methods and systems implement a variety of sensors, including in embodiments various combinations of EEG sensors, biochemical sensors, photoplethysmography (PPG) sensors, microphones, and accelerometers, to detect, predict, and/or classify various physiological events and/or conditions related to epilepsy, sleep apnea, and/or vestibular disorders. The events can include neuroelectrical events, cardiac events, and/or pulmonary events, among others. In some cases, the method and systems implement trained artificial intelligence (AI) models to detect, classify, and/or predict. The methods and systems are also capable of optimizing a treatment window, suggesting treatments that may improve the overall well-being of the patient (including improving pre- or post-event symptoms and effects), and/or interacting with various care providers.

An intracranial pressure monitoring device includes a housing defining a first internal chamber, a plurality of strain gauges disposed on an inner surface of a diaphragm defined by a wall of the first internal chamber, a device for generating orientation signals, and circuitry coupled to the plurality of strain gauges and to the device. The circuitry is configured to generate intracranial pressure data from signals received from the plurality of strain gauges, generate orientation data based on the orientation signals received from the device, and store the intracranial pressure data and the orientation data in a computer readable storage such that the intracranial pressure data and orientation data are associated with each other.