A wearable device and a method of operating the same are provided. The wearable device includes a shoe assembly, a plurality of pressure sensors, a processing circuit and an alarm module. The plurality of pressure sensors are disposed on the shoe assembly and configured to generate a plurality of pressure sensing values. The processing circuit is configured to calculate a center of gravity coordinate according to the plurality of pressure sensing values and coordinates of the plurality of pressure sensors, and generate a determination result according to the center of gravity coordinate. The alarm module is configured to output an alarm signal to perform an alarm function.

An electronic device for gesture recognition, includes a processor operably connected to a transceiver. The transceiver is configured to transmit and receive signals for measuring range and speed. The processor is configured to transmit the signals, via the transceiver. in response to a determination that a triggering event occurred, the processor is configured to track movement of an object relative to the electronic device within a region of interest based on reflections of the signals received by the transceiver to identify range measurements and speed measurements associated with the object. The processor is also configured to identify features from the reflected signals, based on at least one of the range measurements and the speed measurements. The processor is further configured to identify a gesture based in part on the features from the reflected signals. Additionally, the processor is configured to perform an action indicated by the gesture.

Training a machine learning neural network (MLNN) in radiowave based monitoring of fall characteristics in diagnosing injury. The method comprises receiving, in a first set of input layers of the MLNN, from a millimeter wave (mmWave) radar sensing device, a set of mmWave radar point cloud data representing fall attributes associated with a subject, each of the first set associated with a respective fall attribute; receiving, at a second set of input layers of the MLNN, a set of personal attributes of the subject, training a MLNN classifier based on supervised training that establishes a correlation between an injury condition of the subject as generated at the output layer, the mmWave point cloud data, and personal attributes; and adjusting an initial matrix of weights by backpropagation to increase correlation between the injury condition, the mmWave point cloud data, and the personal attributes.

According to an embodiment, a method of processing acceleration information by a wearable device is provided, the method including: acquiring the acceleration information indicating acceleration according to movement of the wearable device; acquiring a plurality of acceleration characteristics including a plurality of characteristics of a power spectrum of the acceleration and a range of the acceleration on the basis of the acceleration information; determining characteristic values according to two characteristics determined according to a type of a disease to be monitored among the plurality of acceleration characteristics; and providing an alarm signal in response to the characteristic value falling within an abnormality range.

A management system for managing a walk training apparatus according to one aspect of the present disclosure includes: a state detecting portion configured to detect a loaded state in which the user applies a load to the walk training apparatus during use of the walk training apparatus; an evaluation value calculating portion configured to calculate an evaluation value based on which the load applied to the walk training apparatus by the user is evaluated; and a timing determination portion configured to, in a case where the evaluation value is equal to or more than a threshold associated with the walk training apparatus, determine that a timing of maintenance of the walk training apparatus has come.

The present specification discloses systems and methods of patient monitoring in which multiple sensors are used to detect physiological parameters and the data from those sensors are correlated to determine if an alarm should, or should not, be issued, thereby resulting in more precise alarms and fewer false alarms. Electrocardiogram readings can be combined with invasive blood pressure, non-invasive blood pressure, and/or pulse oximetry measurements to provide a more accurate picture of pulse activity and patient respiration. In addition, the monitoring system can also use an accelerometer or heart valve auscultation to further improve accuracy.

An electronic device includes a housing sidewall defining an opening and a display component, such as a display cover, disposed in the opening to form a gap between the housing sidewall and the display component. In at least one example, the cavity is defined by the sidewall and the display cover with the cavity in fluid communication with an external environment through the gap. In at least one example, an epoxy component at least partially defines the cavity and can be in direct contact with the housing sidewall.

An electronic device includes a housing sidewall defining an opening and a display component, such as a display cover, disposed in the opening to form a gap between the housing sidewall and the display component. In at least one example, the cavity is defined by the sidewall and the display cover with the cavity in fluid communication with an external environment through the gap. In at least one example, an epoxy component at least partially defines the cavity and can be in direct contact with the housing sidewall.

The invention provides a body-worn system that continuously measures pulse oximetry and blood pressure, along with motion, posture, and activity level, from an ambulatory patient. The system features an oximetry probe that comfortably clips to the base of the patient's thumb, thereby freeing up their fingers for conventional activities in a hospital, such as reading and eating. The probe secures to the thumb and measures time-dependent signals corresponding to LEDs operating near 660 and 905 nm. Analog versions of these signals pass through a low-profile cable to a wrist-worn transceiver that encloses a processing unit. Also within the wrist-worn transceiver is an accelerometer, a wireless system that sends information through a network to a remote receiver, e.g. a computer located in a central nursing station.

An electrocardiography monitor is provided. A sealed housing includes one end wider than an opposite end of the sealed housing. Electronic circuitry is provided within the sealed housing. The electronic circuitry includes an electrographic front end circuit to sense electrocardiographic signals and a micro-controller interfaced to the electrocardiographic front end circuit to sample the electrocardiographic signals. A buzzer within the housing outputs feedback to a wearer of the sealed housing.