Embodiments are directed to identifying and measuring bodily states and feedback systems. A computer system initializes a tracking and measuring device to generate patient data related to a bodily state or feedback system of a patient. The computer system gathers the patient data using the initialized tracking and measuring device, and identifies a baseline parameter used to determine a baseline state relative to the gathered patient data. The computer system further gathers additional patient data using the initialized tracking and measuring device and compares the additional gathered patient data to the identified baseline parameter. Then, if the additional gathered patient data differs from the baseline state by a specified threshold amount, the computer system determines that a change in the patient's bodily state or feedback system has occurred and/or determines the amount of change in the bodily state or feedback systems that has occurred.

A personal protective equipment wearing detection apparatus is provided which can accurately detect the approach or contact of a person's head by use of a plurality of contact detection sensors. A personal protective equipment wearing detection apparatus 100 includes a headband contact detection sensor 110 and a chin strap contact detection sensor 120, which are mounted on a headband 92 and a chin strap 94 of a helmet 90, respectively. The headband contact detection sensor 110 and the chin strap contact detection sensor 120 are connected to a controller 103 of a detection apparatus body 101. While one of the two contact detection sensors, the headband contact detection sensor 110 and the chin strap contact detection sensor 120, outputs a contact detection signal to the controller 103, the controller 103 connects the other contact detection sensor to GND.

The present invention relates to: a device and method for assessing the risk of lonely death using a door open sensor; and a LED system for assessing the risk of lonely death. More specifically, the device for assessing the risk of lonely death using a door open sensor, according to one embodiment of the present invention, comprises: a door open recognition unit which recognizes that a door has been opened; an outside activity time calculation unit which, when the door is recognized to have been opened, and activity of a human body is not detected from the time point when the door is recognized to have been opened to a predetermined time, determines an outside activity state and calculates an outside activity duration which is the time during which the outside activity state is maintained; an inside activity time calculation unit which, when activity of the human body is detected at a first time point, and activity of the human body is detected again at a second time point which includes an idle detection period after the first time point, determines an inside activity state and calculates an inside activity duration which is the time during which the inside activity state is maintained; and a risk assessment unit which assesses the risk of lonely death by generating a probability distribution model on the basis of the outside activity durations and inside activity durations calculated during a first period, and applying, to the probability distribution model, the outside activity duration and inside activity duration calculated after the first period.

A safety circuit for a Personal Alert Safety System (PASS) device includes a safety logic circuit and an alarm circuit. The safety logic circuit is communicably coupled to the PASS device. The safety logic circuit includes a timer configured to determine a time elapsed since the timer has been last reset. The safety logic circuit is configured to switch from an off state to an on state upon receiving an activation signal from the PASS device and reset the timer upon switching to the on state, generate a trigger signal in response to the timer exceeding a time threshold, and reset the timer upon receiving a reset signal from the PASS device before the timer exceeds the time threshold. The alarm circuit is communicably coupled to the safety logic circuit and configured to generate an alarm signal upon receiving the trigger signal from the safety logic circuit.

A pressure sensing mat having first and second conductive layers and an insulative layer. The first conductive layer defines a first aperture and includes first spaced apart conductive regions and first non-conductive regions therebetween. The first spaced apart conductive regions and non-conductive regions extends in a first direction. The second conductive layer defines a second aperture and includes second spaced apart conductive regions and second non-conductive regions therebetween. The second spaced apart conductive regions and the second non-conductive regions extend in a second direction different than the first direction. The insulative layer is between the first and second conductive layers and defines a third aperture. The first, second, and third apertures are aligned with each other such that the first, second, and third apertures form a vent through the first and second conductive layers and the insulative layer.

Various embodiments provide methods, apparatus, systems, computing entities, and/or the like, for identifying deviated behavior of an individual indicated by outlying activity counts and outlying activity timings classified by a prediction interval profile generated from historical behavior data. In an embodiment, an example method comprises accessing sensor data describing behavioral activities of an individual during historical time periods and generating a prediction interval profile for the behavioral activities comprising a predicted count interval within a prediction time period for at least some behavioral activities. The method further includes receiving sensor data for the prediction time period and extracting an observed activity count and an observed activity timing for each behavioral activity. The method then includes classifying a particular behavioral activity as a behavioral deviation if the observed activity count does not satisfy the predicted count interval and/or if the observed activity timing does not satisfy the predicted timing interval.

Systems and methods for configuration for contextual response to motion-based events are disclosed. For example, a predefined event may be detected. The system may determine that a subject associated with the event is of a given type of subjects and may determine whether another person is present in the environment associated with the event to assist in providing aid. The presence of the other person may be detected, a type of the other person may be performed, and a notification may be output on a second device associated with the other person based on the type. The system may track when the other person reach an area associated with the event and may cause the first device to perform an action to assist the other person in providing aid.

A head guard is provided. The head guard includes one or more sensors as part of an sensory input and communications system. The head guard wirelessly communicates data to remote computing devices for intelligent data collection.

A security and automation unit for building, offices or homes includes multiple sensors and multiple resolvers. The resolvers include one or more of a presence resolver, an alarm resolver, a climate resolver, and an event resolver, and at least one resolver includes a neural network. The event resolver includes a self-learning module and at least one of a cognitive module and a proactive module. The self-learning module finds clusters of activation of pieces of equipment at recorded events. The cognitive module analyzes the clusters and modifies an associated scenario for at least one piece of equipment. The proactive module analyzes the clusters and creates at least one new scenario for at least one piece of equipment. The sensors include some of a movement sensor, an acoustic sensor, an image sensor, a light sensor, a CO2 sensor, a thermometer, and a humidity sensor.

Disclosed herein are systems, devices, and methods for an uncertainty-aware robot system that may perform a personalized risk analysis of an observed person. The uncertainty-aware robot system determines a recognized behavior for the observed person based on sensor information indicative of a gait of the observed person. The uncertainty-aware robot system determines an uncertainty score for the recognized behavior based on a comparison of the recognized behavior to potentially expected behaviors associated with the observed person and the environment. The uncertainty-aware robot system generates a remedial action instruction based on the uncertainty score.