Abstract: 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.

Abstract: Systems and methods for monitoring sleep are disclosed. According to an aspect, a method includes emitting light into tissue. The method also includes detecting light backscattered from the tissue. Further, the method includes determining a sleep pattern based on the backscattered light.

Abstract: Systems and methods for monitoring sleep are disclosed. According to an aspect, a method includes emitting light into tissue. The method also includes detecting light backscattered from the tissue. Further, the method includes determining a sleep pattern based on the backscattered light.

Abstract: A spirometer includes a housing, a mouthpiece coupled to the housing, and a measurement unit. The measurement unit is configured to receive air expelled by a user, and generate an electrical quantity corresponding to a peak expiratory flow or a forced expiratory volume based on the expelled air. The spirometer also includes a processing module supported by the housing, and configured to receive the electrical quantity from the measurement unit, a display coupled to the measurement unit to display an indication of the peak expiratory flow or the forced expiratory volume, and an energy harvester. The energy harvester is coupled to the measurement unit and the processing module, and is configured to receive energy from one of a group consisting of the measurement unit and an energy sensor, store the received energy in an energy storage device, and transfer the energy to the processing module.

Abstract: Systems and methods for monitoring sleep are disclosed. According to an aspect, a method includes emitting light into tissue. The method also includes detecting light backscattered from the tissue. Further, the method includes determining a sleep pattern based on the backscattered light.

Abstract: Systems and methods for monitoring sleep are disclosed. According to an aspect, a method includes emitting light into tissue. The method also includes detecting light backscattered from the tissue. Further, the method includes determining a sleep pattern based on the backscattered light.

Abstract: A spirometer includes a housing, a mouthpiece coupled to the housing, and a measurement unit. The measurement unit is configured to receive air expelled by a user, and generate an electrical quantity corresponding to a peak expiratory flow or a forced expiratory volume based on the expelled air. The spirometer also includes a processing module supported by the housing, and configured to receive the electrical quantity from the measurement unit, a display coupled to the measurement unit to display an indication of the peak expiratory flow or the forced expiratory volume, and an energy harvester. The energy harvester is coupled to the measurement unit and the processing module, and is configured to receive energy from one of a group consisting of the measurement unit and an energy sensor, store the received energy in an energy storage device, and transfer the energy to the processing module.

Abstract: Systems and methods for monitoring sleep are disclosed. According to an aspect, a method includes emitting light into tissue. The method also includes detecting light backscattered from the tissue. Further, the method includes determining a sleep pattern based on the backscattered light.