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.

Fall detection systems and methods use radar chips to scan monitored regions such that data obtained by the scanning radar chip are processed to identify targets within the monitored region. Targets are tracked and profiled indicating their posture and fall detection rules are applied. Standard energy profiles and time dependent energy profiles are generated for various segments of the monitored region and compared to the current energy profile for each target segment of the monitored region. Anomalies are detected, false fall alerts filtered out and verified fall alerts are generated.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving a video that includes a depiction of a body of a user; detecting a plurality of skeletal joints of the body depicted in the video; tracking movement of the plurality of skeletal joints across a set of frames of the video; and smoothing the movement of a first set of the plurality of skeletal joints between frames in the first set of frames independently of smoothing movement of a second set of the plurality of skeletal joints in the first set of frames.

An athlete wearing footwear measures jump heights with a motion sensor mounted on the footwear over toes of the athlete. By sensing vertical jump start motions the sensor detects jump start and finish times of −4 g start and −4 g landing. The sensor, a body wearable mems sensor developed by JAWKU, L.L.C., has a previously installed generic factory scale calibration factor. The athlete replaces this calibration factor with a new calibration scale factor selecting an “absolute” external reference device which measures jump height. This device measures several jump heights then inputted to an algorithm app in the sensor to calculate the new calibration scale factor customized to the actual athlete. The motion sensor has built in programming apps to periodically receive an upgraded factory scale calibration factor which upgrade is based on an ever increasing data pool of jump heights. The updated factory calibration factor is then again replaced by the athlete personally taking several new measured jumps which jump heights are in turn inputted to the sensor. The progress made in evolving jumping skills based on training and specific conditioning exercises can thus be motion sensor evaluated.

A body motion determination system (100) configured to determine whether or not a subject (S) on a bed (BD) has a body motion includes: a plurality of load detectors (11, 12, 13, 14) each configured to detect the load of the subject on the bed; a respiratory waveform obtaining unit (32) configured to obtain a respiratory waveform of the subject based on a temporal variation of the load of the subject detected by each of the plurality of load detectors; and a body motion determining unit (33) configured to determine whether or not the subject has the body motion based on a comparison between a first threshold value and a standard deviation of the temporal variations in the load of the subject detected by at least one of the plurality of load detectors. The body motion determining unit is configured to compensate the standard deviation to be used in the comparison by an amplitude of the respiratory waveform.

The present invention provides methods and systems for enhancing clinical safety of psychoactive therapies (e.g., 5-HT2A agonists (e.g., LSD and psilocybin), dissociatives, and empathogens) when administered in a clinical treatment setting. In particular, the invention provides methods and systems for monitoring a patient and an attendant, e.g., via an access module capable of relaying session data and/or deriving a patient response metric.

A monitoring system can protect the privacy of a treatment recipient while monitoring the treatment recipient being treated. A transmitter transmits a beacon signal. A beacon detector detects an RSSI(2) of the beacon signal. A monitoring device includes an imaging element, an open-close body, a beacon detector, an obtainer, and an open-close body controller. The imaging element captures an image of a treatment recipient being treated by a treatment provider through an opening. The open-close body opens and closes the opening. The beacon detector detects an RSSI(1) of the beacon signal. The obtainer obtains the RSSI(2) detected by the beacon detector. The open-close body controller controls opening and closing of the open-close body based on the RSSI(1) detected by the beacon detector and the RSSI(2) obtained by the obtainer.

Aspects of the subject disclosure may include, for example, monitoring a communication session in which a user participates, the user being at a location; obtaining sensor information indicative of a physical environment in a vicinity of the location; determining, based at least in part upon the sensor information, whether a person other than the user is in the physical environment, resulting in a determination; and responsive to the determination being that the person is in the physical environment: categorizing, based at least in part upon the sensor information, the person into one class of a plurality of classes of people; generating an alert, the alert indicating to which class the person has been categorized; and providing the alert via the communication session to a communication device being used by the user. Other embodiments are disclosed.

According to one embodiment, a proficiency determination apparatus includes a processing circuit. The processing circuit acquires first time-series data about biological information of a worker in a predetermined period. The processing circuit calculates second time-series data about a physiological index indicating a mental stress on the worker by analyzing the first time-series data. The processing circuit calculates an appearance condition of the physiological index by analyzing the second time-series data. The processing circuit determines a proficiency of the worker based on the appearance condition of the physiological index.

A vital information acquisition apparatus includes an ultra-wideband millimeter-wave radar system which includes at least one transmitting antenna and at least one receiving antenna and is configured to transmit ultra-wideband millimeter-waves to a subject and receive ultra-wideband millimeter-waves reflected by the subject, and a controller includes circuitry that converts a plurality of received ultra-wideband millimeter-waves to radar signals reflected by the subject, stores the radar signals, calculates the differential signals among the radar signals at each position, calculates the intensity of the differential signals at each position, and estimates respiratory intervals, heartbeat intervals and position of the subject.