A wearable device and a system that includes the wearable device is provided. The wearable device includes at least one sensor configured to sense a characteristic of a user, a communication interface configured to obtain a first identifier of a vehicle or equipment, and a controller. The controller is configured to monitor the user based on the first identifier or send the first identifier to a monitoring system; determine whether there is a harm possibly occurring to the user of the wearable device based on at least one output from the at least one sensor, or send the at least one output to the monitoring system via the communication interface; and output, after the harm is determined to be possibly occurring, an alarm based on receiving confirmation from the user, or based on not receiving any confirmation from the user within a predetermined amount of time.

A mount for a device configured to monitor the movements or other activities of patient. Aspects include a monitoring unit and base, where the base may further include a pad with one or more pins extending into the base. The pad may be positioned inside a garment worn by a patient, the pins passing through the garment and electrically connecting to circuits in the fabric of the garment (e.g. a sock worn by the patient). The circuits may include sensors which are response to changes in pressure caused by patient movement. Output from the sensors may be carried by the circuits in the garment to the pins in the pad, and from there through the garment and into the base and the monitoring unit for processing and reporting to caregivers as needed.

A garment is intended to identify a danger situation for the user and react. The garment comprises an emergency device provided with sensors. Furthermore, the emergency device comprises an electronic processing unit and a supervisor and communication unit. The supervisor and communication unit, after being informed of the danger situation by the electronic processing unit, monitors the user by means of the sensors and assesses the level of user activity in order to decide or not to call for further assistance.

A method, system, apparatus, and/or device that may include: determining, by a processor, that an alert event has occurred; determining, by the processor, a level of the alert event, wherein the level of the alert event is a caution alert level, an urgent alert level, or a critical alert level; determining, by the processor, an initial alert activity associated with the caution alert level, the urgent alert level, or the critical alert level; performing, by the processor, the initial alert activity receiving, from an input device, an updated alert activity associated with the caution alert level, the urgent alert level, or the critical alert level; and in response to that the initial alert activity conflicting with the updated alert activity, maintaining, by the processor, using the initial alert activity associated with the caution alert level, the urgent alert level, or the critical alert level.

Systems, devices, and methods for remote monitoring and managing of patients with chronic pain are discussed. A remote monitoring system comprises a cloud-computing device and a remote device. The cloud-computing device receives patient data including physiological or functional information sensed by sensors, and provides on-demand cloud-based services including establishing a correspondence between one or more physiological or functional states and one or more pain levels, detecting patient physiological or functional state, predicting a pain level, detecting a patient behavior, generating a recommendation for adjusting sensor operations based on the patient behavior, and storing patient data and other information in a cloud storage. The remote device can access the cloud storage and the cloud-based services, provide the stored information to an authorized user or the patient, control an implantable device to initiate or adjust a neuromodulation therapy, or adjust sensor operations.

A method and system for activity classification. A pressure sensor receives input data resulting from physical activity of a subject performing an activity. The input data includes pressure data from at least one pressure sensor, and may include other data acquired through other types of sensors. A deep learning neural network is applied to the input data for identifying the activity. The neural network is trained with reference to training data from a training database. The training data may include empirical data from a database of previous data of corresponding activities, synthesized data prepared from the empirical data or simulated data. The training data may include data from physical activity of the subject being monitored by the system. Different aspects of the neural network may be trained with reference to the training data, and some aspects may be locked or opened depending on the application and the circumstances.

In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

A system for monitoring health and safety of workers in a manufacturing facility is presented. The system includes a user interface, a set of sensors, a database, management software and/or a health monitoring system, among other components. The system is configured to monitor health of workers using biometric data gathered by the set of sensors. In one or more arrangements, the system also tracks the position and motion of the worker. In one or more arrangements, the data gathered is aggregated in a database for datamining purposes so as to facilitate health monitoring and mitigation of identified illness. The system may be configured to screen and identify workers who are not in normal health. The system may be configured to screen workers health when clocking into or out of the time keeping system. The system may be configured to perform contact tracing.

According to an aspect, there is provided a computer-implemented method for evaluating movement of a subject. The method comprises obtaining a first signal representing measurements of the subject from a first sensor; processing the first signal to determine a quality measure for the first signal; determining if the determined quality measure meets a first criterion; if the determined quality measure meets the first criterion, determining values for a plurality of features in a first feature set, the first feature set comprising one or more first features to be determined from the first signal, and evaluating the movement of the subject based on the values for the plurality of features in the first feature set; and, if the determined quality measure does not meet the first criterion, determining values for one or more features in a second feature set, wherein the one or more features in the second feature set are a subset of the plurality of features in the first feature set and the second feature set does not include at least one of the one or more first features in the first feature set, and evaluating the movement of the subject based on the values for the one or more features in the second feature set. A corresponding apparatus and computer program product are also provided.

The present disclosure relates to an emergency management system configured to initiate an emergency request: the emergency management system comprising: a personal computing device configured to gather vital data of a user, the personal computing device comprising at least one communication interface operable to communicate with at least one of an external electronic device and an emergency service provider, an electronic storage configured to store personal data of the user, at least one processor connectable to the electronic storage, the at least one processor being operable: to derive an emergency level indicator on the basis of the personal data and the gathered vital data, and p1 to generate an emergency request and to transmit the emergency request to the emergency service provider on the basis of the emergency level indicator.