Abstract: The disclosure deals with a system and method for inducing sleep loss in animal test subjects, such as rats. A sleep deprivation chamber uses a DC Servo motor with a controller to cause a bar to sweep across the rodent cage floor. The system is programmed to sweep the bar across the floor of the rodent cage at varying intervals. The maximum speed at which the bar sweeps the entire rodent cage is within 3 seconds. The chamber is designed such that it can structurally accommodate a receiver and record EEG/EMG telemetrically in animals that have been implanted with sleep transmitters. During the sleep deprivation protocol, food and water are available to animals in the chamber at all times. The chamber is also designed to fit a standardized rodent (e.g., rat or mouse) cage, and plural cages such as an 8-chamber sleep restriction device can be simultaneously operated.

Abstract: The present disclosure provides a wearable computing device. The wearable computing device includes one or more sensors that output sensor data. The wearable computing device includes a machine-learned smoking gesture detection model trained to detect a smoking gesture based on the sensor data. The wearable computing device includes one or more processors and one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include inputting the sensor data into the machine-learned smoking gesture detection model. The operations include receiving, as an output of the machine-learned smoking gesture detection model, a gesture classification that indicates whether the sensor data is indicative of the smoking gesture.

Abstract: The present disclosure provides a wearable computing device. The wearable computing device includes one or more sensors that output sensor data. The wearable computing device includes a machine-learned smoking gesture detection model trained to detect a smoking gesture based on the sensor data. The wearable computing device includes one or more processors and one or more non-transitory computer-readable media that store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include inputting the sensor data into the machine-learned smoking gesture detection model. The operations include receiving, as an output of the machine-learned smoking gesture detection model, a gesture classification that indicates whether the sensor data is indicative of the smoking gesture.