Described herein are head orientation training devices for sports training and systems including such devices. A head orientation training device (HOTD) can include a position sensor configured to sense a tilt of the device, continually, while the device is activated. The HOTD can also include a computing device, configured to retrieve the tilt of the device from the position sensor, repeatedly, while the apparatus is activated. Also, the computing device of the HOTD can be configured to activate an alarm (such an audible or a visual alert) when the tilt of the apparatus exceeds a tilt threshold. The tilt threshold can be user definable as well.

Controlled-environment facility resident behavioral and/or health monitoring may employ controlled-environment facility resident wearables each having a band configured to be affixed around a portion of a controlled-environment facility resident, irremovable by the resident and may include sensor(s) configured to measure biometric(s) of the controlled-environment facility resident and one or more physical parameter(s) experienced by the wearable, with a transmitter transmitting the biometric(s) and/or the physical parameter(s) to a controlled-environment facility management system. The controlled-environment facility management system may predetermine one or more normal input levels of the biometric(s) and/or physical parameter(s), receive the transmitted biometric(s) and/or physical parameter(s), determine whether received biometric(s) and/or physical parameter(s) rises above or falls below the predetermined normal input level(s), and alert controlled-environment facility personnel and/or law enforcement when received physical parameter(s) and/or received biometric(s) rise above or fall below the predetermined normal input level(s).

A system for detecting and discriminating the severity of a fall includes a mobile device configured to communicate a network, a notification module, and a wearable device configured to communicate with the mobile device, the wearable device including a fall monitor and an activity log resident on the wearable device, where the fall monitor is configured to record detected movement on the activity log. The notification module is configured to effect a selectable setting of a rate of communication between the mobile device and the wearable device based on at least part of a predetermined pattern of a fall discriminator within the activity log, where the selectable setting defines a predetermined period of communication between the mobile device and the wearable device. The fall discriminator is configured to determine when the activity log includes a notable fall event based on the predetermined pattern.

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.

A wearable badge for an employee that records and transmits audio from client interactions with the professional, comprising two microphones and two microphone channels that focus one microphone on the speech of the employee and the other microphone on the speech of the customer, making diarizing easier. The wearable badge also comprises a module to determine whether or not the employee is maintaining an appropriate social distance with customers.

A system may obtain a set of features characterizing a segment of inertial measurement unit (IMU) data generated by an IMU of an ear-wearable device. The system may apply a machine learning model (MLM) that takes the features characterizing the segment of the IMU data as input. The system may determine, based on output values produced by the MLM, whether a user of the ear-wearable device has potentially been subject to physical abuse. The system may then perform an action in response to determining that the user of the ear-wearable device has potentially been subject to physical abuse.

A monitoring system a user activity sensor to determine patterns of activity based upon the user activity occurring over time.

There is provided a method and apparatus for detecting a fall event of the user. In particular, the method includes collecting data associated with activities of the user from a plurality of sensors and distributing the collected data to data sub-windows using signal windowing and segmentation, the data sub-windows indicative of a pre-fall moment, a fall moment, and a post-fall moment. The method further includes extracting a plurality of features from one or more of the data sub-windows and determining whether the event is a fall event at least in part based on the extracted features. The determination of whether the event is a fall event can further be determined by applied support vector machine (SVM) technique. The developed machine learning based methods may be substantially optimum in terms of a trade-off between accuracy and complexity of the evaluation. The method further includes multiple rejection filters in order to aid with the prevention of false alarms due to fall-like activities of daily living (ADLs). The method further includes a personalization process to update the machine learning based methods associated with each user.

One aspect of the apparatus comprising, a sensor configured to acquire a biological signal of a user, and a controller configured to, determine whether the biological signal is continuously outside a predetermined range for a first time period, after determining that the biological signal has been continuously outside the predetermined range for the first time period, then determine whether the biological signal is inside the predetermined range, and activate an alarm if the controller has determined that (i) the biological signal has been outside the predetermined range for the first time period, and (ii) the biological signal has been continuously inside the predetermined range for a second time period, the second time period being longer than the first time period.

Avalanche transceiver, and associated systems and methods are disclosed herein. In one embodiment, a method for identifying a location of a victim buried in an avalanche includes: emitting a signal by a transmitting transceiver of the victim; receiving the signal by a receiving transceiver; and identifying an orientation from the receiving transceiver to the victim based on constructing a straight line from the receiving transceiver to the transmitting transceiver.