A system includes a wearable article and a housing assembly including a receptacle defining a chamber and having an access opening providing access to the chamber to removably receive an electronic module within the chamber. The housing assembly further includes an interface having first and second electrical contacts exposed to the chamber. First and second conductive leads are connected to the electrical contacts through the bottom side of the receptacle to place the leads in electronic communication with the contacts. The housing assembly is bonded between top and bottom layers of material forming a portion of the wearable article, such that the layers are bonded to the receptacle by a bonding material.

A system for monitoring patients during a consciousness-altering therapeutic treatment session including a data collection module in electronic communication with network servers for storage of data on non-transitory computer readable media for monitoring a patient's well-being during and after the treatment session. A method of using the system in treating a patient, by continuously, continually, or at the healthcare professionals discretion monitoring the well-being of the patient during a consciousness-altering therapeutic treatment session through one or more wearable devices and a patient mobile device in electronic communication with a facilitator mobile device, and continuously monitoring the well-being of the patient after the treatment session with the wearable device.

Systems and methods for predicting problem behavior in individuals with developmental and behavior disabilities. A plurality of sensors are configured to collect multimodal data signals of a subject individual including a wearable upper body motion sensing device with a plurality of inertial measurement units (IMUs). An electronic controller is configured to receive output signals from each of IMUs and to model an upper body position of the subject individual based on the output signals from the IMUs. A trained machine-learning model is then applied by providing an input data set that includes multimodal signal data (e.g., including signal data from at least one IMU) and/or features extracted from the multimodal signal data. The machine-learning model is trained to produce as output an indication of whether a precursor to the problem behavior is detected and, in response to detecting the precursor, a notification (or alarm) is generated.

A method for guiding deep breathing may include receiving a request from a user to initiate a deep breathing exercise on a user-controlled device. The method may include monitoring deep breathing using one or more sensors on an ear-worn device in response to initiating the deep breathing exercise. Examples of sensors include at least one of a motion detector, a microphone, a heart rate sensor, and an electrophysiological sensor. The method may further include initiating an end to the deep breathing exercise. The method may be used with various hearing systems including an ear-worn device and optionally a user-controllable device, such as a smartphone.

The present invention relates to a method for contactlessly measuring the amount of menstrual blood in a menstrual cup. The amount of menstrual blood that has been stored in a menstrual cup can be simply measured by using a contactless sensor means, thereby enabling the user to periodically check the amount of menstrual blood. This enables early detection and treatment of uterine fibroid, which may even lead to hysterectomy.

Trained machine learning models can be used for analysis of signals obtained through an in-ear or on-body device. Signals can be analyzed to determine information related to activities such as eating, chewing, drinking, coughing, or sneezing. In addition, data from an in-ear thermometer or other data sensors can be analyzed in conjunction with the machine learning models to provide data or recommendations to a user on a user device or initiate an action.

A blood pressure measurement device measures a blood pressure of a subject by a blood pressure measurement unit, detects a body sound of the subject during blood pressure measurement by a sound detection unit. The measured blood pressure and the detected body sound are recorded in association with each other by time information. The factor for the increase of measured blood pressure value can be specified by showing the chronological blood pressure measurement result along with checking the presence or absence of a body sound such as snoring etc.

A garment includes a securing portion operable to removably secure the garment about an abdomen of a wearer; a sensor attachment portion pivotably attached to the securing portion, the sensor attachment portion including a sensor mount configured to receive and retain a sensor therein; and a sensor received in the flexible sensor mount; the securing portion and the sensor attachment portion being configured such that, when the securing portion is secured around the back of a wearer, the sensor attachment portion pivots with respect to the securing portion so as to self-position the sensor attachment portion across (a) an upper portion of the wearer's abdomen or (b) a lower portion of the wearer's abdomen; the flexible sensor mount being configured to orient a sensor received therein to be flush with skin of the wearer when the garment is worn by the wearer and to self-adjust during the course of pregnancy.

A system includes a collar that is worn around a neck of the user. A stimulator is coupled to the collar such that the stimulator is positioned adjacent to an airway of the user. The sensor is coupled to the collar and configured to generate data associated with the airway of the user. The memory is coupled to the collar and storing machine-readable instructions. The control system is coupled to the collar and includes one or more processors configured to execute the machine-readable instructions to determine, based at least on an analysis of the generated data, that the user is currently experiencing an apnea event. In response to the determination, the control system causes the stimulator to provide electrical stimulation, at a first intensity level, to one or more muscles of the user that are adjacent to the airway to aid in stopping the apnea event.

Disclosed in the present disclosure is a method, system and apparatus for prediction, estimation and prevention of occurrence of agitation episode in a subject predisposed to agitation. The method comprises receiving, from a first monitoring device attached to a subject, physiological data of sympathetic nervous system activity in the subject and activity data of the subject; receiving, from a computing device, a plurality of indications associated with a plurality of agitation episodes of the subject; analyzing, using at least one machine learning model, the physiological data, the activity data, and the plurality of indications to determine a probability of an occurrence of an agitation episode of the subject; and sending a signal to a second monitoring device to notify the second monitoring device of the probability of the occurrence of the agitation episode of the subject such that treatment can be provided to the subject to decrease sympathetic nervous system activity in the subject.